Internet Research Task Force (IRTF)                  K. Pentikousis, Ed.
Request for Comments: 7476                                          EICT
Category: Informational                                        B. Ohlman
ISSN: 2070-1721                                                 Ericsson
                                                              D. Corujo
                                                 Universidade de Aveiro
                                                              G. Boggia
                                                    Politecnico di Bari
                                                               G. Tyson
                                       Queen Mary, University of London
                                                              E. Davies
                                                 Trinity College Dublin
                                                            A. Molinaro
                                                                  UNIRC
                                                                 S. Eum
                                                                   NICT
                                                             March 2015


          Information-Centric Networking: Baseline Scenarios

Abstract

  This document aims at establishing a common understanding about a set
  of scenarios that can be used as a base for the evaluation of
  different information-centric networking (ICN) approaches so that
  they can be tested and compared against each other while showcasing
  their own advantages.  Towards this end, we review the ICN literature
  and document scenarios which have been considered in previous
  performance evaluation studies.  We discuss a variety of aspects that
  an ICN solution can address.  This includes general aspects, such as,
  network efficiency, reduced complexity, increased scalability and
  reliability, mobility support, multicast and caching performance,
  real-time communication efficiency, energy consumption frugality, and
  disruption and delay tolerance.  We detail ICN-specific aspects as
  well, such as information security and trust, persistence,
  availability, provenance, and location independence.

  This document is a product of the IRTF Information-Centric Networking
  Research Group (ICNRG).











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Status of This Memo

  This document is not an Internet Standards Track specification; it is
  published for informational purposes.

  This document is a product of the Internet Research Task Force
  (IRTF).  The IRTF publishes the results of Internet-related research
  and development activities.  These results might not be suitable for
  deployment.  This RFC represents the consensus of the Information-
  Centric Networking Research Group of the Internet Research Task Force
  (IRTF).  Documents approved for publication by the IRSG are not a
  candidate for any level of Internet Standard; see Section 2 of RFC
  5741.

  Information about the current status of this document, any errata,
  and how to provide feedback on it may be obtained at
  http://www.rfc-editor.org/info/rfc7476.

Copyright Notice

  Copyright (c) 2015 IETF Trust and the persons identified as the
  document authors.  All rights reserved.

  This document is subject to BCP 78 and the IETF Trust's Legal
  Provisions Relating to IETF Documents
  (http://trustee.ietf.org/license-info) in effect on the date of
  publication of this document.  Please review these documents
  carefully, as they describe your rights and restrictions with respect
  to this document.






















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Table of Contents

  1. Introduction ....................................................3
     1.1. Baseline Scenario Selection ................................4
     1.2. Document Goals and Outline .................................5
  2. Scenarios .......................................................6
     2.1. Social Networking ..........................................6
     2.2. Real-Time Communication ....................................7
     2.3. Mobile Networking ..........................................9
     2.4. Infrastructure Sharing ....................................11
     2.5. Content Dissemination .....................................13
     2.6. Vehicular Networking ......................................14
     2.7. Delay- and Disruption-Tolerance ...........................17
          2.7.1. Opportunistic Content Sharing ......................20
          2.7.2. Emergency Support and Disaster Recovery ............21
     2.8. Internet of Things ........................................22
     2.9. Smart City ................................................25
  3. Cross-Scenario Considerations ..................................27
     3.1. Multiply Connected Nodes and Economics ....................27
     3.2. Energy Efficiency .........................................31
     3.3. Operation across Multiple Network Paradigms ...............33
  4. Summary ........................................................34
  5. Security Considerations ........................................35
  6. Informative References .........................................36
  Acknowledgments ...................................................44
  Authors' Addresses ................................................44

1.  Introduction

  Information-centric networking (ICN) marks a fundamental shift in
  communications and networking.  In contrast with the omnipresent and
  very successful host-centric paradigm, which is based on perpetual
  connectivity and the end-to-end principle, ICN changes the focal
  point of the network architecture from the end host to "named
  information" (or content, or data).  In this paradigm, connectivity
  may well be intermittent.  End-host and in-network storage can be
  capitalized upon transparently, as bits in the network and on storage
  devices have exactly the same value.  Mobility and multiaccess are
  the norm, and anycast, multicast, and broadcast are natively
  supported.

  It is also worth noting that with the transition from a host-centric
  to an information-centric communication model the security paradigm
  changes as well.  In a host-centric network, the basic idea is to
  create secure (remote-access) tunnels to trusted providers of data.
  In an information-centric network, on the other hand, any source
  (cache) should be equally usable.  This requires some mechanism for




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  making each information item trustworthy by itself; this can be
  achieved, for example, by name-data integrity or by signing data
  objects.

  Although interest in ICN is growing rapidly, ongoing work on
  different architectures, such as NetInf [NetInf], the original
  Content-Centric Networking [CCN], and its successors, Project CCNx
  [CCNx] and Named Data Networking (NDN) [NDNP], the Publish-Subscribe
  Internet (PSI) architecture [PSI], and the Data-Oriented Network
  Architecture [DONA] is far from being completed.  One could think of
  ICN today as being at a stage of development similar to that of
  packet-switched networking in the late 1970s when different
  technologies, e.g., DECnet, Internetwork Packet Exchange (IPX), and
  IP, just to name a few, were being actively developed and put to the
  test.  As such, ICN's current development phase and the plethora of
  approaches to tackle the hardest problems make this a very active and
  growing research area, but, on the downside, it also makes it more
  difficult to compare different proposals on an equal footing.  This
  document aims to partially address this by establishing a common
  understanding about potential experimental setups where different ICN
  approaches can be tested and compared against each other while
  showcasing their advantages.

  The first draft version of this document appeared in November 2012.
  It was adopted by ICNRG at IETF 87 (July 2013) as the document to
  address the work item on the definition of "reference baseline
  scenarios to enable performance comparisons between different
  approaches".  Earlier draft versions of this document have been
  presented during the ICNRG meetings at IETF 85, IETF 86, IETF 87,
  IETF 88, IETF 89, and the ICNRG interim meeting in Stockholm in
  February 2013.  This document has been reviewed, commented, and
  discussed extensively for a period of nearly two years by the vast
  majority of ICNRG members, which certainly exceeds 100 individuals.
  It is the consensus of ICNRG that the baseline scenarios described in
  this document should be published in the IRTF Stream of the RFC
  series.  This document does not constitute a standard.

1.1.  Baseline Scenario Selection

  Earlier surveys [SoA1] [SoA2] note that describing ICN architectures
  is akin to shooting a moving target.  We find that comparing these
  different approaches is often even more tricky.  It is not uncommon
  that researchers devise different performance evaluation scenarios,
  typically with good reason, in order to highlight the advantages of
  their approach.  This should be expected to some degree at this early
  stage of ICN development.  Nevertheless, this document shows that





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  certain baseline scenarios seem to emerge in which ICN architectures
  could showcase their comparative advantages over current systems, in
  general, and against each other, in particular.

  This document surveys the peer-reviewed ICN literature and presents
  prominent evaluation study cases as a foundation for the baseline
  scenarios to be considered by the IRTF Information-Centric Networking
  Research Group (ICNRG) in its future work.  There are two goals for
  this document: first, to provide a set of use cases and applications
  that highlight opportunities for testing different ICN proposals;
  second, to identify key attributes of a common set of techniques that
  can be instrumental in evaluating ICN.  Further, these scenarios are
  intended to equip researchers with sufficient configuration data to
  effectively evaluate their ICN proposals in a variety of settings,
  particularly extending beyond scenarios focusing simply on
  traditional content delivery.  The overall aim is that each scenario
  is described at a sufficient level of detail, and with adequate
  references to already published work, so that it can serve as the
  base for comparative evaluations of different approaches.  Example
  code that implements some of the scenarios and topologies included in
  this document is available from
  <http://telematics.poliba.it/icn-baseline-scenarios>.

1.2.  Document Goals and Outline

  This document incorporates input from ICNRG participants and their
  corresponding text contributions, has been reviewed by several ICNRG
  active participants (see Section 7), and represents the consensus of
  the research group.  However, this document does not constitute an
  IETF standard, but is an Informational document; see also [RFC5743].
  As mentioned above, these scenarios are intended to provide a
  framework for evaluating different ICN approaches.  The methodology
  for how to do these evaluations as well as definitions of metrics
  that should be used are described in a separate document
  [EVAL-METHOD].  In addition, interested readers should consider
  reviewing [CHALLENGES].

  The remainder of this document presents a number of scenarios grouped
  into several categories in Section 2, followed by a number of cross-
  scenario considerations in Section 3.  Overall, note that certain
  evaluation scenarios span across these categories, so the boundaries
  between them should not be considered rigid and inflexible.
  Section 4 summarizes the main evaluation aspects across the range of
  scenarios discussed in this document.







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2.  Scenarios

  This section presents nine scenario categories based on use cases and
  evaluations that have appeared in the peer-reviewed literature.

2.1.  Social Networking

  Social-networking applications have proliferated over the past decade
  based on overlay content dissemination systems that require large
  infrastructure investments to roll out and maintain.  Content
  dissemination is at the heart of the ICN paradigm.  Therefore, we
  would expect that social-networking scenarios are a "natural fit" for
  comparing ICN performance with traditional client-server TCP/IP-based
  systems.  Mathieu et al. [ICN-SN], for instance, illustrate how an
  Internet Service Provider (ISP) can capitalize on CCN to deploy a
  short-message service akin to Twitter at a fraction of the complexity
  of today's systems.  Their key observation is that such a service can
  be seen as a combination of multicast delivery and caching.  That is,
  a single user addresses a large number of recipients, some of which
  receive the new message immediately as they are online at that
  instant, while others receive the message whenever they connect to
  the network.

  Along similar lines, Kim et al. [VPC] present an ICN-based social-
  networking platform in which a user shares content with her/his
  family and friends without the need for centralized content servers;
  see also Section 2.4, below, and [CBIS].  Based on the CCN naming
  scheme, [VPC] takes a user name to represent a set of devices that
  belong to the person.  Other users in this in-network, serverless
  social sharing scenario can access the user's content not via a
  device name/address but with the user's name.  In [VPC], signature
  verification does not require any centralized authentication server.
  Kim and Lee [VPC2] present a proof-of-concept evaluation in which
  users with ordinary smartphones can browse a list of members or
  content using a name, and download the content selected from the
  list.

  In other words, the above-mentioned evaluation studies indicate that
  with ICN there may be no need for an end-to-end system design that
  intermediates between content providers and consumers in a hub-and-
  spoke fashion at all times.

  Earlier work by Arianfar et al. [CCR] considers a similar pull-based
  content retrieval scenario using a different architecture, pointing
  to significant performance advantages.  Although the authors consider
  a network topology (redrawn in Figure 1 for convenience) that has
  certain interesting characteristics, they do not explicitly address
  social networking in their evaluation scenario.  Nonetheless,



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  similarities are easy to spot: "followers" (such as C0, C1, ..., and
  Cz in Figure 1) obtain content put "on the network" (I1, ..., Im, and
  B1, B2) by a single user (e.g., Px) relying solely on network
  primitives.

  \--/
  |C0|
  /--\     +--+     +--+     +--+               +--+
      *=== |I0| === |I1| ... |In|               |P0|
  \--/     +--+     +--+     +--+               +--+
  |C1|                           \             / o
  /--\                            +--+     +--+  o
   o                              |B1| === |B2|  o
   o              o o o o         +--+     +--+  o
   o                             /             \ o
   o       +--+     +--+     +--+                +--+
   o  *=== |Ik| === |Il| ... |Im|                |Px|
  \--/     +--+     +--+     +--+                +--+
  |Cz|
  /--\

  Figure 1.  Dumbbell with Linear Daisy Chains

  In summary, the social-networking scenario aims to exercise each ICN
  architecture in terms of network efficiency, multicast support,
  caching performance and its reliance on centralized mechanisms (or
  lack thereof).

