Network Working Group                                         G. Trewitt
Request for Comments: 1076                           Stanford University
Obsoletes: RFC 1023                                         C. Partridge
                                                               BBN/NNSC
                                                          November 1988


                 HEMS Monitoring and Control Language

                          TABLE OF CONTENTS

1.   Status of This Memo                                               1
    Introduction                                                      2
2.   Overview and Scope                                                2
3.   Overview of Query Processor Operation                             4
4.   Encoding of Queries and Responses                                 5
4.1  Notation Used in This Proposal                                    5
5.   Data Organization                                                 6
5.1  Example Data Tree                                                 7
5.2  Arrays                                                            8
6.   Components of a Query                                             9
7.   Reply to a Query                                                 10
8.   Query Language                                                   12
8.1  Moving Around in the Data Tree                                   14
8.2  Retrieving Data                                                  15
8.3  Data Attributes                                                  16
8.4  Examining Memory                                                 18
8.5  Control Operations:  Modifying the Data Tree                     19
8.6  Associative Data Access:  Filters                                21
8.7  Terminating a Query                                              26
9.   Extending the Set of Values                                      27
10.  Authorization                                                    27
11.  Errors                                                           28
I.   ASN.1 Descriptions of Query Language Components                  29
I.1  Operation Codes                                                  30
I.2  Error Returns                                                    31
I.3  Filters                                                          33
I.4  Attributes                                                       34
I.5  VendorSpecific                                                   36
II.  Implementation Hints                                             36
III. Obtaining a Copy of the ASN.1 Specification                      42

1. STATUS OF THIS MEMO

  This RFC specifies a query language for monitoring and control of
  network entities.  This RFC supercedes RFC-1023, extending the query
  language and providing more discussion of the underlying issues.




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  This language is a component of the High-Level Entity Monitoring
  System (HEMS) described in RFC-1021 and RFC-1022.  Readers may wish
  to consult these RFCs when reading this memo.  RFC-1024 contains
  detailed assignments of numbers and structures used in this system.
  Portions of RFC-1024 that define query language structures are
  superceded by definitions in this memo.  This memo assumes a
  knowledge of the ISO data encoding standard, ASN.1.

  Distribution of this memo is unlimited.

INTRODUCTION

  This RFC specifies the design of a general-purpose, yet efficient,
  monitoring and control language for managing network entities.  The
  data in the entity is modeled as a hierarchy and specific items are
  named by giving the path from the root of the tree.  Most items are
  read-only, but some can be "set" in order to perform control
  operations.  Both requests and responses are represented using the
  ISO ASN.1 data encoding rules.

2. OVERVIEW AND SCOPE

  The basic model of monitoring and control used in this memo is that a
  query is sent to a monitored entity and the entity sends back a
  response.  The term query is used in the database sense -- it may
  request information, modify data, or both.  We will use gateway-
  oriented examples, but it should be understood that this query-
  response mechanism is applicable to any IP entity.

  In particular, there is no notion of an interactive "conversation" as
  in SMTP [RFC-821] or FTP [RFC-959].  A query is a complete request
  that stands on its own and elicits a complete response.

  In order to design the query language, we had to define a model for
  the data to be retrieved by the queries, which required some
  understanding of and assumptions to be made about the data.  We ended
  up with a fairly flexible data model, which places few limits on the
  type or size of the data.

  Wherever possible, we give motivations for the design decisions or
  assumptions that led to particular features or definitions.  Some of
  the important global considerations and assumptions are:

        - The query processor should place as little computational
          burden on the monitored entity as possible.

        - It should not be necessary for a monitored entity to store
          the complete query.  Nothing in the query language should



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          preclude an implementation from being able to process the
          query on the fly, producing portions of the response while
          the query is still being read and parsed.  There may be
          other constraints that require large amounts of data to be
          buffered, but the query language design must not be one.

        - It is assumed that there is some mechanism to transport a
          sequence of octets to a query processor within the
          monitored entity and that there is some mechanism to return
          a sequence of octets to the entity making the query.  In
          HEMS, this is provided by HEMP and its underlying transport
          layer.  The query language design is independent of these
          details, however, and could be grafted onto some other
          protocol.

        - The data model must provide organization for the data, so
          that it can be conveniently named.

        - Much of the data to be monitored will be contained in
          tables.  Some tables may contain other tables.  The query
          language should be able to deal with such tables.

        - We don't provide capabilities for data reduction in the
          query language.  We will provide for data selection, for
          example, only retrieving certain table entries, but we will
          not provide general facilities for processing data, such as
          computing averages.

        - Because one monitoring center may be querying many
          (possibly hetrogenous) hosts, it must be possible to write
          generic queries that can be sent to all hosts, and have the
          query elicit as much information as is available from each
          host.  i.e., queries must not be aborted just because they
          requested non-existent data.

  There were some assumptions that we specifically did not make:

        - It is up to the implementation to choose what degree of
          concurrency will be allowed when processing queries.  By
          locking only portions of the database, it should be
          possible to achieve good concurrency while still preventing
          deadlock.

        - This specification makes no statement about the use of the
          "definite" and "indefinite" length forms in ASN.1.  There
          is currently some debate about this usage in the ISO
          community; implementors should note the recommendations in
          the ASN.1 specification.



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  Other RFCs associated with HEMS are:

     RFC-1021        Overview;
     RFC-1022        Transport protocol and message encapsulation;
     RFC-1024        Precise data definitions.

  The rest of this report is organized as follows:

     Section 3       Gives a brief overview of the data model and the
                     operation of the query processor.

     Section 4       Describes the encoding used for queries and
                     responses, and the notation used to represent them
                     in this report.

     Section 5       Describes how the data is organized in the
                     monitored entity, and the view provided of it by
                     the query processor.

     Section 6       Describes the basic data types that may be given
                     to the query processor as input.

     Section 7       Describes how a reply to a query is organized.

     Section 8       Describes the operations available in the query
                     language.

     Section 9       Describes how the set of data in the tree may be
                     extended.

     Section 10      Describes how authorization issues affect the
                     execution of a query.

     Section 11      Describes how errors are reported, and their
                     effect on the processing of the query.

     Appendix I      Gives precise ASN.1 definitions of the data types
                     used by the query processor.

     Appendix II     Gives extensive implementation hints for the core
                     of the query processor.

3. OVERVIEW OF QUERY PROCESSOR OPERATION

  In this section, we give an overview of the operation of the query
  processor, to provide a framework for the later sections.

  The query language models the manageable data as a tree, with each



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  branch representing a different aspect of the entity, such as
  different layers of protocols.  Subtrees are further divided to
  provide additional structure to the data.  The leaves of the tree
  contain the actual data.

  Given this data representation, the task of the query processor is to
  traverse this tree and retrieve (or modify) data specified in a
  query.  A query consists of instructions to move around in the tree
  and to retrieve (or modify) named data.  The result of a query is an
  exact image of the parts of the tree that the query processor
  visited.

  The query processor is very simple -- it only understands eight
  commands, most of which share the same structure.  It is helpful to
  think of the query processor as an automaton that walks around in the
  tree, directed by commands in the query.  As it moves around, it
  copies the tree structure it traverses to the query result.  Data
  that is requested by the query is copied into the result as well.
  Data that is changed by a query is copied into the result after the
  modification is made.

4. ENCODING OF QUERIES AND RESPONSES

  Both queries and responses are encoded using the representation
  defined in ISO Standard ASN.1 (Abstract Syntax Notation 1).  ASN.1
  represents data as sequences of <tag,length,contents> triples that
  are encoded as a stream of octets.  The data tuples may be
  recursively nested to represent structured data such as arrays or
  records.  For a full description, see the ISO standards IS 8824 and
  IS 8825.  See appendix for information about obtaining these
  documents.

4.1 Notation Used in This Proposal

  The notation used in this memo is similar to that used in ASN.1, but
  less formal, smaller, and (hopefully) easier to read.  We will refer
  to a <tag,length,contents> tuple as a "data object".  In this RFC, we
  will not be concerned with the details of the object lengths.  They
  exist in the actual ASN.1 encoding, but will be omitted in the
  examples here.