2.2.  Real-Time Communication

  Real-time audio and video (A/V) communications include an array of
  services ranging from one-to-one voice calls to multiparty multimedia
  conferences with support ranging from whiteboards to augmented
  reality.  Real-time communications have been studied and deployed in
  the context of packet- and circuit-switched networks for decades.
  The stringent Quality of Service (QoS) requirements that this type of
  communication imposes on network infrastructure are well known.
  Since one could argue that network primitives that are excellent for
  information dissemination are not well-suited for conversational
  services, ICN evaluation studies should consider real-time
  communication scenarios in detail.

  Notably, Jacobson et al. [VoCCN] presented an early evaluation where
  the performance of a VoIP (Voice over IP) call using an information-
  centric approach was compared with that of an off-the-shelf VoIP
  implementation using RTP/UDP.  The results indicated that despite the
  extra cost of adding security support in the ICN approach,
  performance was virtually identical in the two cases evaluated in



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  their testbed.  However, the experimental setup presented is quite
  rudimentary, while the evaluation considered a single voice call
  only.  Xuan and Yan [NDNpb] revisit the same scenario but are
  primarily interested in reducing the overhead that may arise in one-
  to-one communication employing an ICN architecture.  Both studies
  illustrate that quality telephony services are feasible with at least
  one ICN approach.  That said, future ICN evaluations should employ
  standardized call arrival patterns, for example, following well-
  established methodologies from the QoS and QoE (Quality of
  Experience) evaluation toolbox and would need to consider more
  comprehensive metrics.

  Given the widespread deployment of real-time A/V communications, an
  evaluation of an ICN system should demonstrate capabilities beyond
  feasibility.  For example, with respect to multimedia conferencing,
  Zhu et al. [ACT] describe the design of a distributed audio
  conference tool based on NDN.  Their system includes ICN-based
  conference discovery, speaker discovery, and voice data distribution.
  The reported evaluation results point to gains in scalability and
  security.  Moreover, Chen et al. [G-COPSS] explore the feasibility of
  implementing a Massively Multiplayer Online Role-Playing Game
  (MMORPG) based on CCNx code and show that stringent temporal
  requirements can be met, while scalability is significantly improved
  when compared to a host-centric (IP-based) client-server system.
  This type of work points to benefits for both the data and control
  path of a modern network infrastructure.

  Real-time communication also brings up the issue of named data
  granularity for dynamically generated content.  In many cases, A/V
  data is generated in real-time and is distributed immediately.  One
  possibility is to apply a single name to the entire content, but this
  could result in significant distribution delays.  Alternatively,
  distributing A/V content in smaller "chunks" that are named
  individually may be a better option with respect to real-time
  distribution but raises naming scalability concerns.

  We observe that, all in all, the ICN research community has hitherto
  only scratched the surface of illustrating the benefits of adopting
  an information-centric approach as opposed to a host-centric one, and
  thus more work is recommended in this direction.  Scenarios in this
  category should illustrate not only feasibility but reduced
  complexity, increased scalability, reliability, and capacity to meet
  stringent QoS/QoE requirements when compared to established host-
  centric solutions.  Accordingly, the primary aim of this scenario is
  to exercise each ICN architecture in terms of its ability to satisfy
  real-time QoS requirements and provide improved user experience.





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2.3.  Mobile Networking

  IP mobility management relies on anchors to provide ubiquitous
  connectivity to end-hosts as well as moving networks [MMIN].  This is
  a natural choice for a host-centric paradigm that requires end-to-end
  connectivity and a continuous network presence for hosts [SCES].  An
  implicit assumption in host-centric mobility management is therefore
  that the mobile node aims to connect to a particular peer, as well as
  to maintain global reachability and service continuity [EEMN].
  However, with ICN, new ideas about mobility management should come to
  the fore, capitalizing on the different nature of the paradigm, such
  as native support for multihoming, abstraction of network addresses
  from applications, less dependence on connection-oriented sessions,
  and so on [MOBSURV].

  Dannewitz et al. [N-Scen] illustrate a scenario where a multiaccess
  end-host can retrieve email securely using a combination of cellular
  and Wireless Local Area Network (WLAN) connectivity.  This scenario
  borrows elements from previous work, e.g., [DTI], and develops them
  further with respect to multiaccess.  Unfortunately, Dannewitz et al.
  [N-Scen] do not present any results demonstrating that an ICN
  approach is, indeed, better.  That said, the scenario is interesting
  as it considers content specific to a single user (i.e., her mailbox)
  and does point to reduced complexity.  It is also compatible with
  recent work in the Distributed Mobility Management (DMM) Working
  Group within the IETF.  Finally, Xylomenos et al. [PSIMob] as well as
  Pentikousis [EEMN] argue that an information-centric architecture can
  avoid the complexity of having to manage tunnels to maintain end-to-
  end connectivity as is the case with mobile anchor-based protocols
  such as Mobile IP (and its variants).  Similar considerations hold
  for a vehicular (networking) environment, as we discuss in Section
  2.6.

  Overall, mobile networking scenarios have not been developed in
  detail, let alone evaluated at a large scale.  Further, the majority
  of scenarios discussed so far have related to the mobility of the
  information consumer, rather than the source.  We expect that in the
  coming period more papers will address this topic.  Earlier work
  [mNetInf] argues that for mobile and multiaccess networking scenarios
  we need to go beyond the current mobility management mechanisms in
  order to capitalize on the core ICN features.  They present a testbed
  setup (redrawn in Figure 2) that can serve as the basis for other ICN
  evaluations.  In this scenario, node "C0" has multiple network
  interfaces that can access local domains N0 and N1 simultaneously,
  allowing C0 to retrieve objects from whichever server (I2 or I3) can
  supply them without necessarily needing to access the servers in the
  core network "C" (P1 and P2).  Lindgren [HybICN] explores this




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  scenario further for an urban setting.  He uses simulation and
  reports sizable gains in terms of reduction of object retrieval times
  and core network capacity use.

  +------------+      +-----------+
  | Network N0 |      | Network C |
  |            |      |           |
  | +--+       | ==== |    +--+   |
  | |I2|       |      |    |P1|   |
  | +--+       |      |    +--+   |
  |     \--/   |      |           |
  +-----|C0|---+      |           |
  |     /--\   |      |           |
  | +--+       |      |           |
  | |I3|       |      |      +--+ |
  | +--+       | ==== |      |P2| |
  |            |      |      +--+ |
  | Network N1 |      |           |
  +------------+      +-----------+

  Figure 2.  Overlapping Wireless Multiaccess

  The benefits from capitalizing on the broadcast nature of wireless
  access technologies has yet to be explored to its full potential in
  the ICN literature, including quantifying possible gains in terms of
  energy efficiency [E-CHANET].  Obviously, ICN architectures must
  avoid broadcast storms.  Early work in this area considers
  distributed packet suppression techniques that exploit delayed
  transmissions and overhearing; examples can be found in [MobiA] and
  [CCNMANET] for ICN-based mobile ad-hoc networks (MANETs), and in
  [RTIND] and [CCNVANET] for vehicular scenarios.

  One would expect that mobile networking scenarios will be naturally
  coupled with those discussed in the previous sections, as more users
  access social-networking and multimedia applications through mobile
  devices.  Further, the constraints of real-time A/V applications
  create interesting challenges in handling mobility, particularly in
  terms of maintaining service continuity.  This scenario therefore
  spans across most of the others considered in this document with the
  likely need for some level of integration, particularly considering
  the well-documented increases in mobile traffic.  Mobility is further
  considered in Section 2.7 and the economic consequences of nodes
  having multiple network interfaces is explored in Section 3.1.

  Host-centric mobility management has traditionally used a range of
  metrics for evaluating performance on a per-node and network-wide
  level.  The first metric that comes to mind is handover latency,
  defined in [RFC5568] as the "period during which the mobile node is



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  unable to send or receive packets".  This metric should be considered
  in ICN performance evaluation studies dealing with mobility.  Note
  that, in IP-based networks, handover latency has been addressed by
  the introduction of mobility management protocols that aim to hide
  node mobility from the correspondent node, and often follow a make-
  before-break approach in order to ensure seamless connectivity and
  minimize (or eliminate altogether) handover latency.  The "always-on"
  and "always best connected" [ABC] paradigms have guided mobility
  management research and standardization for a good decade or so.  One
  can argue that such mechanisms are not particularly suited for ICN.
  That said, there has been a lot of interest recently in distributed
  mobility management schemes (see [MMIN] for a summary), where
  mobility management support is not "always on" by default.  Such
  schemes may be more suitable for ICN.  As a general recommendation,
  ICN designs should aim to minimize handover latency so that the end-
  user and service QoE is not affected adversely.

  Network overhead, such as the amount of signaling necessary to
  minimize handover latency, is also a metric that should be considered
  when studying ICN mobility management.  In the past, network overhead
  has been seen as one of the main factors hindering the deployment of
  various mobility solutions.  In IP-based networks, network overhead
  includes, but is not limited to, tunneling overhead, in-band control
  protocol overhead, mobile terminal and network equipment state
  maintenance and update.  ICN designs and evaluation studies should
  clearly identify the network overhead associated with handling
  mobility.  Alongside network overhead, deployment complexity should
  also be studied.

  To summarize, mobile networking scenarios should aim to provide
  service continuity for those applications that require it, decrease
  complexity and control signaling for the network infrastructure, as
  well as increase wireless capacity utilization by taking advantage of
  the broadcast nature of the medium.  Beyond this, mobile networking
  scenarios should form a cross-scenario platform that can highlight
  how other scenarios can still maintain their respective performance
  metrics during periods of high mobility.

2.4.  Infrastructure Sharing

  A key idea in ICN is that the network should secure information
  objects per se, not the communications channel that they are
  delivered over.  This means that hosts attached to an information-
  centric network can share resources on an unprecedented scale,
  especially when compared to what is possible in an IP network.  All
  devices with network access and storage capacity can contribute their
  resources thereby increasing the value of an information-centric




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  network, although compensation schemes motivating users to contribute
  resources remain a research challenge primarily from a business
  perspective.

  For example, Jacobson et al. [CBIS] argue that in ICN the "where and
  how" of obtaining information are new degrees of freedom.  They
  illustrate this with a scenario involving a photo-sharing application
  that takes advantage of whichever access network connectivity is
  available at the moment (WLAN, Bluetooth, and even SMS) without
  requiring a centralized infrastructure to synchronize between
  numerous devices.  It is important to highlight that since the focus
  of communication changes, keep-alives in this scenario are simply
  unnecessary, as devices participating in the testbed network
  contribute resources in order to maintain user content consistency,
  not link state information as is the case in the host-centric
  paradigm.  This means that the notion of "infrastructure" may be
  completely different in the future.

  Muscariello et al. [SHARE], for instance, presented early work on an
  analytical framework that attempts to capture the storage/bandwidth
  tradeoffs that ICN enables and can be used as the foundation for a
  network planning tool.  In addition, Chai et al. [CL4M] explore the
  benefits of ubiquitous caching throughout an information-centric
  network and argue that "caching less can actually achieve more."
  These papers also sit alongside a variety of other studies that look
  at various scenarios such as caching HTTP-like traffic [CCNCT] and
  BitTorrent-like traffic [BTCACHE].  We observe that much more work is
  needed in order to understand how to make optimal use of all
  resources available in an information-centric network.  In real-world
  deployments, policy and commercial considerations are also likely to
  affect the use of particular resources, and more work is expected in
  this direction as well.

  In conclusion, scenarios in this category would cover the
  communication-computation-storage tradeoffs that an ICN deployment
  must consider.  This would exercise features relating to network
  planning, perhaps capitalizing on user-provided resources, as well as
  operational and economical aspects of ICN, and contrast them with
  other approaches.  An obvious baseline to compare against in this
  regard is existing federations of IP-based Content Distribution
  Networks (CDNs), such as the ones discussed in the IETF Content
  Delivery Networks Interconnection Working Group.









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2.5.  Content Dissemination

  Content dissemination has attracted more attention than other aspects
  of ICN.  Scenarios in this category abound in the literature,
  including stored and streaming A/V distribution, file distribution,
  mirroring and bulk transfers, versioned content services (cf.
  Subversion-type revision control), as well as traffic aggregation.

  Decentralized content dissemination with on-the-fly aggregation of
  information sources was envisaged in [N-Scen], where information
  objects can be dynamically assembled based on hierarchically
  structured subcomponents.  For example, a video stream could be
  associated with different audio streams and subtitle sets, which can
  all be obtained from different sources.  Using the topology depicted
  in Figure 1 as an example, an application at C1 may end up obtaining,
  say, the video content from I1, but the user-selected subtitles from
  Px.  Semantics and content negotiation, on behalf of the user, were
  also considered, e.g., for the case of popular tunes that may be
  available in different encoding formats.  Effectively, this scenario
  has the information consumer issuing independent requests for content
  based on information identifiers, and stitching the pieces together
  irrespective of "where" or "how" they were obtained.

  A case in point for content dissemination are vehicular ad hoc
  networks (VANETs), as an ICN approach may address their needs for
  information dissemination between vehicles better than today's
  solutions, as discussed in the following section.  The critical part
  of information dissemination in a VANET scenario revolves around
  "where" and "when".  For instance, one may be interested in traffic
  conditions 2 km ahead while having no interest in similar information
  about the area around the path origin.  VANET scenarios may provide
  fertile ground for showcasing the ICN advantage with respect to
  content dissemination especially when compared with current host-
  centric approaches.  That said, information integrity and filtering
  are challenges that must be addressed.  As mentioned above, content
  dissemination scenarios in VANETs have a particular affinity to the
  mobility scenarios discussed in Section 2.3.

  Content dissemination scenarios, in general, have a large overlap
  with those described in the previous sections and are explored in
  several papers, such as [DONA], [PSI], [PSIMob], [NetInf], [CCN],
  [CBIS], and [CCR], just to name a few.  In addition, Chai et al.
  [CURLING] present a hop-by-hop hierarchical content resolution
  approach that employs receiver-driven multicast over multiple
  domains, advocating another content dissemination approach.  Yet,
  largely, work in this area did not address the issue of access
  authorization in detail.  Often, the distributed content is mostly
  assumed to be freely accessible by any consumer.  Distribution of



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  paid-for or otherwise restricted content on a public ICN network
  requires more attention in the future.  Fotiou et al. [ACDICN]
  consider a scheme to this effect, but it still requires access to an
  authorization server to verify the user's status after the
  (encrypted) content has been obtained.  This may effectively negate
  the advantage of obtaining the content from any node, especially in a
  disruption-prone or mobile network.

  In summary, scenarios in this category aim to exercise primarily
  scalability and the cost and performance attributes of content
  dissemination.  Particularly, they should highlight the ability of an
  ICN to scale to billions of objects, while not exceeding the cost of
  existing content dissemination solutions (i.e., CDNs) and, ideally,
  increasing performance.  These should be shown in a holistic manner,
  improving content dissemination for both information consumers and
  publishers of all sizes.  We expect that in particular for content
  dissemination, in both extreme as well as typical scenarios, can be
  specified by drawing data from current CDN deployments.

2.6.  Vehicular Networking

  Users "on wheels" are interested in road safety, traffic efficiency,
  and infotainment applications that can be supported through vehicle-
  to-vehicle (V2V) and vehicle-to-infrastructure (V2I) wireless
  communications.  These applications exhibit unique features in terms
  of traffic generation patterns, delivery requirements, and spatial
  and temporal scope, which pose great challenges to traditional
  networking solutions.  VANETs, by their nature, are characterized by
  challenges such as fast-changing topology, intermittent connectivity,
  and high node mobility, but also by the opportunity to combine
  information from different sources as each vehicle does not care
  about "who" delivers the named data objects.

  ICN is an attractive candidate solution for vehicular networking, as
  it has several advantages.  First, ICN fits well to the nature of
  typical vehicular applications that are geography- and time-dependent
  (e.g., road traveler information, accident warning, point-of-interest
  advertisements) and usually target vehicles in a given area,
  regardless of their identity or IP address.  These applications are
  likely to benefit from in-network and decentralized data caching and
  replication mechanisms.  Second, content caching is particularly
  beneficial for intermittent on-the-road connectivity and can speed up
  data retrieval through content replication in several nodes.  Caching
  can usually be implemented at relatively low cost in vehicles, as the
  energy demands of the ICN device are likely to be a negligible
  fraction of the total vehicle energy consumption, thus allowing for
  sophisticated processing, continuous communication, and adequate
  storage in the vehicle.  Finally, ICN natively supports asynchronous



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  data exchange between end-nodes.  By using (and redistributing)
  cached named information objects, a mobile node can serve as a link
  between disconnected areas.  In short, ICN can enable communication
  even under intermittent network connectivity, which is typical of
  vehicular environments with sparse roadside infrastructure and fast-
  moving nodes.

  The advantages of ICN in vehicular networks were preliminarily
  discussed in [EWC] and [DMND], and additionally investigated in
  [DNV2V], [RTIND], [CCNHV], [CCDIVN], [CCNVANET], and [CRoWN].  For
  example, Bai and Krishnamachari [EWC] take advantage of the localized
  and dynamic nature of a VANET to explore how a road congestion
  notification application can be implemented.  Wang et al. [DMND]
  consider data collection where Road-Side Units (RSUs) collect
  information from vehicles by broadcasting NDN-like Interest packets.
  The proposed architecture is evaluated using simulation in a grid
  topology and is compared against a host-centric alternative based on
  Mobile IP.  See Figure 3 for an indicative example of an urban VANET
  topology.  Their results indicate high efficiency for ICN even at
  high speeds.  That said, this work is a preliminary exploration of
  ICN in vehicular environments, so various issues remain for
  evaluation.  They include system scalability to large numbers of
  vehicles and the impact of vehicles that forward Interest packets or
  relay data to other vehicles.

     + - - _- - -_- - - -_- - _- - - +
     |    /_\   /_\     /_\  /_\     |
     |    o o   o o     o o  o o     |
     |    +-------+     +-------+ _  |
     |    |       |     |       |/_\ |
     |  _ |       |     |       |o o |
     | /_\|       |    |       |     |
     | o o+--_----+\===/+--_----+    |
     |      /_\    |RSU|  /_\        |
     |      o o    /===\  o o        |
     |    +-------+     +-------+ _  |
     |    |       |     |       |/_\ |
     | _  |       |     |       |o o |
     |/_\ |       |     |       |    |
     |o o +_-----_+     +_-----_+    |
     |    /_\   /_\     /_\   /_\    |
     +_ _ o_o_ _o_o_ _ _o_o_ _o_o_ _ +

  Figure 3.  Urban Grid VANET Topology

  As mentioned in the previous section, due to the short communication
  duration between a vehicle and the RSU, and the typically short time
  of sustained connectivity between vehicles, VANETs may be a good



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  showcase for the ICN advantages with respect to content
  dissemination.  Wang et al. [DNV2V], for instance, analyze the
  advantages of hierarchical naming for vehicular traffic information
  dissemination.  Arnould et al. [CCNHV] apply ICN principles to safety
  information dissemination between vehicles with multiple radio
  interfaces.  In [CCDIVN], TalebiFard and Leung use network coding
  techniques to improve content dissemination over multiple ICN paths.
  Amadeo et al. [CCNVANET] [CRoWN] propose an application-independent
  ICN framework for content retrieval and distribution where the role
  of provider can be played equivalently by both vehicles and RSUs.
  ICN forwarding is extended through path-state information carried in
  Interest and Data packets, stored in a new data structure kept by
  vehicular nodes, and exploited also to cope with node mobility.

  Typical scenarios for testing content distribution in VANETs may be
  highways with vehicles moving in straight lines, with or without RSUs
  along the road, as shown in Figure 4.  With an NDN approach in mind,
  for example, RSUs may send Interest packets to collect data from
  vehicles [DMND], or vehicles may send Interest packets to collect
  data from other peers [RTIND] or from RSUs [CCNVANET].  Figure 2
  applies to content dissemination in VANET scenarios as well, where C0
  represents a vehicle that can obtain named information objects via
  multiple wireless peers and/or RSUs (I2 and I3 in the figure).  Grid
  topologies such as the one illustrated in Figure 3 should be
  considered in urban scenarios with RSUs at the crossroads or
  co-located with traffic lights as in [CRoWN].

       \___/                    \___/
       |RSU|                    |RSU|
     ================================
          _     _     _     _
         /_\   /_\   /_\   /_\
     _ _ o_o_ _o_o_ _o_o_ _o_o_ _ _ _
          _     _     _     _
         /_\   /_\   /_\   /_\
         o o   o o   o o   o o
     ================================

  Figure 4.  Highway VANET Topology

  To summarize, VANET scenarios aim to exercise ICN deployment from
  various perspectives, including scalability, caching, transport, and
  mobility issues.  There is a need for further investigation in (i)
  challenging scenarios (e.g., disconnected segments); (ii) scenarios
  involving both consumer and provider mobility; (iii) smart caching
  techniques that take into consideration node mobility patterns,
  spatial and temporal relevance, content popularity, and social
  relationships between users/vehicles; (iv) identification of new



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  applications (beyond data dissemination and traffic monitoring) that
  could benefit from the adoption of an ICN paradigm in vehicular
  networks (e.g., mobile cloud, social networking).

2.7.  Delay- and Disruption-Tolerance

  Delay- and Disruption-Tolerant Networking (DTN) originated as a means
  to extend the Internet to interplanetary communications [DTN].
  However, it was subsequently found to be an appropriate architecture
  for many terrestrial situations as well.  Typically, this was where
  delays were greater than protocols such as TCP could handle, and
  where disruptions to communications were the norm rather than
  occasional annoyances, e.g., where an end-to-end path does not
  necessarily exist when communication is initiated.  DTN has now been
  applied to many situations, including opportunistic content sharing,
  handling infrastructural issues during emergency situations (e.g.,
  earthquakes) and providing connectivity to remote rural areas without
  existing Internet provision and little or no communications or power
  infrastructure.

  The DTN architecture [RFC4838] is based on a "store, carry, and
  forward" paradigm that has been applied extensively to situations
  where data is carried between network nodes by a "data mule", which
  carries bundles of data stored in some convenient storage medium
  (e.g., a USB memory stick).  With the advent of sensor and peer-to-
  peer (P2P) networks between mobile nodes, DTN is becoming a more
  commonplace type of networking than originally envisioned.  Since ICN
  also does not rely on the familiar end-to-end communications
  paradigm, there are clear synergies [DTNICN].  It could therefore be
  argued that many of the key principles embodied within DTN also exist
  in ICN, as we explain next.

  First, both approaches rely on in-network storage.  In the case of
  DTN, bundles are stored temporarily on devices on a hop-by-hop basis.
  In the case of ICN, information objects are also cached on devices in
  a similar fashion.  As such, both paradigms must provision storage
  within the network.

  Second, both approaches espouse late binding of names to locations
  due to the potentially large interval between request and response
  generation.  In the case of DTN, it is often impossible to predict
  the exact location (in a disconnected topology) where a node will be
  found.  Similarly, in the case of ICN, it is also often impossible to
  predict where an information object might be found.  As such, the
  binding of a request/bundle to a destination (or routing locator)
  must be performed as late as possible.





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  Finally, both approaches treat data as a long-lived component that
  can exist in the network for extended periods of time.  In the case
  of DTN, bundles are carried by nodes until appropriate next hops are
  discovered.  In the case of ICN, information objects are typically
  cached until storage is exhausted.  As such, both paradigms require a
  direct shift in the way applications interact with the network.