  Data objects that have no internal ASN.1 structure such as integer or
  octet string are referred to as "simple types" or "simple objects".
  Objects which are constructed out of other ASN.1 data objects will be
  referred to as "composite types" or "composite objects".






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  The notation
      ID(value)
  represents a simple object whose tag is "ID" with the given value.  A
  composite object is represented as
      ID{ ... contents ... }
  where contents is a sequence of data objects.  The contents may
  include both simple and structured types, so the structure is fully
  recursive.

  The difference between simple and composite types is close to the
  meaning of the "constructor" bit in ASN.1.  For the uses here, the
  distinction is made based upon the semantics of the data, not the
  representation.  Therefore, even though an OctetString can be
  represented in ASN.1 using either constructed or non-constructed
  forms, it is conceptually a simple type, with no internal structure,
  and will always be written as
      ID("some arbitrary string")
  in this RFC.

  There are situations where it is necessary to specify a type but give
  no value, such as when referring to the name of the data.  In this
  situation, the same notation is used, but with the value omitted:
      ID   or  ID()   or   ID{}
  Such objects have zero length and no contents.  The latter two forms
  are used when a distinction is being made between simple and
  composite data, but the difference is just notation -- the
  representation is the same.

  ASN.1 distinguishes between four "classes" of tags: universal,
  application-specific, context-dependent, and reserved.  HEMS and this
  query language use the first three.  Universal tags are assigned in
  the ASN.1 standard and its addendums for common types, and are
  understood by any application using ASN.1.  Application-specific tags
  are limited in scope to a particular application.  These are used for
  "well-known" identifiers that must be recognizable in any context,
  such as derived data types.  Finally, context-dependent tags are used
  for objects whose meaning is dependent upon where they are
  encountered.  Most tags that identify data are context-dependent.

5. DATA ORGANIZATION

  Data in a monitored entity is modeled as a hierarchy.
  Implementations are not required to organize the data internally as a
  hierarchy, but they must provide this view of the data through the
  query language.  A hierarchy offers useful structure for the
  following operations:





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  Organization    A hierarchy allows related data to be grouped
                  together in a natural way.

  Naming          The name of a piece of data is just the path from the
                  root to the data of interest.

  Mapping onto ASN.1
                  ASN.1 can easily represent a hierarchy by using a
                  "constructor" type as an envelope for an entire
                  subtree.

  Efficient Representation
                  Hierarchical structures are compact and can be
                  traversed quickly.

  Safe Locking    If it is necessary to lock part of the hierarchy (for
                  example, when doing an update), locking an entire
                  subtree can be done efficiently and safely, with no
                  danger of deadlock.

  We will use the term "data tree" to refer to this entire structure.
  Note that this internal model is completely independent of the
  external ASN.1 representation -- any other suitable representation
  would do.  For the sake of efficiency, we do make a one-to-one
  mapping between ASN.1 tags and the (internal) names of the nodes.
  The same could be done for any other external representation.

  Each node in the hierarchy must have names for its component parts.
  Although we would normally think of names as being ASCII strings such
  as "input errors", the actual name is just an ASN.1 tag.  Such names
  are small integers (typically, less than 30) and so can easily be
  mapped by the monitored entity onto its internal representation.

  We use the term "dictionary" to mean an internal node in the
  hierarchy.  Leaf nodes contain the actual data.  A dictionary may
  contain both leaf nodes and other dictionaries.

5.1 Example Data Tree

  Here is a possible organization of the hierarchy in an entity that
  has several network interfaces and does IP routing.  The exact
  organization of data in entities is specified in RFC-1024.  This
  skeletal data tree will be used throughout this RFC in query
  examples.

         System {
                 name                            -- host name
                 clock-msec                      -- msec since boot



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                 interfaces                      -- # of interfaces
                 memory
                 }
         Interfaces {                            -- one per interface
                 InterfaceData{ address, mtu, netMask, ARP{...}, ... }
                 InterfaceData{ address, mtu, netMask, ARP{...}, ... }
                                 :
                 }
         IPRouting {
                 Entry{ ip-addr, interface, cost, ... }
                 Entry{ ip-addr, interface, cost, ... }
                                 :
                 }

     There are three top-level dictionaries in this hierarchy (System,
     Interfaces, and IPRouting) and three other dictionary types
     (InterfaceData, Entry, and ARP), each with multiple instances.

     The "name" of the clock in this entity would be:
         system{ clock-msec }
     and the name of a routing table entry's IP address would be:
         IPRouting{ Entry{ ip-addr } }.

     More than one piece of data can be named by a single ASN.1 object.
     The entire collection of system information is named by:
         system
     and the name of a routing table's IP address and cost would be:
         IPRouting{ Entry{ ip-addr, cost } }.

5.2 Arrays

  There is one sub-type of a dictionary that is used as the basis for
  tables of objects with identical types.  We call these dictionaries
  arrays.  In the example above, the dictionaries for interfaces,
  routing tables, and ARP tables are all arrays.

  In the examples above, the "ip-addr" and "cost" fields are named.  In
  fact, these names refer to the field values for ALL of the routing
  table entries -- the name doesn't (and can't) specify which routing
  table entry is intended.  This ambiguity is a problem wherever data
  is organized in tables.  If there was a meaningful index for such
  tables (e.g., "routing table entry #1"), there would be no problem.
  Unfortunately, there usually isn't such an index.  The solution to
  this problem requires that the data be accessed on the basis of some
  of its content.  Filters, discussed in section 8.6, provide this
  mechanism.

  The primary difference between arrays and plain dictionaries is that



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  arrays may contain only one type of item, while dictionaries, in
  general, will contain many different types of items.  For example,
  the dictionary IPRouting (which is an array) will contain only items
  of type Entry.

  The fact that these objects are viewed externally as arrays or tables
  does not mean that they are represented in an implementation as
  linear lists of objects.  Any collection of same-typed objects is
  viewed as an array, even though it might be stored internally in some
  other format, for example, as a hash table.

6. COMPONENTS OF A QUERY

  A HEMS query consists of a sequence of ASN.1 objects, interpreted by
  a simple stack-based interpreter.  [Although we define the query
  language in terms of the operations of a stack machine, the language
  does not require an implementation to use a stack machine.  This is a
  well-understood model, and is easy to implement.]  One ASN.1 tag is
  reserved for operation codes; all other tags indicate data that will
  eventually be used by an operation.  These objects are pushed onto
  the stack when received.  Opcodes are immediately executed and may
  remove or add items to the stack.  Because ASN.1 itself provides
  tags, very little needs to be done to the incoming ASN.1 objects to
  make them suitable for use by the query interpreter.

  Each ASN.1 object in a query will fit into one of the following
  categories:

  Opcode    An opcode tells the query interpreter to perform an action.
            They are described in detail in section 8.  Opcodes are
            represented by an application-specific type whose value
            determines the operation.

  Template  These are objects that name one or more items in the data
            tree.  Named items may be either simple items (leaf nodes)
            or entire dictionaries, in which case the entire subtree
            "underneath" the dictionary is understood.  Templates are
            used to select specific data to be retrieved from the data
            tree.  A template may be either simple or structured,
            depending upon what it is naming.  A template only names
            the data -- there are no values contained in it.  Therefore
            the leaf objects in a template will all have a length of
            zero.

            Examples of very simple templates are:
                name()   or   System{}
            Each of these is just one ASN.1 data object, with zero
            length.  The first names a single data item in the "System"



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            dictionary (and must appear in that context), and the
            second names the entire "System" dictionary.  A more
            complex template such as:
                Interfaces{ InterfaceData{ address, netMask, ARP } }
            names two simple data items and a dictionary, iterated over
            all occurrences of "InterfaceData" within the Interfaces
            array.

  Path      A path is a special case of a template that names only a
            single node in the tree.  It specifies a path down into the
            dictionary tree and names exactly one node in the
            dictionary tree.

  Value     These are used to give data values when needed in a query,
            for example, when changing a value in the data tree.  A
            value can be thought of as either a filled-in template or
            as the ASN.1 representation some part of the data tree.

  Filter    A boolean expression that can be executed in the context of
            a particular dictionary that is used to select or not
            select items in the dictionary.  The expressions consist of
            the primitives "equal", "greater-or-equal",
            "less-or-equal", and "present" possibly joined by "and",
            "or", and "not".  (See section 8.6.)