  Through these similarities, it becomes possible to identify many DTN
  principles that are already in existence within ICN architectures.
  For example, ICN nodes will often retain information objects locally,
  making them accessible later on, much as DTN bundles are handled.
  Consequently, these synergies suggest strong potential for marrying
  the two technologies.  This could include, for instance, building new
  integrated Information-Centric Delay Tolerant Network (ICDTN)
  protocols or, alternatively, building ICN schemes over existing DTN
  protocols (and vice versa).

  The above similarities suggest that integration of the two principles
  would be feasible.  Beyond this, there are also a number of
  identifiable direct benefits.  Through caching and replication, ICN
  offers strong information resilience, whilst, through store-and-
  forward, DTN offers strong connectivity resilience.  As such, both
  architectures could benefit greatly from each other.  Initial steps
  have already been taken in the DTN community to integrate ICN
  principles, e.g., the Bundle Protocol Query Block [BPQ] has been
  proposed for the DTN Bundle Protocol [RFC5050].  Similarly, initial
  steps have also been taken in the ICN community, such as [SLINKY].
  In fact, the Scalable and Adaptive Internet Solutions (SAIL) project
  has developed a prototype implementation of NetInf running over the
  DTN Bundle Protocol.

  Of course, in many circumstances, information-centricity is not
  appropriate for use in delay- and disruption-tolerant environments.
  This is particularly the case when information is not the key
  communications atom transmitted.  Further, situations where a single
  sink is always used for receiving information may not warrant the
  identification and routing of independent information objects.
  However, there are a number of key scenarios where clear benefits
  could be gained by introducing information-centric principles into
  DTNs, two of which we describe later in this section.

  For the purpose of evaluating the use of ICNs in a DTN setting, two
  key scenarios are identified in this document.  (Note the rest of
  this section uses the term "ICDTN".)  These are both prominent use
  cases that are currently active in both the ICN and DTN communities.
  The first is opportunistic content sharing, whilst the second is the
  use of ad hoc networks during disaster recovery (e.g., earthquakes).
  We discuss both types of scenarios in the context of a simulation-



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  based evaluation: due to the scale and mobility of DTN-like setups,
  this is the primary method of evaluation used.  Within the DTN
  community, the majority of simulations are performed using the
  Opportunistic Network Environment (ONE) simulator [ONE], which is
  referred to in this document.  Before exploring the two scenarios,
  the key shared components of their simulation are discussed.  This is
  separated into the two primary inputs that are required: the
  environment and the workload.

  In both types of scenarios the environment can be abstractly modeled
  by a time series of active connections between device pairs.  Unlike
  other scenarios in this document, an ICDTN scenario therefore does
  not depend on (relatively) static topologies but, rather, a set of
  time-varying disconnected topologies.  In opportunistic networks,
  these topologies are actually products of the mobility of users.  For
  example, if two users walk past each other, an opportunistic link can
  be created.  There are two methods used to generate these mobility
  patterns and, in turn, the time series of topologies.  The first is
  synthetic, whereby a (mathematical) model of user behavior is created
  in an agent-based fashion, e.g., random waypoint, Gauss-Markov.  The
  second is trace-driven, whereby the mobility of real users is
  recorded and used.  In both cases, the output is a sequence of time-
  stamped "contacts", i.e., periods of time in which two devices can
  communicate.  An important factor missing from typical mobility
  traces, however, is the capacity of these contacts: how much data can
  be transferred?  In both approaches to modeling mobility, links are
  usually configured as Bluetooth or Wi-Fi (ONE easily allows this,
  although lower-layer considerations are ignored, e.g., interference).
  This is motivated by the predominance of these technologies on mobile
  phones.

  The workload in an ICDTN is modeled much like the workload within the
  other scenarios.  It involves object creation/placement and object
  retrieval.  Object creation/placement can either be done statically
  at the beginning of the simulations or, alternatively, dynamically
  based on a model of user behavior.  In both cases, the latter is
  focused on, as it models far better the characteristics of the
  scenarios.

  Once the environment and workload have been configured, the next step
  is to decide the key metrics for the study.  Unlike traditional
  networking, the QoS expectation is typically far lower in an ICDTN,
  thereby moving away from metrics such as throughput.  At a high
  level, it is of clear interest to evaluate different ICN approaches
  with respect to both their delay- and disruption-tolerance (i.e., how
  effective is the approach when used in an environment subject to
  significant delay and/or disruption) and to their active support for
  operations in a DTN environment.



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  The two most prominent metrics considered in a host-centric DTN are
  delivery probability and delivery delay.  The former relates to the
  probability by which a sent message will be received within a certain
  delay bound, whilst the latter captures the average length of time it
  takes for nodes to receive the message.  These metrics are similarly
  important in an ICDTN, although they are slightly different due to
  the request-response nature of ICN.  Therefore, the two most
  prominent evaluative metrics are satisfaction probability and
  satisfaction delay.  The former refers to the probability by which an
  information request (e.g., Interest) will be satisfied (i.e., how
  often a Data response will be received).  Satisfaction delay refers
  to the length of time it takes an information request to be
  satisfied.

  Note that the key difference between the host-centric and
  information-centric metrics is the need for a round-trip rather than
  a one-way communication.  Beyond this, depending on the focus of the
  work, other elements that may be investigated include name
  resolution, routing, and forwarding in disconnected parts of the
  network; support for unidirectional links; number of round trips
  needed to complete a data transfer; long-term content availability
  (or resilience); efficiency in the face of disruption; and so on.  It
  is also important to weigh these performance metrics against the
  necessary overheads.  In the case of an ICDTN, this is generally
  measured by the number of message replicas required to access
  content.  Note that routing in a DTN is often replication based,
  which leads to many copies of the same message.

2.7.1.  Opportunistic Content Sharing

  The first key baseline scenario in this context is opportunistic
  content sharing.  This occurs when mobile nodes create opportunistic
  links between each other to share content of interest.  For example,
  people riding on an underground train can pass news items between
  their mobile phones.  Equally, content generated on the phones (e.g.,
  tweets [TWIMIGHT]) could be stored for later forwarding (or even
  forwarded amongst interested passengers on the train).  Such
  scenarios, clearly, must be based around either the altruistic or
  incentivized interaction amongst users.  The latter is a particularly
  active area of research.  These networks are often termed "pocket-
  switched networks", as they are independently formed between the user
  devices.  Here, the evaluative scenario of ICDTN microblogging is
  proposed.  As previously discussed, the construction of such an
  evaluative scenario requires a formalization of its environment and
  workload.  Fortunately, there exist a number of datasets that offer
  exactly this information required for microblogging.





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  In terms of the environment (i.e., mobility patterns), the Haggle
  project produced contact traces based on conference attendees using
  Bluetooth.  These traces are best targeted at application scenarios
  in which a small group of (50-100) people are in a relatively
  confined space.  In contrast, larger-scale traces are also available,
  most notably MIT's Reality Mining project.  These are better suited
  for cases where longer-term movement patterns are of interest.

  The second input, workload, relates to the creation and consumption
  of microblogs (e.g., tweets).  This can be effectively captured
  because subscriptions conveniently formalize who consumes what.  For
  bespoke purposes, specific data can be directly collected from
  Twitter for trace-driven simulations.  Several Twitter datasets are
  already available to the community containing a variety of data,
  ranging from Tweets to follower graphs.  See
  <http://www.tweetarchivist.com> and
  <http://socialcomputing.asu.edu/datasets/Twitter>.  These datasets
  can therefore be used to extract information production, placement,
  and consumption.

2.7.2.  Emergency Support and Disaster Recovery

  The second key baseline scenario in this context relates to the use
  of ICDTNs in emergency scenarios.  In these situations, it is typical
  for infrastructure to be damaged or destroyed, leading to the
  collapse of traditional forms of communications (e.g., cellular
  telephone networks).  This has been seen in the recent North Indian
  flooding, as well as the 2011 Tohoku earthquake and tsunami.  Power
  problems often exacerbate the issue, with communication failures
  lasting for days.  Therefore, in order to address this, DTNs have
  been used due to their high levels of resilience and independence
  from fixed infrastructure.  The most prominent use of DTNs in
  disaster areas would be the dissemination of information, e.g.,
  warnings and evacuation maps.  Unlike the previous scenario, it can
  be assumed that certain users (e.g., emergency responders) are highly
  altruistic.  However, it is likely many other users (e.g., endangered
  civilians) might become far more conservative in how they use their
  devices for battery-conserving purposes.  Here, we focus on the
  dissemination of standard broadcast information that should be
  received by all parties; generally, this is something led by
  emergency responders.

  For the environmental setup, there are no commonly used mobility
  traces for disaster zones, unlike in the previous scenario.  This is
  clearly due to the difficultly (near impossibility) of acquiring them
  in a real setting.  That said, various synthetic models are
  available.  The Post-Disaster Mobility Model [MODEL1] models
  civilians and emergency responders after a disaster has occurred,



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  with people attempting to reach evacuation points (this has also been
  implemented in the ONE simulator).  Aschenbruck et al. [MODEL2] focus
  on emergency responders, featuring the removal of nodes from the
  disaster zone, as well as things like obstacles (e.g., collapsed
  buildings).  Cabrero et al. [MODEL3] also look at emergency
  responders but focus on patterns associated with common procedures.
  For example, command and control centers are typically set up with
  emergency responders periodically returning.  Clearly, the mobility
  of emergency responders is particularly important in this setting
  because they usually are the ones who will "carry" information into
  the disaster zone.  It is recommended that one of these emergency-
  specific models be used during any evaluations, due to the inaccuracy
  of alternate models used for "normal" behavior.

  The workload input in this evaluative scenario is far simpler than
  for the previous scenario.  In emergency cases, the dissemination of
  individual pieces of information to all parties is the norm.  This is
  often embodied using things like the Common Alert Protocol (CAP),
  which is an XML standard for describing warning message.  It is
  currently used by various systems, including the Integrated Public
  Alert & Warning System and Google Crisis Response.  As such, small
  objects (e.g., 512 KB to 2 MB) are usually generated containing text
  and images; note that the ONE simulator offers utilities to easily
  generate these.  These messages are also always generated by central
  authorities, therefore making the placement problem easier (they
  would be centrally generated and given to emergency responders to
  disseminate as they pass through the disaster zone).  The key
  variable is therefore the generation rate, which is synonymous with
  the rate that microblogs are written in the previous scenario.  This
  will largely be based on the type of disaster occurring; however,
  hourly updates would be an appropriate configuration.  Higher rates
  can also be tested, based on the rate at which situations change
  (landslides, for example, can exhibit highly dynamic properties).

  To summarize, this section has highlighted the applicability of ICN
  principles to existing DTN scenarios.  Two evaluative setups have
  been described in detail, namely, mobile opportunistic content
  sharing (microblogging) and emergency information dissemination.

2.8.  Internet of Things

  Advances in electronics miniaturization combined with low-power
  wireless access technologies (e.g., ZigBee, Near Field Communication
  (NFC), Bluetooth, and others) have enabled the coupling of
  interconnected digital services with everyday objects.  As devices
  with sensors and actuators connect into the network, they become
  "smart objects" and form the foundation for the so-called Internet of




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  Things (IoT).  IoT is expected to increase significantly the amount
  of content carried by the network due to machine-to-machine (M2M)
  communication as well as novel user-interaction possibilities.

  Yet, the full potential of IoT does not lie in simple remote access
  to smart object data.  Instead, it is the intersection of Internet
  services with the physical world that will bring about the most
  dramatic changes.  Burke [IoTEx], for instance, makes a very good
  case for creating everyday experiences using interconnected things
  through participatory sensing applications.  In this case, inherent
  ICN capabilities for data discovery, caching, and trusted
  communication are leveraged to obtain sensor information and enable
  content exchange between mobile users, repositories, and
  applications.

  Kutscher and Farrell [IWMT] discuss the benefits that ICN can provide
  in these environments in terms of naming, caching, and optimized
  transport.  The Named Information URI scheme (ni) [RFC6920], for
  instance, could be used for globally unique smart object
  identification, although an actual implementation report is not
  currently available.  Access to information generated by smart
  objects can be of varied nature and often vital for the correct
  operation of large systems.  As such, supporting timestamping,
  security, scalability, and flexibility need to be taken into account.