  Values, Paths, and Templates usually have names in the context-
  dependent class, except for a few special cases, which are in the
  application-specific class.

7. REPLY TO A QUERY

  The data returned to the monitoring entity is a sequence of ASN.1
  data items.  Conceptually, the reply is a subset of the data tree,
  where the query selects which portions are to be included.  This is
  exactly true for data retrieval requests, and essentially true for
  data modification requests -- the reply contains the data after it
  has been modified.  The key point is that the data in a reply
  represents the state of the data tree immediately after the query was
  executed.

  The sequence of the data is determined by the sequence of query
  language operations and the order of data items within Templates and
  Values given as input to these operations.  If a query requests data
  from two of the top-level dictionaries in the data tree, by giving
  two templates such as:

         System{ name, interfaces }
         Interfaces{



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                 InterfaceData { address, netMask, mtu }
                 }

  then the response will consist of two ASN.1 data objects, as follows:

         System {
                 name("system name"),
                 interfaces(2)
                 }
         Interfaces {
                 InterfaceData { address(36.8.0.1),
                                 netMask(FFFF0000),
                                 mtu(1500)
                                 }
                 InterfaceData { address(10.1.0.1),
                                 mtu(1008),
                                 netMask(FF000000)
                                 }
                 }

  With few exceptions, each of the data items in the hierarchy is named
  in the context-specific ASN.1 type space.  Because of this, the
  returned objects must be fully qualified.  For example, the name of
  the entity must always be returned encapsulated inside an ASN.1
  object for "System".  If it were not, there would be no way to tell
  if the object that was returned was "name" inside the "System"
  dictionary or "address" inside the "interfaces" dictionary (assuming
  in this case that "name" and "address" were assigned the same integer
  as their ASN.1 tags).

  Having fully-qualified data simplifies decoding of the data at the
  receiving end and allows the tags to be locally chosen.  Definitions
  for tags within routing tables won't conflict with definitions for
  tags within interfaces.  Therefore, the people doing the name
  assignments are less constrained.  In addition, most of the
  identifiers will be fairly small integers, which is an advantage
  because ASN.1 can fit tag numbers up to 30 in a one-octet tag field.
  Larger numbers require a second octet.

  If data is requested that doesn't exist, either because the tag is
  not defined, or because an implementation doesn't provide that data
  (such as when the data is optional), the response will contain an
  ASN.1 object that is empty.  The tag will be the same as in the
  query, and the object will have a length of zero.

  The same response is given if the requested data does exist, but the
  invoker of the query does not have authorization to access it.  See
  section 10 for more discussion of authorization mechanisms.



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  This allows completely generic queries to be composed without regard
  to whether the data is defined or implemented at all of the entities
  that will receive the query.  All of the available data will be
  returned, without generating errors that might otherwise terminate
  the processing of the query.

8. QUERY LANGUAGE

  The query language is designed to be expressive enough to write
  useful queries with, yet simple enough to be easy to implement.  The
  query processor should be as simple and fast as possible, in order to
  avoid placing a burden on the monitored entity, which may be a
  critical node such as a gateway.

  Although queries are formed in a flexible way using what we term a
  "language", this is not a programming language.  There are operations
  that operate on data, but most other features of programming
  languages are not present.  In particular:

        - Programs are not stored in the query processor.

        - The only form of temporary storage is a stack, of limited
          depth.

        - There are no subroutines.

        - There are no explicit control structures defined in the
          language.

  The central element of the language is the stack.  It may contain
  templates, (and therefore paths), values, and filters taken from the
  query.  In addition, it can contain dictionaries (and therefore
  arrays) from the data tree.  At the beginning of a query, it contains
  one item, the root dictionary.

  The overall operation consists of reading ASN.1 objects from the
  input stream.  All objects that aren't opcodes are pushed onto the
  stack as soon as they are read.  Each opcode is executed immediately
  and may remove items from the stack, may generate ASN.1 objects and
  send them to the output stream, and may leave items on the stack.
  Because each input object is dealt with immediately, portions of the
  response may be generated while the query is still being received.

  In the descriptions below, operator names are in capital letters,
  preceded by the arguments used from the stack and followed by results
  left on the stack.  For example:





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  OP                             a b   OP   a t
            means that the OP operator takes <a> and <b> off of the
            stack and leaves <t> on the stack.  Most of the operators
            in the query language leave the first operand (<a> in this
            example) on the stack for future use.

  If both <a> and <b> were received as part of the query (as opposed to
  being calculated by previous operations), then this part of the query
  would have consisted of the sequence:
      <a>
      <b>
      OP
  So, like other stack-based languages, the arguments and operators
  must be presented in postfix order, with an operator following its
  operands.

  Here is a summary of all of the operators defined in the query
  language.  Most of the operators can take several different sets of
  operands and behave differently based upon the operand types.
  Details and examples are given later.

  BEGIN                   dict1 path   BEGIN   dict1 dict
                   array path filter   BEGIN   array dict
            Move down in the data tree, establishing a context for
            future operations.

  END                           dict   END   --
            Undo the most recent BEGIN.

  GET                           dict   GET   dict
                       dict template   GET   dict
               array template filter   GET   array
            Retrieve data from the data tree.

  GET-ATTRIBUTES
                                dict   GET-ATTRIBUTES   dict
                       dict template   GET-ATTRIBUTES   dict
               array template filter   GET-ATTRIBUTES   array
            Retrieve attribute information about data in the data tree.

  GET-RANGE   dict path start length   GET-RANGE   dict
            Retrieve a subrange of an OctetString.  Used for reading
            memory.

  SET                     dict value   SET   dict
                  array value filter   SET   array
            Change values in the data tree, possibly performing control
            functions.



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  CREATE                 array value   CREATE   dict
            Create new table entries.

  DELETE                array filter   DELETE   array
            Delete table entries.

  These operators are defined so that it is impossible to generate an
  invalid query response.  Since a response is supposed to be a
  snapshot of a portion (or portions) of the data tree, it is important
  that only data that is actually in the tree be put in the response.
  Two features of the language help guarantee this:

     - Data is put in the response directly from the tree (by
       GET-*).  Data does not go from the tree to the stack and
       then into the response.

     - Dictionaries on the stack are all derived from the initial,
       root dictionary.  The operations that manipulate
       dictionaries (BEGIN and END) also update the response with
       the new location in the tree.

8.1 Moving Around in the Data Tree

  The initial point of reference in the data tree is the root.  That
  is, operators name data starting at the root of the tree.  It is
  useful to be able to move to some other dictionary in the tree and
  then name data from that point.  The BEGIN operator moves down in the
  tree and END undoes the last unmatched BEGIN.

  BEGIN is used for two purposes:

     - By moving to a dictionary closer to the data of interest,
       the name of the data can be shorter than if the full name
       (from the root) were given.

     - It is used to establish a context for filtered operations
       to operate in.  Filters are discussed in section 8.6.

  BEGIN                   dict1 path   BEGIN    dict1 dict
            Follow <path> down the dictionary starting from <dict1>.
            Push the final dictionary named by <path> onto the stack.
            <path> must name a dictionary (not a leaf node).  At the
            same time, produce the beginning octets of an ASN.1 object
            corresponding to the new dictionary.  It is up to the
            implementation to choose between using the "indefinite
            length" representation or the "definite length" form and
            going back and filling the length in later.




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  END                           dict   END   --
            Pop <dict> off of the stack and terminate the open ASN.1
            object(s) started by the matching BEGIN.  Must be paired
            with a BEGIN.  If an END operation pops the root dictionary
            off of the stack, the query is terminated.

  <path> must point to a regular dictionary.  If any part of it refers
  to a non-existent node, if it points to a leaf node, or if it refers
  to a node inside an array-type dictionary, then it is in error, and
  the query is terminated immediately.

  An additional form of BEGIN, which takes a filter argument, is
  described later.

8.2 Retrieving Data

  The basic model that all of the data retrieval operations follow is
  that they take a template and fill in the leaf nodes of the template
  with the appropriate data values.