  Ghodsi et al. [NCOA] examine hierarchical and self-certifying naming
  schemes and point out that ensuring reliable and secure content
  naming and retrieval may pose stringent requirements (e.g., the
  necessity for employing PKI), which can be too demanding for low-
  powered nodes, such as sensors.  That said, earlier work by Heidemann
  et al. [nWSN] shows that, for dense sensor network deployments,
  disassociating sensor naming from network topology and using named
  content at the lowest level of communication in combination with in-
  network processing of sensor data is feasible in practice and can be
  more efficient than employing a host-centric binding between node
  locator and the content existing therein.

  Burke et al. [NDNl] describe the implementation of a building
  automation system for lighting control where the security, naming,
  and device discovery NDN mechanisms are leveraged to provide
  configuration, installation, and management of residential and
  industrial lighting control systems.  The goal is an inherently
  resilient system, where even smartphones can be used for control.
  Naming reflects fixtures with evolved identification and node-
  reaching capabilities, thus simplifying bootstrapping, discovery, and
  user interaction with nodes.  The authors report that this ICN-based
  system requires less maintenance and troubleshooting than typical
  IP-based alternatives.



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  Biswas et al. [CIBUS] visualize ICN as a contextualized information-
  centric bus (CIBUS) over which diverse sets of service producers and
  consumers coexist with different requirements.  ICN is leveraged to
  unify different platforms to serve consumer-producer interaction in
  both infrastructure and ad hoc settings.  Ravindran et al. [Homenet]
  show the application of this idea in the context of a home network,
  where consumers (residents) require policy-driven interactions with
  diverse services such as climate control, surveillance systems, and
  entertainment systems.  Name-based protocols are developed to enable
  zero-configuration node and service discovery, contextual service
  publishing and subscription, policy-based routing and forwarding with
  name-based firewall, and hoc device-to-device communication.

  IoT exposes ICN concepts to a stringent set of requirements that are
  exacerbated by the quantity of nodes, as well as by the type and
  volume of information that must be handled.  A way to address this is
  proposed in [IoTScope], which tackles the problem of mapping named
  information to an object, diverting from the currently typical
  centralized discovery of services and leveraging the intrinsic ICN
  scalability capabilities for naming.  It extends the base [PURSUIT]
  design with hierarchically based scopes, facilitating lookup, access,
  and modifications of only the part of the object information that the
  user is interested in.  Another important aspect is how to
  efficiently address resolution and location of the information
  objects, particularly when large numbers of nodes are connected, as
  in IoT deployments.  In [ICN-DHT], Katsaros et al. propose a
  Distributed Hash Table (DHT) that is compared with the Data-Oriented
  Network Architecture described in [DONA].  Their results show how
  topological routing information has a positive impact on resolution,
  at the expense of memory and processing overhead.

  The use of ICN mechanisms in IoT scenarios faces the most dynamic and
  heterogeneous type of challenges, when taking into consideration the
  requirements and objectives of such integration.  The disparity in
  technologies (not only in access technologies, but also in terms of
  end-node diversity such as sensors, actuators, and their
  characteristics) as well as in the information that is generated and
  consumed in such scenarios, will undoubtedly bring about many of the
  considerations presented in the previous sections.  For instance, IoT
  shares similarities with the constraints and requirements applicable
  to vehicular networking.  Here, a central problem is the deployment
  of mechanisms that can use opportunistic connectivity in unreliable
  networking environments (similar to the vehicular networking and DTN
  scenarios).

  However, one important concern in IoT scenarios, also motivated by
  this strongly heterogeneous environment, is how content dissemination
  will be affected by the different semantics of the disparate



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  information and content being shared.  In fact, this is already a
  difficult problem that goes beyond the scope of ICN [SEMANT].  With
  the ability of the network nodes to cache forwarded information to
  improve future requests, a challenge arises regarding whether the ICN
  fabric should be involved in any kind of procedure (e.g., tagging)
  that facilitates the relationship or the interpretation of the
  different sources of information.

  Another issue lies with the need for having energy-efficiency
  mechanisms related to the networking capabilities of IoT
  infrastructures.  Often, the devices in IoT deployments have limited
  battery capabilities, and thus need low power consumption schemes
  working at multiple levels.  In principle, energy efficiency gains
  should be observed from the inherent in-network caching capability.
  However, this might not be the most usual case in IoT scenarios,
  where the information (particularly from sensors or controlling
  actuators) is more akin to real-time traffic, thus reducing the scale
  of potential savings due to ubiquitous in-network caching.

  ICN approaches, therefore, should be evaluated with respect to their
  capacity to handle the content produced and consumed by extremely
  large numbers of diverse devices.  IoT scenarios aim to exercise ICN
  deployment from different aspects, including ICN node design
  requirements, efficient naming, transport, and caching of time-
  restricted data.  Scalability is particularly important in this
  regard as the successful deployment of IoT principles could increase
  both device and content numbers dramatically beyond all current
  expectations.

2.9.  Smart City

  The rapid increase in urbanization sets the stage for the most
  compelling and challenging environments for networking.  By 2050 the
  global population will reach nine billion people, 75% of which will
  dwell in urban areas.  In order to cope with this influx, many cities
  around the world have started their transformation toward the "smart
  city" vision.  Smart cities will be based on the following innovation
  axes: smart mobility, smart environment, smart people, smart living,
  and smart governance.  In development terms, the core goal of a smart
  city is to become a business-competitive and attractive environment,
  while serving citizen well-being [CPG].

  In a smart city, ICT plays a leading role and acts as the glue
  bringing together all actors, services, resources (and their
  interrelationships) that the urban environment is willing to host and
  provide [MVM].  ICN appears particularly suitable for these
  scenarios.  Domains of interest include intelligent transportation
  systems, energy networks, health care, A/V communications, peer-to-



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  peer and collaborative platforms for citizens, social inclusion,
  active participation in public life, e-government, safety and
  security, and sensor networks.  Clearly, this scenario has close ties
  to the vision of IoT, discussed in the previous section, as well as
  to vehicular networking.

  Nevertheless, the road to build a real information-centric digital
  ecosystem will be long, and more coordinated effort is required to
  drive innovation in this domain.  We argue that smart-city needs and
  ICN technologies can trigger a virtuous innovation cycle toward
  future ICT platforms.  Recent concrete ICN-based contributions have
  been formulated for home energy management [iHEMS], geo-localized
  services [ACC], smart-city services [IB], and traffic information
  dissemination in vehicular scenarios [RTIND].  Some of the proposed
  ICN-based solutions are implemented in real testbeds, while others
  are evaluated through simulation.

  Zhang et al. [iHEMS] propose a secure publish-subscribe architecture
  for handling the communication requirements of Home Energy Management
  Systems (HEMS).  The objective is to safely and effectively collect
  measurement and status information from household elements, aggregate
  and analyze the data, and ultimately enable intelligent control
  decisions for actuation.  They consider a simple experimental testbed
  for their proof-of-concept evaluation, exploiting open source code
  for the ICN implementation, and emulating some node functionality in
  order to facilitate system operation.

  A different scenario is considered in [ACC], where DHTs are employed
  for distributed, scalable, and geographically aware service lookup in
  a smart city.  Also in this case, the ICN application is validated by
  considering a small-scale testbed: a small number of nodes are
  emulated with simple embedded PCs or specific hardware boards (e.g.,
  for some sensor nodes); other nodes (which connect the principal
  actors of the tests) are emulated with workstations.  The proposal in
  [IB] draws from a smart-city scenario (mainly oriented towards waste
  collection management) comprising sensors and moving vehicles, as
  well as a cloud-computing system that supports data retrieval and
  storage operations.  The main aspects of this proposal are analyzed
  via simulation using open source code that is publicly available.
  Some software applications are designed on real systems (e.g., PCs
  and smartphones).

  With respect to evaluating ICN approaches in smart-city scenarios, it
  is necessary to consider generic metrics useful to track and monitor
  progress on services results and also for comparing localities
  between themselves and learn from the best [ISODIS].  In particular,
  it is possible to select a specific set of Key Performance Indicators
  (KPIs) for a given project in order to evaluate its success.  These



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  KPIs may reflect the city's environmental and social goals, as well
  as its economic objectives, and they can be calculated at the global,
  regional, national, and local levels.  Therefore, it is not possible
  to define a unique set of interesting metrics, but in the context of
  smart cities, the KPIs should be characterized with respect to the
  developed set of services offered by using the ICN paradigm.

  To sum up, smart-city scenarios aim to exercise several ICN aspects
  in an urban environment.  In particular, they can be useful to (i)
  analyze the capacity of using ICN for managing extremely large data
  sets; (ii) study ICN performance in terms of scalability in
  distributed services; (iii) verify the feasibility of ICN in a very
  complex application like vehicular communication systems; and (iv)
  examine the possible drawbacks related to privacy and security issues
  in complex networked environments.

3.  Cross-Scenario Considerations

  This section discusses considerations that span multiple scenarios.

3.1.  Multiply Connected Nodes and Economics

  The evolution of, in particular, wireless networking technologies has
  resulted in a convergence of the bandwidth and capabilities of
  various different types of network.  Today, a leading-edge mobile
  telephone or tablet computer will typically be able to access a Wi-Fi
  access point, a 4G cellular network, and the latest generation of
  Bluetooth local networking.  Until recently, a node would usually
  have a clear favorite network technology appropriate to any given
  environment.  The choice would, for example, be primarily determined
  by the available bandwidth with cost as a secondary determinant.
  Furthermore, it is normally the case that a device only uses one of
  the technologies at a time for any particular application.

  It seems likely that this situation will change so that nodes are
  able to use all of the available technologies in parallel.  This will
  be further encouraged by the development of new capabilities in
  cellular networks including Small Cell Networks [SCN] and
  Heterogeneous Networks [HetNet].  Consequently, mobile devices will
  have similar choices to wired nodes attached to multiple service
  providers allowing "multihoming" via the various different
  infrastructure networks as well as potential direct access to other
  mobile nodes via Bluetooth or a more capable form of ad hoc Wi-Fi.

  Infrastructure networks are generally under the control of separate
  economic entities that may have different policies about the
  information of an ICN deployed within their network caches.  As ICN
  shifts the focus from nodes to information objects, the interaction



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  between networks will likely evolve to capitalize on data location
  independence, efficient and scalable in-network named object
  availability, and access via multiple paths.  These interactions
  become critical in evaluating the technical and economic impact of
  ICN architectural choices, as noted in [ArgICN].  Beyond simply
  adding diversity in deployment options, these networks have the
  potential to alter the incentives among existing (and future, we may
  add) network players, as noted in [EconICN].

  Moreover, such networks enable more numerous internetwork
  relationships where exchange of information may be conditioned on a
  set of multilateral policies.  For example, shared SCNs are emerging
  as a cost-effective way to address coverage of complex environments
  such as sports stadiums, large office buildings, malls, etc.  Such
  networks are likely to be a complex mix of different cellular and
  WLAN access technologies (such as HSPA, LTE, and Wi-Fi) as well as
  ownership models.  It is reasonable to assume that access to content
  generated in such networks may depend on contextual information such
  as the subscription type, timing, and location of both the owner and
  requester of the content.  The availability of such contextual
  information across diverse networks can lead to network
  inefficiencies unless data management can benefit from an
  information-centric approach.  The "Event with Large Crowds"
  demonstrator created by the SAIL project investigated this kind of
  scenario; more details are available in [SAIL-B3].

  Jacobson et al. [CCN] include interactions between networks in their
  overall system design and mention both "an edge-driven, bottom-up
  incentive structure" and techniques based on evolutions of existing
  mechanisms both for ICN router discovery by the end-user and for
  interconnecting between Autonomous Systems (ASes).  For example, a
  BGP extension for domain-level content prefix advertisement can be
  used to enable efficient interconnection between ASes.  Liu et al.
  [MLDHT] proposed to address the "suffix-hole" issue found in prefix-
  based name aggregation through the use of a combination of Bloom-
  filter-based aggregation and multi-level DHT.