  GET                  dict template   GET   dict
            Emit an ASN.1 object with the same "shape" as the given
            template, except with values filled in for each node.  The
            first ASN.1 tag of <template> should refer to an object in
            <dict>.  If a dictionary tag is supplied anywhere in
            <template>, the entire dictionary contents are emitted to
            the response.  Any items in the template that are not in
            <dictionary> (or its components) are represented as objects
            with a length of zero.

                                dict   GET   dict
            If there is no template, get all of the items in the
            dictionary.  This is equivalent to providing a template
            that lists all of the items in the dictionary.

  An additional form of GET, which takes a filter argument, is
  described later.

  Here is an example of using the BEGIN operator to move down the data
  tree to the TCP dictionary and then using the GET operator to
  retrieve 5 data values from the TCP Stats dictionary:

      IPTransport{ TCP } BEGIN
      Stats{ octetsIn, octetsOut, inputPkts, outputPkts, badtag } GET
      END






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  This might return:

      IPTransport{ TCP
          Stats{ octetsIn(13255), octetsOut(82323),
                 inputPkts(9213), outputPkts(12425), badtag() }
      }

  "badtag" is a tag value that is undefined.  No value is returned for
  it, indicating that there is no data value associated with it.

8.3 Data Attributes

  Although ASN.1 "self-describes" the structure and syntax of the data,
  it gives no information about what the data means.  For example, by
  looking at the raw data, it is possible to tell that an item is of
  type [context 5] and is 4 octets long.  That does not tell how to
  interpret the data (is this an integer, an IP address, or a 4-
  character string?) or what the data means (IP address of what?).
  Even if the data were "tagged", in ASN.1 parlance, that would only
  give the base type (e.g., IP-address or counter) and not the meaning.

  Most of the time, this information will come from RFC-1024, which
  defines the ASN.1 tags and their precise meaning.  When extensions
  have been made, it may not be possible to get documentation on the
  extensions.  (Extensions are discussed in section 9.)

  The GET-ATTRIBUTES operator is similar to the GET operator, but
  returns a set of attributes describing the data rather than the data
  itself.  This information is intended to be sufficient to let a human
  understand the meaning of the data and to let a sophisticated
  application treat the data appropriately.  Such an application could
  use the attribute information to format the data on a display and
  decide whether it is appropriate to subtract one sample from another.

  Some of the attributes are textual descriptions to help a human
  understand the nature of the data and provide meaningful labels for
  it.  Extensive descriptions of standard data are optional, since they
  are defined in RFC-1024.  Complete descriptions of extensions must be
  available, even if they are documented in a user's manual.  Network
  firefighters may not have a current manual handy when the network is
  broken.

  The format of the attributes is not as simple as the format of the
  data itself.  It isn't possible to use the data's tag, since that
  would look exactly like the data itself.  The format is:

      Attributes ::= [APPLICATION 3] IMPLICIT SEQUENCE {
              tagASN1         [0] IMPLICIT INTEGER,



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              valueFormat     [1] IMPLICIT INTEGER,
              longDesc        [2] IMPLICIT IA5String OPTIONAL,
              shortDesc       [3] IMPLICIT IA5String OPTIONAL,
              unitsDesc       [4] IMPLICIT IA5String OPTIONAL,
              precision       [5] IMPLICIT INTEGER OPTIONAL,
              properties      [6] IMPLICIT BITSTRING OPTIONAL,
              valueSet        [7] IMPLICIT SET OF valueDesc OPTIONAL
              }

  The GET-ATTRIBUTES operator is similar to the GET operator.  The
  major difference is that dictionaries named in the template do not
  elicit data for the entire subtree.

  GET-ATTRIBUTES
                       dict template   GET-ATTRIBUTES   dict
            Emit a single ASN.1 Attributes object for each of the
            objects named in <template>.  For each of these, the
            tagASN1 field will be set to the corresponding tag from the
            template.  The rest of the fields are set as appropriate
            for the data object.  Any items in the template that are
            not in <dictionary> (or its components) elicit an
            Attributes object with a valueFormat of NULL, and no other
            descriptive information.

  or
                                dict   GET-ATTRIBUTES   dict
            If there is no template, emit Attribute objects for all of
            the items in the dictionary.  This is equivalent to
            providing a template that lists all of the items in the
            dictionary.  This allows a complete list of a dictionary's
            contents to be obtained.

  An additional form of GET-ATTRIBUTES, which takes a filter argument,
  is described later.

  Here is an example of using the GET-ATTRIBUTES operator to request
  attributes for three objects in the System dictionary:

      System{ name, badtag, clock-msec } GET-ATTRIBUTES

  "badtag" is some unknown tag.  The result might be:

      System{
              Attributes{
                      tagASN1(name),
                      valueFormat(IA5String),
                      longDesc("The primary hostname."),




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                      shortDesc("hostname")
              },
              Attributes{
                      tagASN1(badtag), valueFormat(NULL)
              }
              Attributes{
                      tagASN1(clock-msec),
                      valueFormat(Integer),
                      longDesc("milliseconds since boot"),
                      shortDesc("uptime"), unitsDesc("ms")
                      precision(4294967296),
                      properties(1)
              }

  Note that in this example "name" and "clock-msec" are integer values
  for the ASN.1 tags for the two data items.  "badtag" is an integer
  value that has no corresponding name in this context.

  There will always be exactly as many Attributes items in the result
  as there are objects in the template.  Attributes objects for items
  which do not exist in the entity will have a valueFormat of NULL and
  none of the optional elements will appear.

      [ A much cleaner method would be to store the attributes as
      sub-components of the data item of interest.  For example,
      requesting
          System{ clock-msec }  GET
      would normally just get the value of the data.  Asking for an
      additional layer down the tree would now get its attributes:
          System{ clock-msec{ shortDesc, unitsDesc }  GET
      would get the named attributes.  (The attributes would be
      named with application-specific tags.)  Unfortunately, ASN.1
      doesn't provide a notation to describe this type of
      organization.  So, we're stuck with the GET-ATTRIBUTES
      operator.  However, if a cleaner organization were possible,
      this decision would have been made differently. ]

8.4 Examining Memory

  Even with the ability to symbolically access all of this information
  in an entity, there will still be times when it is necessary to get
  to very low levels and examine memory, as in remote debugging
  operations.  The building blocks outlined so far can easily be
  extended to allow memory to be examined.

  Memory is modeled as an ordinary object in the data tree, with an
  ASN.1 representation of OctetString.  Because of the variety of
  addressing architectures in existence, the conversion from the



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  internal memory model to OctetString is very machine-dependent.  The
  only simple case is for byte-addressed machines with 8 bits per byte.

  Each address space in an entity is represented by one "memory" data
  item.  In a one-address-space situation, this dictionary will
  probably be in "System" dictionary.  If each process has its own
  address space, then one "memory" item might exist for each process.
  Again, this is very machine-dependent.

  Although the GET-RANGE operator is provided primarily for the purpose
  of retrieving the contents of memory, it can be used on any object
  whose base type is OctetString.

  GET-RANGE   dict path start length   GET-RANGE   dict
            Get <length> elements of the OctetString, starting at
            <start>.  <start> and <length> are both ASN.1 INTEGER type.
            <path>, starting from <dict>, must specify a node
            representing memory, or some other OctetString.

  The returned data may not be <length> octets long, since it may take
  more than one octet to represent one memory location.

  Memory items in the data tree are special in that they will not
  automatically be returned when the entire contents of a dictionary
  are requested.  e.g., If memory is part of the "System" dictionary,
  then the query
      System GET
  will emit the entire contents of the System dictionary, but not the
  memory item.

8.5 Control Operations:  Modifying the Data Tree

  All of the operators defined so far only allow data in an entity to
  be retrieved.  By replacing the template argument used in the GET
  operators with a value, data in the entity can be changed.  Very few
  items in the data tree can be changed; those that can are noted in
  RFC-1024.

  Values in the data tree can modified in order to change configuration
  parameters, patch routing tables, etc.  Control functions, such as
  bringing an interface "down" or "up", do not usually map directly to
  changing a value.  In such cases, an item in the tree can be defined
  to have arbitrary side-effects when a value is assigned to it.
  Control operations then consist of "setting" this item to an
  appropriate command code.  Reading the value of such an item might
  return the current status.  Again, details of such data tree items
  are given in RFC-1024.




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  This "virtual command-and-status register" model is very powerful,
  and can be extended by an implementation to provide whatever controls
  are needed.  It has the advantage that the control function is
  associated with the controlled object in the data tree.  In addition,
  no additional language features are required to support control
  functions, and the same operations used to locate data for retrieval
  are used to describe what is being controlled.

  For all of the control and data modification operations, the fill-
  in-the-blank model used for data retrieval is extended: the response
  to an operation is the affected part of the data tree, after the
  operation has been executed.  Therefore, for normal execution, SET
  and CREATE will return the object given as an argument, and DELETE
  will return nothing (because the affected portion was deleted).

  SET                     dict value   SET   dict
            Set the value(s) of data in the entity to the value(s)
            given in <value>.  The result will be the value of the data
            after the SET.  Attempting to set a non-settable item will
            not produce an error, but will yield a result in the reply
            different from what was sent.

  CREATE                 array value   CREATE   dict
            Insert a new entry into <array>.  Depending upon the
            context, there may be severe restrictions about what
            constitutes a valid <value>.  The result will be the actual
            item added to the <array>.  Note that only one item can be
            added per CREATE operation.

  DELETE                array filter   DELETE   array
            Delete the entry(s) in <array> that match <filter>.
            Filters are described later in this document.  Normally, no
            data items will be produced in the response, but if any of
            the items that matched the filter could not be deleted,
            they will be returned in the response.

  An additional form of SET, which takes a filter argument, is
  described later.

  Here is an example of attempting to use SET to change the number of
  interfaces in an entity:
      System{ interfaces(5) } SET
  Since that is not a settable parameter, the result would be:
      System{ interfaces(2) }
  giving the old value.

  Here is an example of how CREATE would be used to add a routing table
  entry for net for 128.89.0.0.



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      IPRouting BEGIN                   -- get dictionary
      Entries{ DestAddr(128.89.0.0), ... }    -- entry to insert
      CREATE
      END                                 -- finished with dict

  The result would be what was added:
      IPRouting{ Entries{ DestAddr(128.89.0.0), ... } }

  The results in the response of these operators is consistent of the
  global model of the response:  it contains a subset of the data in
  the tree immediately after the query is executed.

  Note that CREATE and DELETE only operate on arrays, and then only on
  arrays that are specifically intended for it.  For example, it is
  quite reasonable to add and remove entries from routing tables or ARP
  tables, both of which are arrays.  However, it doesn't make sense to
  add or remove entries in the "Interfaces" dictionary, since the
  contents of that array is dictated by the hardware.  For each array
  in the data tree, RFC-1024 indicates whether CREATE and DELETE are
  valid.

  CREATE and DELETE are always invalid in non-array contexts.  If
  DELETE were allowed on monitored data, then the deleted data would
  become unmonitorable to the entire world.  Conversely, if it were
  possible to CREATE arbitrary dictionary entries, there would be no
  way to give such entries any meaning.  Even with the data in place,
  there is nothing that would couple the data to the operation of the
  monitored entity. [Creation and deletion would also add considerable
  complication to an implementation, because without them, all of the
  data structures that represent the data tree are essentially static,
  with the exception of dynamic tables such as the ones mentioned,
  which already have mechanisms in place for adding and removing
  entries.]

8.6 Associative Data Access:  Filters

  One problem that has not been dealt with was alluded to earlier: When
  dealing with array data, how do you specify one or more entries based
  upon some value in the array entries?  Consider the situation where
  there are several interfaces.  The data might be organized as:

      Interfaces {                            -- one per interface
              InterfaceData { address, mtu, netMask, ARP{...}, ... }
              InterfaceData { address, mtu, netMask, ARP{...}, ... }
                              :
              }

  If you only want information about one interface (perhaps because



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  there is an enormous amount of data about each), then you have to
  have some way to name it.  One possibility would be to just number
  the interfaces and refer to the desired interface as
      InterfaceData(3)
  for the third one.

  But this is not sufficient, because interface numbers may change over
  time, perhaps from one reboot to the next.  It is even worse when
  dealing with arrays with many elements, such as routing tables, TCP
  connections, etc.  Large, changing arrays are probably the more
  common case, in fact.  Because of the lack of utility of indexing in
  this context, there is no general mechanism provided in the language
  for indexing.

  A better scheme is to select objects based upon some value contained
  in them, such as the IP address.  The query language uses filters to
  select specific table entries that an operator will operate on.  The
  operators BEGIN, GET, GET-ATTRIBUTES, SET, and DELETE can take a
  filter argument that restricts their operation to entries that match
  the filter.

  A filter is a boolean expression that is executed for each element in
  an array.  If an array entry "matches" the filter (i.e., if the filter
  produces a "true" result), then it is used by the operation.  A
  filter expression is very restricted: it can only compare data
  contained in the array element and the comparisons are only against
  constants.  Comparisons may be connected by AND, OR and NOT
  operators.

  The ASN.1 definition of a filter is:

      Filter          ::= [APPLICATION 2] CHOICE {
                              present         [0] DataPath,
                              equal           [1] DataValue,
                              greaterOrEqual  [2] DataValue,
                              lessOrEqual     [3] DataValue,
                              and             [4] SEQUENCE OF Filter,
                              or              [5] SEQUENCE OF Filter,
                              not             [6] Filter
                              }

      DataPath        ::= ANY                 -- Path with no value

      DataValue       ::= ANY                 -- Single data value

  This definition is similar to the filters used in the ISO monitoring
  protocol (CMIP) and was derived from that specification.




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  "DataPath" is the name of a single data item; "DataValue" is the
  value of a single data item.  The three comparisons are all of the
  form "data OP constant", where "data" is the value from the tree,
  "constant" is the value from the filter expression, and "OP" is one
  of equal, greater-than-or-equal, or less-than-or-equal.  The last
  operation, "present", tests to see if the named item exists in the
  data tree.  By its nature, it requires no value, so only a path needs
  to be given.

  Here is an example of a filter that matches an Interface whose IP
  address is 10.1.0.1:
      Filter{ equal{ address(10.0.0.51) } }
  Note that the name of the data to be compared is relative to the
  "InterfaceData" dictionary.

  Each operator, when given a filter argument, takes an array
  (dictionary containing only one type of item) as its first argument.
  In the current example, this would be "Interfaces".  The items in it
  are all of type "InterfaceData".  This tag is referred to as the
  "iteration tag".

  Before a filtered operation is used, BEGIN must be used to put the
  array (dictionary) on top of the stack, to establish it as the
  context that the filter iterates over.  The general operation of a
  filtered operation is then:

        1. Iterate over the items in the array.

        2. For each element in the array, execute the filter.

        3. If the filter succeeds, do the requested operation
           (GET/SET/etc.) on the matched element, using the
           template/value/path as input to the operation.  At this
           point, the execution of the operation is the same as in
           the non-filtered case.

  This is a model of operation; actual implementations may take
  advantage of whatever lookup techniques are available for the
  particular table (array) involved.

  Therefore, there are three inputs to a filtered operation:

        1. The "current dictionary" on the stack.  This is the
           array-type dictionary to be searched, set by an earlier
           BEGIN.

        2. A filter, to test each item in the array.  Each path or
           value mentioned in the filter must be named in the context



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           of an item in the array, as if it was the current
           dictionary.  For example, in the case where a filtered
           operation iterates over the set of "InterfaceData" items
           in the "Interfaces" array, each value or path in the
           filter should name an item in the "InterfaceData"
           dictionary, such as "address".

        3. A template, path, or value associated with the operation
           to be performed.  The leading ASN.1 tag in this must match
           the iteration tag.  In the current example where the
           filter is searching the "Interfaces" dictionary, the first
           tag in the template/tag/value must be "InterfaceData".

  The operators which take filters as arguments are:

  BEGIN            array path filter   BEGIN   array dict
            Find a dictionary in <array> that matches <filter>.  Use
            that as the starting point for <path> and push the
            dictionary corresponding to <path> onto the stack.  If more
            than one dictionary matches <filter>, then any of the
            matches may be used.  This specification does not state how
            the choice is made.  At least one dictionary must match; it
            is an error if there are no matches.  (Perhaps it should be
            an error for there to be multiple matches; actual
            experience is needed to decide.)