  Name aggregation has been discussed for a flat naming design, for
  example, in [NCOA], in which the authors note that based on
  estimations in [DONA] flat naming may not require aggregation.  This
  is a point that calls for further study.  Scenarios evaluating name
  aggregation, or lack thereof, should take into account the amount of
  state (e.g., size of routing tables) maintained in edge routers as
  well as network efficiency (e.g., amount of traffic generated).







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                +---------------+
    +---------->| Popular Video |
    |           +---------------+
    |             ^           ^
    |             |           |
    |           +-+-+ $0/MB +-+-+
    |           | A +-------+ B |
    |           ++--+       +-+-+
    |            | ^         ^ |
    |      $8/MB | |         | | $10/MB
    |            v |         | v
  +-+-+  $0/MB  +--+---------+--+
  | D +---------+       C       |
  +---+         +---------------+

  Figure 5.  Relationships and Transit Costs between Networks A to D

  DiBenedetto et al. [RP-NDN] study policy knobs made available by NDN
  to network operators.  New policies that are not feasible in the
  current Internet are described, including a "cache sharing peers"
  policy, where two peers have an incentive to share content cached in,
  but not originating from, their respective network.  The simple
  example used in the investigation considers several networks and
  associated transit costs, as shown in Figure 5 (based on Figure 1 of
  [RP-NDN]).  Agyapong and Sirbu [EconICN] further establish that ICN
  approaches should incorporate features that foster (new) business
  relationships.  For example, publishers should be able to indicate
  their willingness to partake in the caching market, proper reporting
  should be enabled to avoid fraud, and content should be made
  cacheable as much as possible to increase cache hit ratios.

  Kutscher et al. [SAIL-B3] enable network interactions in the NetInf
  architecture using a name resolution service at domain edge routers
  and a BGP-like routing system in the NetInf Default-Free Zone.
  Business models and incentives are studied in [SAIL-A7] and
  [SAIL-A8], including scenarios where the access network provider (or
  a virtual CDN) guarantees QoS to end users using ICN.  Figure 6
  illustrates a typical scenario topology from this work that involves
  an interconnectivity provider.












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  +----------+     +-----------------+     +------+
  | Content  |     | Access Network/ |     | End  |
  | Provider +---->|  ICN Provider   +---->| User |
  +----------+     +-+-------------+-+     +------+
                     |             |
                     |             |
                     v             v
  +-------------------+     +----------------+       +------+
  | Interconnectivity |     | Access Network |       | End  |
  |     Provider      +---->|     Provider   +------>| User |
  +-------------------+     +----------------+       +------+

  Figure 6.  Setup and Operating Costs of Network Entities

  Jokela et al. [LIPSIN] propose a two-layer approach where additional
  rendezvous systems and topology formation functions are placed
  logically above multiple networks and enable advertising and routing
  content between them.  Visala et al. [LANES] further describe an ICN
  architecture based on similar principles, which, notably, relies on a
  hierarchical DHT-based rendezvous interconnect.  Rajahalme et al.
  [PSIRP1] describe a rendezvous system using both a BGP-like routing
  protocol at the edge and a DHT-based overlay at the core.  Their
  evaluation model is centered around policy-compliant path stretch,
  latency introduced by overlay routing, caching efficacy, and load
  distribution.

  Rajahalme et al. [ICCP] point out that ICN architectural changes may
  conflict with the current tier-based peering model.  For example,
  changes leading to shorter paths between ISPs are likely to meet
  resistance from Tier-1 ISPs.  Rajahalme [IDMcast] shows how
  incentives can help shape the design of specific ICN aspects, and in
  [IDArch] he presents a modeling approach to exploit these incentives.
  This includes a network model that describes the relationship between
  Autonomous Systems based on data inferred from the current Internet,
  a traffic model taking into account business factors for each AS, and
  a routing model integrating the valley-free model and policy
  compliance.  A typical scenario topology is illustrated in Figure 7,
  which is redrawn here based on Figure 1 of [ICCP].  Note that it
  relates well with the topology illustrated in Figure 1 of this
  document.











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                       o-----o
                 +-----+  J  +-----+
                 |     o--*--o     |
                 |        *        |
              o--+--o     *     o--+--o
              |  H  +-----------+  I  |
              o-*-*-o     *     o-*-*-o
                * *       *       * *
           ****** ******* * ******* *******
           *            * * *             *
        o--*--o        o*-*-*o         o--*--o
        |  E  +--------+  F  +---------+  G  +
        o-*-*-o        o-----o         o-*-*-o
          * *                            * *
     ****** *******                 ****** ******
     *            *                 *           *
  o--*--o      o--*--o           o--*--o     o--*--o
  |  A  |      |  B  +-----------+  C  |     |  D  |
  o-----o      o--+--o           o--+--o     o----+o
                  |                 |         ^^  | route
            data  |            data |    data ||  | to
                  |                 |         ||  | data
              o---v--o          o---v--o     o++--v-o
              | User |          | User |     | Data |
              o------o          o------o     o------o

  Legend:
  *****  Transit link
  +---+  Peering link
  +--->  Data delivery or route to data

  Figure 7.  Tier-Based Set of Interconnections between AS A to J

  To sum up, the evaluation of ICN architectures across multiple
  network types should include a combination of technical and economic
  aspects, capturing their various interactions.  These scenarios aim
  to illustrate scalability, efficiency, and manageability, as well as
  traditional and novel network policies.  Moreover, scenarios in this
  category should specifically address how different actors have proper
  incentives, not only in a pure ICN realm, but also during the
  migration phase towards this final state.

3.2.  Energy Efficiency

  ICN has prominent features that can be taken advantage of in order to
  significantly reduce the energy footprint of future communication
  networks.  Of course, one can argue that specific ICN network
  elements may consume more energy than today's conventional network



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  equipment due to the potentially higher energy demands for named-data
  processing en route.  On balance, however, ICN introduces an
  architectural approach that may compensate on the whole and can even
  achieve higher energy efficiency rates when compared to the host-
  centric paradigm.

  We elaborate on the energy efficiency potential of ICN based on three
  categories of ICN characteristics.  Namely, we point out that a) ICN
  does not rely solely on end-to-end communication, b) ICN enables
  ubiquitous caching, and c) ICN brings awareness of user requests (as
  well as their corresponding responses) at the network layer thus
  permitting network elements to better schedule their transmission
  patterns.

  First, ICN does not mandate perpetual end-to-end communication, which
  introduces a whole range of energy consumption inefficiencies due to
  the extensive signaling, especially in the case of mobile and
  wirelessly connected devices.  This opens up new opportunities for
  accommodating sporadically connected nodes and could be one of the
  keys to an order-of-magnitude decrease in energy consumption compared
  to the potential contributions of other technological advances.  For
  example, web applications often need to maintain state at both ends
  of a connection in order to verify that the authenticated peer is up
  and running.  This introduces keep-alive timers and polling behavior
  with a high toll on energy consumption.  Pentikousis [EEMN] discusses
  several related scenarios and explains why the current host-centric
  paradigm, which employs perpetual end-to-end connections, introduces
  built-in energy inefficiencies, and argues that patches to make
  currently deployed protocols energy-aware cannot provide for an
  order-of-magnitude increase in energy efficiency.

  Second, ICN network elements come with built-in caching capabilities,
  which is often referred to as "ubiquitous caching".  Pushing data
  objects to caches closer to end-user devices, for example, could
  significantly reduce the amount of transit traffic in the core
  network, thereby reducing the energy used for data transport.  Guan
  et al. [EECCN] study the energy efficiency of a CCNx architecture
  (based on their proposed energy model) and compare it with
  conventional content dissemination systems such as CDNs and P2P.
  Their model is based on the analysis of the topological structure and
  the average hop length from all consumers to the nearest cache
  location.  Their results show that an information-centric approach
  can be more energy efficient in delivering popular and small-size
  content.  In particular, they also note that different network-
  element design choices (e.g., the optical bypass approach) can be
  more energy efficient in delivering infrequently accessed content.





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  Lee et al. [EECD] investigate the energy efficiency of various
  network devices deployed in access, metro, and core networks for both
  CDNs and ICN.  They use trace-based simulations to show that an ICN
  approach can substantially improve the network energy efficiency for
  content dissemination mainly due to the reduction in the number of
  hops required to obtain a data object, which can be served by
  intermediate nodes in ICN.  They also emphasize that the impact of
  cache placement (in incremental deployment scenarios) and
  local/cooperative content replacement strategies needs to be
  carefully investigated in order to better quantify the energy
  efficiencies arising from adopting an ICN paradigm.

  Third, ICN elements are aware of the user request and its
  corresponding data response; due to the nature of name-based routing,
  they can employ power consumption optimization processes for
  determining their transmission schedule or powering down inactive
  network interfaces.  For example, network coding [NCICN] or adaptive
  video streaming [COAST] can be used in individual ICN elements so
  that redundant transmissions, possibly passing through intermediary
  networks, could be significantly reduced, thereby saving energy by
  avoiding carrying redundant traffic.

  Alternatively, approaches that aim to simplify routers, such as
  [PURSUIT], could also reduce energy consumption by pushing routing
  decisions to a more energy-efficient entity.  Along these lines, Ko
  et al. [ICNDC] design a data center network architecture based on ICN
  principles and decouple the router control-plane and data-plane
  functionalities.  Thus, data forwarding is performed by simplified
  network entities, while the complicated routing computation is
  carried out in more energy-efficient data centers.

  To summarize, energy efficiency has been discussed in ICN evaluation
  studies, but most published work is preliminary in nature.  Thus, we
  suggest that more work is needed in this front.  Evaluating energy
  efficiency does not require the definition of new scenarios or
  baseline topologies, but does require the establishment of clear
  guidelines so that different ICN approaches can be compared not only
  in terms of scalability, for example, but also in terms of power
  consumption.

3.3.  Operation across Multiple Network Paradigms

  Today the overwhelming majority of networks are integrated with the
  well-connected Internet with IP at the "waist" of the technology
  hourglass.  However, there is a large amount of ongoing research into
  alternative paradigms that can cope with conditions other than the
  standard set assumed by the Internet.  Perhaps the most advanced of
  these is Delay- and Disruption-Tolerant Networking (DTN).  DTN is



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  considered as one of the scenarios for the deployment in Section 2.7,
  but here we consider how ICN can operate in an integrated network
  that has essentially disjoint "domains" (a highly overloaded term!)
  or regions that use different network paradigms and technologies, but
  with gateways that allow interoperation.

  ICN operates in terms of named data objects so that requests and
  deliveries of information objects can be independent of the
  networking paradigm.  Some researchers have contemplated some form of
  ICN becoming the new waist of the hourglass as the basis of a future
  reincarnation of the Internet, e.g., [ArgICN], but there are a large
  number of problems to resolve, including authorization, access
  control, and transactional operation for applications such as
  banking, before some form of ICN can be considered as ready to take
  over from IP as the dominant networking technology.  In the meantime,
  ICN architectures will operate in conjunction with existing network
  technologies as an overlay or in cooperation with the lower layers of
  the "native" technology.

  It seems likely that as the reach of the "Internet" is extended,
  other technologies such as DTN will be needed to handle scenarios
  such as space communications where inherent delays are too large for
  TCP/IP to cope with effectively.  Thus, demonstrating that ICN
  architectures can work effectively in and across the boundaries of
  different networking technologies will be important.

  The NetInf architecture, in particular, targets the inter-domain
  scenario by the use of a convergence-layer architecture [SAIL-B3],
  and Publish-Subscribe Internet Routing Paradigm (PSIRP) and/or
  Publish-Subscribe Internet Technology (PURSUIT) is envisaged as a
  candidate for an IP replacement.