  GET          array template filter   GET   array
            For each item in <array> that matches <filter>, fill in the
            template with values from the data tree and emit the
            result.  The first tag of <template> must be equal to the
            iteration tag.  Selected parts of matched items are emitted
            based upon <template>, just as in a non-filtered GET
            operation.

  GET-ATTRIBUTES
               array template filter   GET-ATTRIBUTES   array
            Same as GET, except emit attributes rather than data
            values.

  SET             array value filter   SET   array
            Same as GET, except set the values in <value> rather than
            retrieving values.  Several values in the data tree will be
            changed if the filter matches more than one item in the
            array.

  DELETE                array filter   DELETE   array
            Delete the entry(s) in <array> that match <filter>.




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  Notes about filter execution:

     - Expressions are executed by inorder tree traversal.

     - Since the filter operations are all GETs and comparisons,
       there are no side-effects to filter execution, so an
       implementation is free to execute only as much of the
       filter as required to produce a result (e.g., don't execute
       the rest of an AND if the first comparison turns out to be
       false).

     - It is not an error for a filter to test a data item that
       isn't in the data tree.  In this situation, the comparison
       just fails (is false).  This means that filters don't need
       to test for the existence of optional data before
       attempting to compare it.

  Here is an example of how filtering would be used to obtain the input
  and output packet counts for the interface with IP address 10.0.0.51.

      Interfaces BEGIN                      -- dictionary
      InterfaceData{ pktsIn, pktsOut }      -- template
      Filter{ equal{ address(10.0.0.51) } }
      GET
      END                                   -- finished with dict

  The returned value would be something like:

      Interfaces{                             -- BEGIN
        InterfaceData{ pktsIn(1345134), pktsOut(1023729) }
                                              -- GET
      }                                       -- END

  The annotations indicate which part of the response is generated by
  the different operators in the query.

  Here is an example of accessing a table contained within some other
  table.  Suppose we want to get at the ARP table for the interface
  with IP address 36.8.0.1 and retrieve the entire ARP entry for the
  host with IP address 36.8.0.23.  In order to retrieve a single entry
  in the ARP table (using a filtered GET), a BEGIN must be used to get
  down to the ARP table.  Since the ARP table is contained within the
  Interfaces dictionary (an array), a filtered BEGIN must be used.

      Interfaces BEGIN                        -- dictionary
      InterfaceData{ ARP }                    -- path
      Filter{ equal{ address(36.8.0.1) } }    -- filter
      BEGIN                                   -- filtered BEGIN



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      -- Now in ARP table for 38.0.0.1; get entry for 38.8.0.23.
      addrMap                                 -- whole entry
      Filter{ equal{ ipAddr(36.8.0.23) } }    -- filter
      GET                                     -- filtered GET
      END
      END

  The result would be:

      Interfaces{                             -- first BEGIN
        InterfaceData{ ARP{                   -- second BEGIN
          addrMap{ ipAddr(36.8.0.23), physAddr(..) } -- from GET
        } }                                   -- first END
      }                                       -- second END

  Note which parts of the output are generated by different parts of
  the query.

  Here is an example of how the SET operator would be used to shut down
  the interface with ip-address 10.0.0.51 by changing its status to
  "down".

      Interfaces BEGIN                    -- get dictionary
      Interface{ Status(down) }           -- value to set
      Filter{ equal{ IP-addr(10.0.0.51) } }
      SET
      END

  If the SET is successful, the result would be:

      Interfaces{                             -- BEGIN
          Interface{ Status(down) }           -- from SET
      }                                       -- END

8.7 Terminating a Query

  A query is implicitly terminated when there are no more ASN.1 objects
  to be processed by the interpreter.  For a perfectly-formed query,
  the interpreter would be back in the state it was when it started:
  the stack would have only the root dictionary on it, and all of the
  ASN.1 objects in the result would be terminated.

  If there are still "open" ASN.1 objects in the result (caused by
  leaving ENDs off of the query), then these are closed, as if a
  sufficient number of ENDs were provided.  This condition would be
  indicated by the existence of dictionaries other than the root
  dictionary on the stack.




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  If an extra END is received that would pop the root dictionary off of
  the stack, the query is terminated immediately.  No error is
  generated.

9. EXTENDING THE SET OF VALUES

  There are two ways to extend the set of values understood by the
  query language.  The first is to register the data and its meaning
  and get an ASN.1 tag assigned for it.  This is the preferred method
  because it makes that data specification available for everyone to
  use.

  The second method is to use the VendorSpecific application type to
  "wrap" the vendor-specific data.  Wherever an implementation defines
  data that is not in RFC-1024, the "VendorSpecific" tag should be used
  to label a dictionary containing the vendor-specific data.  For
  example, if a vendor had some data associated with interfaces that
  was too strange to get standard numbers assigned for, they could,
  instead represent the data like this:

         interfaces {
                 interface {
                         in-pkts, out-pkts, ...
                         VendorSpecific { ephemeris, declination }
                         }
                 }

  In this case, ephemeris and declination correspond to two context-
  dependent tags assigned by the vendor for their non-standard data.

  If the vendor-specific method is chosen, the private data MUST have
  descriptions available through the GET-ATTRIBUTES operator.  Even
  with this descriptive ability, the preferred method is to get
  standard numbers assigned if possible.

10. AUTHORIZATION

  This specification does not state what type of authorization system
  is used, if any.  Different systems may have needs for different
  mechanisms (authorization levels, capability sets, etc.), and some
  systems may not care about authorization at all.  The only effect
  that an authorization system has on a query is to restrict what data
  items in the tree may be retrieved or modified.

  Therefore, there are no explicit query language features that deal
  with protection.  Instead, protection mechanisms are implicit and may
  make some of the data invisible (for GET) or non-writable (for SET):




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     - Each query runs with some level of authorization or set of
       capabilities, determined by its environment (HEMS and the
       HEMP header).

     - Associated with each data item in the data tree is some
       sort of test to determine if a query's authorization should
       grant it access to the item.

  Authorization tests are only applied to query language operations
  that retrieve information (GET, GET-ATTRIBUTES, and GET-RANGE) or
  modify it (SET, CREATE, DELETE).  An authorization system must not
  affect the operation of BEGIN and END.  In particular, the
  authorization must not hide entire dictionaries, because that would
  make a BEGIN on such a dictionary fail, terminating the entire query.

11. ERRORS

  If some particular information is requested but is not available, it
  will be returned as "no-value" by giving the ASN.1 length as 0.

  When there is any other kind of error, such as having improper
  arguments on the top of the stack or trying to execute BEGIN when the
  path doesn't refer to a dictionary, an ERROR object is emitted.

  The contents of this object identify the exact nature of the error:

         Error ::= [APPLICATION 0] IMPLICIT SEQUENCE {
                 errorCode       INTEGER,
                 errorInstance   INTEGER,
                 errorOffset     INTEGER
                 errorDescription IA5String,
                 errorOp         INTEGER,
                 }

  errorCode identifies what the error was, and errorInstance is an
  implementation-dependent code that gives a more precise indication of
  where the error occured.  errorOffset is the location within the
  query where the error occurred.  If an operation was being executed,
  errorOp contains its operation code, otherwise zero.
  errorDescription is a text string that can be printed that gives some
  description of the error.  It will at least describe the errorCode,
  but may also give details implied by errorInstance.  Detailed
  definitions of all of the fields are given in appendix I.2.

  Since there may be several unterminated ASN.1 objects in progress at
  the time the error occurs, each one must be terminated.  Each
  unterminated object will be closed with a copy of the ERROR object.
  Depending upon the type of length encoding used for this object, this



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  will involve filling the value for the length (definite length form)
  or emitting two zero octets (indefinite length form).  After all
  objects are terminated, a final copy of the ERROR object will be
  emitted.  This structure guarantees that the error will be noticed at
  every level of interpretation on the receiving end.

  In summary, if there was an error before any ASN.1 objects were
  generated, then the result would simply be:
      error{...}

  If a couple of ASN.1 objects were unterminated when the error
  occurred, the result might look like:
      interfaces{
           interface { name(...) type(...) error{...} }
           error{...}
           }
      error{...}

  It would be possible to define a "WARNING" object that has a similar
  (or same) format as ERROR, but that would be used to annotate
  responses when a non-fatal "error" occurs, such as attempting to
  SET/CREATE/DELETE and the operation is denied.  This would be an
  additional complication, and we left it out in the interests of
  simplicity.

I. ASN.1 DESCRIPTIONS OF QUERY LANGUAGE COMPONENTS

  A query consists of a sequence of ASN.1 objects, as follows:

      Query := IMPLICIT SEQUENCE of QueryElement;

      QueryElement ::= CHOICE {
              Operation,
              Filter,
              Template,
              Path,
              InputValue
              }

  Operation and Filter are defined below.  The others are:

      Template        ::= any
      Path            ::= any
      InputValue      ::= any

  These three are all similar, but have different restrictions on their
  structure:




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  Template        Specifies a portion of the tree, naming one or more
                  values, but not containing any values.

  Path            Specifies a single path from one point in the tree to
                  another, naming exactly one value, but not containing
                  a value.

  InputValue      Gives a value to be used by a query language
                  operator.



  A query response consists of a sequence of ASN.1 objects, as follows:

      Response := IMPLICIT SEQUENCE of ResponseElement;

      ResponseElement ::= CHOICE {
              ResultValue,
              Error
              }

  Error is defined below.  The others are:

      ResultValue     ::= any

  ResultValue is similar to Template, above:

  ResultValue     Specifies a portion of the tree, naming and
                  containing one or more values.

  The distinctions between these are elaborated in section 6.

I.1 Operation Codes

  Operation codes are all encoded in a single application-specific
  type, whose value determines the operation to be performed.  The
  definition is:

      Operation ::= [APPLICATION 1] IMPLICIT INTEGER {
              reserved(0),
              begin(1),
              end(2),
              get(3),
              get-attributes(4),
              get-range(5),
              set(6),





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              create(7),
              delete(8)
              }

I.2 Error Returns

  An Error object is returned within a reply when an error is
  encountered during the processing of a query.  Note that the
  definition this object is similar to that of the HEMP protocol error
  structure.  The error codes have been selected to keep the code
  spaces distinct between the two.  This is intended to ease the
  processing of error messages.  See section 11 for more information.

      Error ::= [APPLICATION 0] IMPLICIT SEQUENCE {
              errorCode       INTEGER,
              errorInstance   INTEGER,
              errorOffset     INTEGER
              errorDescription IA5String,
              errorOp         INTEGER,
              }

  The fields are defined as follows:

  errorCode       Identifies the general cause of the error.

  errorInstance   An implementation-dependent code that gives a more
                  precise indication of where the error occured in the
                  query processor.  This is most useful when internal
                  errors are reported.

  errorOffset     The location within the query where the error was
                  detected.  The first octet of the query is numbered
                  zero.

  errorOp         If an operation was being executed, this contains its
                  operation code, otherwise zero.

  errorDescription
                  A text string that can be printed that gives some
                  description of the error.  It will at least describe
                  the errorCode, but may also give details implied by
                  errorInstance.

  Some errors are associated with the execution of specific operations,
  and others with the overall operation of the query interpreter.  The
  errorCodes are split into two groups.

  The first group deals with overall interpreter operation.  Except for



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  "unknown operation", these do not set errorOp.

  100             Other error.
                  Any error not listed below.

  101             Format error.
                  An error has been detected in the format of the input
                  stream, preventing further interpretation of the
                  query.

  102             System error.
                  The query processor has failed in some way due to an
                  internal error.

  103             Stack overflow.
                  Too many items were pushed on the stack.

  104             Unknown operation.
                  The operation code is invalid.  errorOp is set.

  The second group is errors that are associated with the execution of
  particular operations.  errorOp will always be set for these.

  200             Other operation error.
                  Any error, associated with an operation, not listed
                  below.

  201             Stack underflow.
                  An operation expected to see some number of operands
                  on the stack, and there were fewer items on the
                  stack.

  202             Operand error.
                  An operation expected to see certain operand types on
                  the stack, and something else was there.

  203             Invalid path for BEGIN.
                  A path given for BEGIN was invalid, because some
                  element in the path didn't exist.

  204             Non-dictionary for BEGIN.
                  A path given for BEGIN was invalid, because the given
                  node was a leaf node, not a dictionary.

  205             BEGIN on array element.
                  The path specified an array element.  The path must
                  point at a single, unique, node.  A filtered BEGIN
                  should have been used.



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  206             Empty filter for BEGIN.
                  The filter for a BEGIN didn't match any array
                  element.

  207             Filtered operation on non-array.
                  A filtered operation was attempted on a regular
                  dictionary.  Filters can only be used on arrays.

  208             Index out of bounds.
                  The starting address or length for a GET-RANGE
                  operation went outside the bounds for the given
                  object.

  209             Bad object for GET-RANGE.
                  GET-RANGE can only be applied to objects whose base
                  type is OctetString.

  This list is probably not quite complete, and would need to be
  extended, based upon implementation experience.

I.3 Filters

  Many of the operations can take a filter argument to select among
  elements in an array.  They are discussed in section 8.6.


       Filter          ::= [APPLICATION 2] CHOICE {
                              present         [0] DataPath,
                              equal           [1] DataValue,
                              greaterOrEqual  [2] DataValue,
                              lessOrEqual     [3] DataValue,
                              and             [4] SEQUENCE OF Filter,
                              or              [5] SEQUENCE OF Filter,
                              not             [6] Filter
                              }

      DataPath        ::= ANY                 -- Path with no value

      DataValue       ::= ANY                 -- Single data value

  A filter is executed by inorder traversal of its ASN.1 structure.

  The basic filter operations are:

  present         tests for the existence of a particular data item in
                  the data tree





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  equal           tests to see if the named data item is equal to the
                  given value.

  greaterOrEqual  tests to see if the named data item is greater than
                  or equal to the given value.

  lessOrEqual     tests to see if the named data item is less than or
                  equal to the given value.

  These may be combined with "and", "or", and "not" operators to form
  arbitrary boolean expressions.  The "and" and "or" operators will
  take any number of terms.  Terms are only evaluated up to the point
  where the outcome of the expression is determined (i.e., an "and"
  term's value is false or an "or" term's value is true).

I.4 Attributes

  One or more Attributes structure is returned by the GET-ATTRIBUTES
  operator.  This structure provides descriptive information about
  items in the data tree.  See the discussion in section 8.3.

      Attributes ::= [APPLICATION 3] IMPLICIT SEQUENCE {
              tagASN1         [0] IMPLICIT INTEGER,
              valueFormat     [1] IMPLICIT INTEGER,
              longDesc        [2] IMPLICIT IA5String OPTIONAL,
              shortDesc       [3] IMPLICIT IA5String OPTIONAL,
              unitsDesc       [4] IMPLICIT IA5String OPTIONAL,
              precision       [5] IMPLICIT INTEGER OPTIONAL,
              properties      [6] IMPLICIT BITSTRING OPTIONAL,
              valueSet        [7] IMPLICIT SET OF valueDesc OPTIONAL
              }
      valueDesc ::= IMPLICIT SEQUENCE {
              value           [0] ANY,        -- Single data value
              desc            [1] IA5String
              }

  The meanings of the various attributes are given below.

  tagASN1         The ASN.1 tag for this object.  This attribute is
                  required.

  valueFormat     The underlying ASN.1 type of the object (e.g.,
                  SEQUENCE or OCTETSTRING or Counter).  This is not
                  just the tag number, but the entire tag, as it would
                  appear in an ASN.1 object.  As such, it includes the
                  class, which should be either UNIVERSAL or
                  APPLICATION.  Applications receiving this should




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                  ignore the constructor bit.  This attribute is
                  required.

  longDesc        A potentially lengthy text description which fully
                  defines the object.  This attribute is optional for
                  objects defined in this memo and required for
                  entity-specific objects.

  shortDesc       A short mnemonic string of less than 15 characters,
                  suitable for labeling the value on a display.  This
                  attribute is optional.

  unitsDesc       A short string used for integer values to indicate
                  the units in which the value is measured (e.g., "ms",
                  "sec", "pkts", etc.).  This attribute is optional.

  precision       For Counter objects, the value at which the Counter
                  will roll-over.  Required for all Counter objects.

  properties      A bitstring of boolean properties of the object.  If
                  the bit is on, it has the given property.  This
                  attribute is optional.  The bits currently defined
                  are:

                  0   If true, the difference between two values of
                      this object is significant.  For example, the
                      changes of a packet count is always significant,
                      it always conveys information.  In this case, the
                      0 bit would be set.  On the other hand, the
                      difference between two readings of a queue length
                      may be meaningless.