  The key items for evaluation over and above the satisfactory
  operation of the architecture in each constituent domain will be to
  ensure that requests and responses can be carried across the network
  boundaries with adequate performance and do not cause malfunctions in
  applications or infrastructure because of the differing
  characteristics of the gatewayed domains.

4.  Summary

  This document presents a wide range of different application areas in
  which the use of information-centric network designs have been
  evaluated in the peer-reviewed literature.  Evidently, this broad
  range of scenarios illustrates the capability of ICN to potentially
  address today's problems in an alternative and better way than host-
  centric approaches as well as to point to future scenarios where ICN
  may be applicable.  We believe that by putting different ICN systems



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  to the test in diverse application areas, the community will be
  better equipped to judge the potential of a given ICN proposal and
  therefore subsequently invest more effort in developing it further.
  It is worth noting that this document collected different kinds of
  considerations, as a result of our ongoing survey of the literature
  and the discussion within ICNRG, which we believe would have
  otherwise remained unnoticed in the wider community.  As a result, we
  expect that this document can assist in fostering the applicability
  and future deployment of ICN over a broader set of operations, as
  well as possibly influencing and enhancing the base ICN proposals
  that are currently available and possibly assist in defining new
  scenarios where ICN would be applicable.

  We conclude this document with a brief summary of the evaluation
  aspects we have seen across a range of scenarios.

  The scalability of different mechanisms in an ICN architecture stands
  out as an important concern (cf. Sections 2.1, 2.2, 2.5, 2.6, 2.8,
  2.9, and 3.1) as does network, resource, and energy efficiency (cf.
  Sections 2.1, 2.3, 2.4, 3.1, and 3.2).  Operational aspects such as
  network planing, manageability, reduced complexity and overhead (cf.
  Sections 2.2, 2.3, 2.4, 2.8, and 3.1) should not be neglected
  especially as ICN architectures are evaluated with respect to their
  potential for deployment in the real world.  Accordingly, further
  research in economic aspects as well as in the communication,
  computation, and storage tradeoffs entailed in each ICN architecture
  is needed.

  With respect to purely technical requirements, support for multicast,
  mobility, and caching lie at the core of many scenarios (cf. Sections
  2.1, 2.3, 2.5, and 2.6).  ICN must also be able to cope when the
  Internet expands to incorporate additional network paradigms (cf.
  Section 3.3).  We have also seen that being able to address stringent
  QoS requirements and increase reliability and resilience should also
  be evaluated following well-established methods (cf. Sections 2.2,
  2.8, and 2.9).

  Finally, we note that new applications that significantly improve the
  end-user experience and forge a migration path from today's host-
  centric paradigm could be the key to a sustained and increasing
  deployment of the ICN paradigm in the real world (cf. Sections 2.2,
  2.3, 2.6, 2.8, and 2.9).

5.  Security Considerations

  This document does not impact the security of the Internet.





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6.  Informative References

  [RFC5743]  Falk, A., "Definition of an Internet Research Task Force
             (IRTF) Document Stream", RFC 5743, December 2009,
             <http://www.rfc-editor.org/info/rfc5743>.

  [RFC5050]  Scott, K. and S. Burleigh, "Bundle Protocol
             Specification", RFC 5050, November 2007,
             <http://www.rfc-editor.org/info/rfc5050>.

  [RFC4838]  Cerf, V., Burleigh, S., Hooke, A., Torgerson, L., Durst,
             R., Scott, K., Fall, K., and H. Weiss, "Delay-Tolerant
             Networking Architecture", RFC 4838, April 2007,
             <http://www.rfc-editor.org/info/rfc4838>.

  [RFC5568]  Koodli, R., Ed., "Mobile IPv6 Fast Handovers", RFC 5568,
             July 2009, <http://www.rfc-editor.org/info/rfc5568>.

  [RFC6920]  Farrell, S., Kutscher, D., Dannewitz, C., Ohlman, B.,
             Keranen, A., and P. Hallam-Baker, "Naming Things with
             Hashes", RFC 6920, April 2013,
             <http://www.rfc-editor.org/info/rfc6920>.

  [NetInf]   Ahlgren, B. et al., "Design considerations for a network
             of information", Proc. CoNEXT Re-Arch Workshop, ACM, 2008.

  [CCN]      Jacobson, V., et al., "Networking Named Content", Proc.
             CoNEXT, ACM, 2009.

  [CCNx]     Mosko, M.,  Solis, I., and E. Uzun, "CCN 1.0 Protocol
             Architecture", Project CCNx documentation, Xerox Palo Alto
             Research Center, 2013,
             <http://ccnx.org/pubs/ICN_CCN_Protocols.pdf>.

  [NDNP]     Zhang, L., et al., "Named Data Networking (NDN) Project",
             NDN Technical Report NDN-0001, Oct. 2010,
             <http://named-data.net/publications/techreports/>.

  [PSI]      Trossen, D. and G. Parisis, "Designing and realizing an
             information-centric internet", IEEE Commun. Mag., vol. 50,
             no. 7, July 2012.

  [DONA]     Koponen, T., et al., "A Data-Oriented (and Beyond) Network
             Architecture", Proc. SIGCOMM, ACM, 2007.

  [SoA1]     Ahlgren, B., et al., "A survey of information-centric
             networking", IEEE Commun. Mag., vol. 50, no. 7, July 2012.




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  [SoA2]     Xylomenos, G., et al. "A survey of information-centric
             networking research", IEEE Communications Surveys and
             Tutorials (2013): 1-26.

  [ICN-SN]   Mathieu, B., et al., "Information-centric networking: a
             natural design for social network applications", IEEE
             Commun. Mag., vol. 50, no. 7, July 2012.

  [VPC]      Kim, J., et al., "Content Centric Network-based Virtual
             Private Community", Proc. ICCE, IEEE, 2011.

  [CBIS]     Jacobson, V., et al., "Custodian-Based Information
             Sharing", IEEE Commun. Mag., vol. 50, no. 7, July 2012.

  [VPC2]     Kim, D. and J. Lee, "CCN-based virtual private community
             for extended home media service", IEEE Trans. Consumer
             Electronics, vol. 57, no. 2, May 2011.

  [CCR]      Arianfar, S., et al., "On content-centric router design
             and implications", Proc. CoNEXT Re-Arch Workshop, ACM,
             2010.

  [VoCCN]    Jacobson, V., et al., "VoCCN: Voice-over Content-Centric
             Networks", Proc. CoNEXT Re-Arch Workshop, ACM, 2009.

  [NDNpb]    Xuan, Y. and Z. Yan, "Enhancing Routing Efficiency in
             Named Data Network with Piggybacked Interest", Proc. CFI,
             ACM, 2013.

  [ACT]      Zhu, Z., et al., "ACT: Audio Conference Tool Over Named
             Data Networking", Proc. SIGCOMM ICN Workshop, ACM, 2011.

  [G-COPSS]  Chen, J., et al., "G-COPSS: A Content Centric
             Communication Infrastructure for Gaming Applications",
             Proc. ICDCS, IEEE, 2012.

  [MMIN]     Pentikousis, K., and P. Bertin., "Mobility Management in
             Infrastructure Networks", IEEE Internet Computing 17, no.
             5 (2013): 74-79.

  [SCES]     Allman, M., et al., "Enabling an Energy-Efficient Future
             Internet through Selectively Connected End Systems", Proc.
             HotNets-VI, ACM, 2007.

  [EEMN]     Pentikousis, K., "In Search of Energy-Efficient Mobile
             Networking", IEEE Commun. Mag., vol. 48, no. 1, Jan. 2010.





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  [MOBSURV]  Tyson, G., et al., "A Survey of Mobility in Information-
             Centric Networks: Challenges and Research Directions",
             Proc. MobiHoc Workshop on Emerging Name-Oriented Mobile
             Networking Design, ACM, 2012.

  [N-Scen]   Dannewitz, C., et al., "Scenarios and research issues for
             a Network of Information", Proc. MobiMedia, ICST, 2012.

  [DTI]      Ott, J. and D. Kutscher, "Drive-thru Internet: IEEE
             802.11b for 'automobile' users", Proc. INFOCOM, IEEE,
             2004.

  [PSIMob]   Xylomenos, G., et al., "Caching and Mobility Support in a
             Publish-Subscribe Internet Architecture", IEEE Commun.
             Mag., vol. 50, no. 7, July 2012.

  [mNetInf]  Pentikousis, K. and T. Rautio, "A Multiaccess Network of
             Information", Proc. WoWMoM, IEEE, 2010.

  [HybICN]   Lindgren, A., "Efficient content distribution in an
             information-centric hybrid mobile networks", Proc. CCNC,
             IEEE, 2011.

  [E-CHANET] M. Amadeo, et al., "E-CHANET: Routing, Forwarding and
             Transport in Information-Centric Multihop Wireless
             Networks", Computer Communications, Elsevier, Jan. 2013
             online.

  [MobiA]    Meisel, M., et al., "Ad Hoc Networking via Named Data",
             Proc. MobiArch, ACM 2010.

  [CCNMANET] Oh, S. Y., et al., "Content Centric Networking in Tactical
             and Emergency MANETs", Proc. Wireless Days, IFIP, 2010.

  [RTIND]    Wang, L., et al., "Rapid Traffic Information Dissemination
             Using Named Data", Proc. MobiHoc NoM workshop, ACM, 2012.

  [CCNVANET] Amadeo, M., et al., "Content-Centric Networking: is that a
             Solution for Upcoming Vehicular Networks?", Proc. VANET,
             ACM, 2012.

  [ABC]      Gustafsson, E., and A. Jonsson. "Always best connected",
             Wireless Communications, IEEE 10.1 (2003): 49-55.

  [SHARE]    Muscariello, L., et al., "Bandwidth and storage sharing
             performance in information centric networking", Proc.
             SIGCOMM ICN Workshop, ACM, 2011.




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  [CL4M]     Chai, W. K., et al., "Cache 'Less for More' in
             Information-centric Networks", Proc. Networking, IFIP,
             2012.

  [CCNCT]    Psaras, I., et al., "Modelling and Evaluation of CCN-
             Caching Trees", In Proc. of the 10th international IFIP
             conference on Networking, Valencia, Spain, May 2011.

  [BTCACHE]  Tyson, G., et al., "A Trace-Driven Analysis of Caching in
             Content-Centric Networks", Proc. ICCCN, IEEE, 2012.

  [CURLING]  Chai, W. K., et al., "CURLING: Content-Ubiquitous
             Resolution and Delivery Infrastructure for Next-Generation
             Services", IEEE Commun. Mag., vol. 49, no. 3, Mar. 2011.

  [ACDICN]   Fotiou, N., et al., "Access control enforcement delegation
             for information-centric networking architectures", Proc.
             SIGCOMM ICN Workshop, ACM, 2012.

  [EWC]      Bai, F. and B. Krishnamachari, "Exploiting the wisdom of
             the crowd: localized, distributed information-centric
             VANETs", IEEE Commun. Mag., vol. 48, no. 5, May 2010.

  [DMND]     Wang, J., R. Wakikawa, and L. Zhang, "DMND: Collecting
             data from mobiles using Named Data", Proc. Vehicular
             Networking Conference (VNC), IEEE, 2010.

  [DNV2V]    Wang, L., et al., "Data Naming in Vehicle-to-Vehicle
             Communications", Proc. INFOCOM NOMEN workshop, IEEE, 2012.

  [CCNHV]    Arnould, G., et al., "A Self-Organizing Content Centric
             Network Model for Hybrid Vehicular Ad-Hoc Networks". Proc.
             DIVANet, ACM, 2011.

  [CCDIVN]   TalebiFard, P. and V.C.M. Leung, "A Content Centric
             Approach to Dissemination of Information in Vehicular
             Networks", Proc. DIVANet, ACM, 2012.

  [CRoWN]    Amadeo, M., et al., "CRoWN: Content-Centric Networking in
             Vehicular Ad Hoc Networks", IEEE Communications Letters,
             vol. 16, no. 9, Sept. 2012.

  [SCN]      Hoydis, J., et al., "Green small-cell networks", IEEE
             Vehicular Technology Magazine, vol. 6, no.1, pp. 37-43,
             March 2011.






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  [HetNet]   Li, H., et al. "Efficient HetNet implementation using
             broadband wireless access with fiber-connected massively
             distributed antennas architecture", IEEE Wireless
             Communications, vol. 18, no.3, pp. 72-78, June 2011.

  [ArgICN]   Trossen, D., et al., "Arguments for an information centric
             internetworking architecture", ACM SIGCOMM CCR, 40:26-33,
             Apr. 2010.

  [EconICN]  Agyapong, P. and M. Sirbu, "Economic Incentives in
             Information Centric Networking: Implications for Protocol
             Design and Public Policy", IEEE Commun. Mag., vol. 50, no.
             12, Dec. 2012.

  [SAIL-B3]  Kutscher, D., Ed., et al., "Final NetInf Architecture",
             SAIL Project Deliverable D-B.3, Jan. 2013,
             <http://www.sail-project.eu/deliverables/>.

  [MLDHT]    Liu, H., et al., "A multi-level DHT routing framework with
             aggregation", Proc. SIGCOMM ICN Workshop, ACM, 2012.

  [NCOA]     Ghodsi, A., et al., "Naming in Content-oriented
             Architectures", Proc. SIGCOMM ICN Workshop, ACM, 2011.

  [RP-NDN]   DiBenedetto, S., et al., "Routing policies in named data
             networking", Proc. SIGCOMM ICN Workshop, ACM, 2011.

  [SAIL-A7]  Salo, J., Ed., et al., "New business models and business
             dynamics of the future networks", SAIL Project Deliverable
             D-A.7, Aug. 2011,
             <http://www.sail-project.eu/deliverables/>.

  [SAIL-A8]  Zhang, N., Ed., et al., "Evaluation of business models",
             SAIL Project Deliverable D-A.8, Jan. 2013,
             <http://www.sail-project.eu/deliverables/>.

  [LIPSIN]   Jokela, P., et al., "LIPSIN: line speed publish/subscribe
             inter-networking", Proc. of ACM SIGCOMM 2009.

  [LANES]    Visala, K., et al., "LANES: An Inter-Domain Data-Oriented
             Routing Architecture", Proc. CoNEXT Re-Arch Workshop, ACM,
             2009.

  [PSIRP1]   Rajahalme, J., et al., "Inter-Domain Rendezvous Service
             Architecture", PSIRP Technical Report TR09-003, Dec. 2009.






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  [ICCP]     Rajahalme J., et al., "Incentive-Compatible Caching and
             Peering in Data-Oriented Networks", Proc. CoNEXT Re-Arch
             Workshop, ACM, 2008.

  [IDMcast]  Rajahalme, J., "Incentive-informed Inter-domain
             Multicast", Proc. Global Internet Symposium 2010.

  [IDArch]   Rajahalme, J., "Inter-domain incentives and Internet
             architecture", PhD. Dissertation, Aalto University, Aug.
             2012.

  [PURSUIT]  Fotiou, N., et al., "Developing Information Networking
             Further: From PSIRP to PURSUIT", Proc. BROADNETS, ICST,
             2010.

  [EECCN]    Guan, K., et al., "On the Energy Efficiency of Content
             Delivery Architectures", Proc. ICC Workshops, IEEE, 2011.

  [EECD]     Lee, U., Rimac, I., Kilper, D., and V. Hilt, "Toward
             energy-efficient content dissemination", IEEE Network,
             vol. 25, no. 2, March-April 2011.

  [NCICN]    Montpetit, M. J., Westphal, C., and D. Trossen, "Network
             coding meets information-centric networking: an
             architectural case for information dispersion through
             native network coding", Proc. MOBIHOC NoM Workshop, ACM,
             2012.

  [COAST]    Gruneberg, K., et al., "File format specification and 3D
             video codec", COAST Project Deliverable D5.1, July 2011,
             <http://www.coast-fp7.eu/deliverables.html>.

  [ICNDC]    Ko, B. J., Pappas, V., Raghavendra, R., Song, Y.,
             Dilmaghani, R. B., Lee, K.-w., and D. Verma, "An
             information-centric architecture for data center
             networks", Proc. SIGCOMM ICN Workshop, ACM, 2012.

  [DTN]      Fall, K., "A delay-tolerant network architecture for
             challenged internets", Proc. SIGCOMM, ACM, 2003.

  [DTNICN]   Tyson, G., Bigham, J., and E. Bodanese, "Towards an
             Information-Centric Delay-Tolerant Network", Proc. IEEE
             INFOCOM NOMEN 2013, Turin, Italy.

  [BPQ]      Farrell, S., Lynch, A., Kutscher, D., and A. Lindgren,
             "Bundle Protocol Query Extension Block", Work in Progress,
             draft-irtf-dtnrg-bpq-00, May 2012.




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  [SLINKY]   Kawadia, V., Riga, N., Opper, J., and D. Sampath, "Slinky:
             An adaptive protocol for content access in disruption-
             tolerant ad hoc networks", in Proc. MobiHoc Workshop on
             Tactical Mobile Ad Hoc Networking, 2011.

  [ONE]      "The Opportunistic Network Environment simulator",
             <http://www.netlab.tkk.fi/tutkimus/dtn/theone>.

  [TWIMIGHT] Hossmann, T., et al. "Twitter in disaster mode: smart
             probing for opportunistic peers", Proc. 3rd ACM
             International Workshop on Mobile Opportunistic Networks,
             ACM, 2012.

  [MODEL1]   Uddin, M.Y.S., Nicol, D.M., Abdelzaher, T.F., and R.H.
             Kravets, "A post-disaster mobility model for Delay
             Tolerant Networking", Simulation Conference (WSC),
             Proceedings of the 2009 Winter, pp. 2785-2796, 13-16 Dec.
             2009.

  [MODEL2]   Aschenbruck, N., Gerhards-Padilla, E., and P. Martini,
             "Modeling mobility in disaster area scenarios",
             Performance Evaluation 66, no. 12 (2009): 773-790.

  [MODEL3]   Cabrero, S., Paneda, X.G., Plagemann, T., Melendi, D., and
             R. Garcia, "An Overlay Routing Protocol for Video over
             sparse MANETs in Emergencies", Cadernos de Informatica 6,
             no. 1 (2011): 195-202.

  [IoTEx]    Burke, J., "Authoring Place-based Experiences with an
             Internet of Things: Tussles of Expressive, Operational,
             and Participatory Goals", Position Paper, Interconnecting
             Smart Objects with the Internet Workshop, IAB, 2011.

  [IWMT]     Kutscher, D. and S. Farrell, "Towards an Information-
             Centric Internet with more Things", Position Paper,
             Interconnecting Smart Objects with the Internet Workshop,
             IAB, 2011.

  [nWSN]     Heidemann, J., et al., "Building efficient wireless sensor
             networks with low-level naming", Proc. SOSP, ACM, 2001.

  [NDNl]     Burke, J., et al., "Authenticated Lighting Control Using
             Named Data Networking", NDN Technical Report NDN-0011,
             Oct. 2012.

  [CIBUS]    Biswas, T., et al., "Contextualized Information-Centric
             Home Network", Proc. ACM SIGCOMM, ACM, 2013.




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  [Homenet]  Ravindran, R., et al., "Information-centric Networking
             based Homenet", Proc. International Workshop on Management
             of the Future Internet (ManFI), IFIP/IEEE, 2013.

  [IoTScope] Marias, G.F., et al., "Efficient information lookup for
             the Internet of Things", Proc. WoWMoM, IEEE, 2012.

  [ICN-DHT]  Katsaros, K., et al., "On inter-domain name resolution for
             information-centric networks", Proc. Networking, Springer,
             2012.

  [SEMANT]   Sheth, A., et al., "Semantic Sensor Web," Internet
             Computing, IEEE , vol. 12, no. 4, pp.78-83, July-Aug. 2008

  [CPG]      Cianci, I., et al., "Content Centric Services in Smart
             Cities", Proc. NGMAST, IEEE, 2012.

  [MVM]      Hernndez-Munoz, J.M., et al., "Smart cities at the
             forefront of the future Internet", The Future Internet,
             Springer, 2011.

  [iHEMS]    Zhang, J., et al., "iHEMS: An Information-Centric Approach
             to Secure Home Energy Management", Proc. SmartGridComm,
             IEEE, 2012.

  [ACC]      Andreini, F., et al., "A scalable architecture for geo-
             localized service access in smart cities", Proc. Future
             Network and Mobile Summit, IEEE, 2011.

  [IB]       Idowu, S. and N. Bari, "A Development Framework for Smart
             City Services, Integrating Smart City Service Components",
             Master's Thesis, Lulea University of Technology, 2012.

  [ISODIS]   ISO/DIS, "Sustainable development and resilience of
             communities --Indicators for city services and quality of
             life", ISO/DIS 37120, 2013.

  [EVAL-METHOD]
             Pentikousis, K., Ed., Ohlman, B., Davies, E., Spirou, S.,
             Boggia, G., and P. Mahadevan, "Information-centric
             Networking: Evaluation Methodology", Work in Progress,
             draft-irtf-icnrg-evaluation-methodology-00, July 2014.

  [CHALLENGES]
             Kutscher, D., Ed., Eum, S., Pentikousis, K., Psaras, I.,
             Corujo, D., Saucez, D., Schmidt, T., and M. Waehlisch,
             "ICN Research Challenges", Work in Progress, draft-irtf-
             icnrg-challenges-01, February 2015.



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Acknowledgments

  Dorothy Gellert contributed to an earlier draft version of this
  document.

  This document has benefited from reviews, pointers to the growing ICN
  literature, suggestions, comments, and proposed text provided by the
  following members of the IRTF Information-Centric Networking Research
  Group (ICNRG), listed in alphabetical order: Marica Amadeo, Hitoshi
  Asaeda, Claudia Campolo, Luigi Alfredo Grieco, Myeong-Wuk Jang, Ren
  Jing, Will Liu, Hongbin Luo, Priya Mahadevan, Ioannis Psaras, Spiros
  Spirou, Dirk Trossen, Jianping Wang, Yuanzhe Xuan, and Xinwen Zhang.

  The authors would like to thank Mark Stapp, Juan Carlos Zuniga, and
  G.Q. Wang for their comments and suggestions as part of their open
  and independent review of this document within ICNRG.

Authors' Addresses

  Kostas Pentikousis (editor)
  EICT GmbH
  Torgauer Strasse 12-15
  10829 Berlin
  Germany

  EMail: [email protected]


  Borje Ohlman
  Ericsson Research
  S-16480 Stockholm
  Sweden

  EMail: [email protected]


  Daniel Corujo
  Instituto de Telecomunicacoes
  Campus Universitario de Santiago
  P-3810-193 Aveiro
  Portugal

  EMail: [email protected]








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  Gennaro Boggia
  Dep. of Electrical and Information Engineering
  Politecnico di Bari
  Via Orabona 4
  70125 Bari
  Italy

  EMail: [email protected]


  Gareth Tyson
  School and Electronic Engineering and Computer Science
  Queen Mary, University of London
  United Kingdom

  EMail: [email protected]


  Elwyn Davies
  Trinity College Dublin/Folly Consulting Ltd
  Dublin, 2
  Ireland

  EMail: [email protected]


  Antonella Molinaro
  Dep. of Information, Infrastructures, and Sustainable
  Energy Engineering
  Universita' Mediterranea di Reggio Calabria
  Via Graziella 1
  89100 Reggio Calabria
  Italy

  EMail: [email protected]


  Suyong Eum
  National Institute of Information and Communications Technology
  4-2-1, Nukui Kitamachi, Koganei
  Tokyo  184-8795
  Japan

  Phone: +81-42-327-6582
  EMail: [email protected]






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