                  1   If true, the value may be modified with SET,
                      CREATE, and DELETE.  Applicability of CREATE and
                      DELETE depends upon whether the object is in an
                      array.

                  2   If true, the object is a dictionary, and a BEGIN
                      may be used on it.  If false, the object is leaf
                      node in the data tree.

                  3   If true, the object is an array-type dictionary,
                      and filters may be used to traverse it.  (Bit 2
                      will be true also.)

  valueSet        For data that is defined as an ASN.1 CHOICE type (an
                  enumerated type), this gives descriptions for each of
                  the possible values that the data object may assume.



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                  Each valueDesc is a <value,description> pair.  This
                  information is especially important for control
                  items, which are very likely to appear in
                  VendorSpecific dictionaries, exactly the situation
                  where descriptive information is needed.

I.5 VendorSpecific

  See the discussion in section 9.

      VendorSpecific          ::= [APPLICATION 4] IMPLICIT SET
                                      of ANY

II. IMPLEMENTATION HINTS

  Although it is not normally in the spirit of RFCs to define an
  implementation, the authors feel that some suggestions will be useful
  to implementors of the query language.  This list is not meant to be
  complete, but merely to give some hints about how the authors imagine
  that the query processor might be implemented efficiently.

     - It should be understood that the stack is of very limited
       depth.  Because of the nature of the query language, it can
       get only about 4 entries (for arguments) plus the depth of
       the tree (up to one BEGIN per level in the tree).  This
       comes out to about a dozen entries in the stack, a modest
       requirement.

     - The stack is an abstraction -- it should be implemented
       with pointers, not by copying dictionaries, etc.

     - An object-oriented approach should make implementation
       fairly easy.  Changes to the "shape" if the data items
       (which will certainly occur, early on) will also be easier
       to make.

     - Only a few "messages" need to be understood by objects.  By
       having pointers to action routines for each basic operation
       (GET,SET,...) associated with each node in the tree, common
       routines (e.g., emit a long integer located at address X)
       can be shared, and special routines (e.g., set the interface
       state for interface X) can be implemented in a common
       framework.  Higher levels need know nothing about what data
       is being dealt with.

     - Most interesting objects are dictionaries, each of which
       can be implemented using pointers to the data and procedure
       "hooks" to perform specific operations such as GET, SET,



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       filtering, etc.

     - The hardest part is actually extracting the data from
       existing TCP/IP implementations that weren't designed with
       detailed monitoring in mind.  Query processors interfacing
       to a UNIX kernel will have to make many system calls in
       order to extract some of the more intricate structures,
       such as routing tables.  This should be less of a problem
       if a system is designed with easy monitoring as a goal.

A Skeletal Implementation

  This section gives a rather detailed example of the core of a query
  processor.  This code has not been tested, and is intended only to
  give implementors ideas about how to tackle some aspects of query
  processor implementation with finesse, rather than brute force.

  The suggested architecture is for each dictionary to have a
  "traverse" routine associated with it, which is called when any sort
  of operation has to be done on that dictionary.  Most nodes will
  share the same traversal routine, but array dictionaries will usually
  have routines that know about whatever special lookup mechanisms are
  required.

  Non-dictionary nodes would have two routines, "action", and
  "compare", which implement query language operations and filter
  comparisons, respectively.  Most nodes would share these routines.

  For example, there should be one "action" routine that does query
  language operations on 32-bit integers, and another that works on
  16-bit integers, etc.

  Any traversal procedure would take arguments like:

      traverse(node, mask, op, filter)
              Treenode        node;   /* generic node-in-tree */
              ASN             mask;   /* internal ASN.1 form */
              enum opset      op;     /* what to do */
              Filter          filter; /* zero if no filter */

      enum opset { begin, get, set, create, delete, geta,
                      c_le, c_ge, c_eq, c_exist };

  The traversal procedure is called whenever anything must be done
  within a dictionary.  The arguments are:

  node            the current dictionary.




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  mask            is either the template, path, or value, depending
                  upon the operation being performed.  The top-level
                  identifier of this object will be looked up in the
                  context of <node>.

  op              is the operation to be performed, either one of the
                  basic operations, or a filter operation.

  filter          is the filter to be applied, or zero if none.  There
                  will be no filter when <op> is a filter-comparison
                  operation.

  The general idea is that the traversal proc associated with a node
  has all of the knowledge about how to get around in this subtree
  encoded within it.  Hopefully, this will be the only place this
  knowledge is coded.  Here is a skeleton of the "standard" traversal
  proc, written mostly in C.

  When the query processor needs to execute a "GET" operation, it would
  just call:
      traverse(current, template, GET, 0)

  Notes about this example:

     - This traversal routine handles either query language
       operations (GET, SET, etc.) or low-level filter operations.
       Separate routines could be defined for the two classes of
       operations, but they do much of the same work.

     - Dictionary nodes have a <traversal> proc defined.

     - Leaf nodes have an <action> proc, which implement GET, SET,
       GET-ATTRIBUTES, CREATE, and DELETE, and a <compare> proc,
       which performs low-level filter comparisons.

     - In the generic routine, the filter argument is unused,
       because the generic routine isn't used for array
       dictionaries, and only array dictionaries use filters.

     - An ASN type contains the top level tag and a list of
       sub-components.

     - size(mask) takes an ASN.1 object and tells how many
       sub-items are in it.  Zero means that this is a simple
       object.

     - lookup(node, tag) looks up a tag in the given (tree)node,
       returning a pointer to the node.  If the tag doesn't exist



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       in that node, a pointer to a special node "NullItem" is
       returned.  NullItem looks like a leaf node and has procs
       that perform the correct action for non-existent data.

     - This example does not do proper error handling, or ASN.1
       generation, both of which would require additional code in
       this routine.

      /*
       *  For op = GET/SET/etc, return:
       *              true on error, otherwise false.
       *  When op is a filter operation, return:
       *              the result of the comparison.
       */
      int std_traverse(node, mask, op, filter)
          Treenode    node;   /* current node */
          ASN         mask;   /* internal ASN.1 form */
          enum opset  op;     /* what to do */
          Filter      filter; /* unused in this routine */
      {
          ASN         item;
          Treenode    target;
          boolean     rv = false;
          extern Treenode NullItem;

          if (filter != null) {
              error(...);
              return true;
          }

          target = lookup(node, mask.tag);

          /*  We are at the leaf of the template/path/value.  */
          if (size(mask) == 0)
              switch (op)
              {
              case BEGIN:
                  /*  non-existent node, or leaf node  */
                  if (target == NullItem || target.traverse == 0) {
                      error(...);
                      return true;
                      }
                  else {
                      begin(node, mask.tag);
                      return false;
                      }

              case GET:       case SET:       case GETA:



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              case GETR:      case CREATE:    case DELETE:
                  /*  A leaf in the mask specifies entire directory.
                      For GET, traverse the entire subtree.  */
                  if (target.traverse)
                      if (op == GET) {
                          foreach subnode in target
                              /*  Need to test to not GET memory.  */
                              rv |= (*target.traverse)
                                      (target, subnode.tag, op, 0);
                          return rv;
                      }
                      else if (op == SET)     /*  no-op  */
                          return false;
                      else if (op != GETA) {
                          error(...);
                          return true;
                      }
                  /*  We're at a leaf in both the mask and the tree.
                      Just execute the operation.
                  */
                  else {
                      if (op == BEGIN) {  /*  Can't begin on leaf  */
                          error(...);
                          return true;
                      else
                          return (*target.action)(target, mask, op);
                      }
                  }  /* else */

              default:        /*  Comparison ops.  */
                  return (*target.compare)(target, mask, op);
              }  /* switch */

          /*  We only get here if mask has structure.  */

          /*  can't have multiple targets for BEGIN  */
          if (op == BEGIN && size(mask) != 1) {
              error(...);
              return true;
          }
          /*  or for a single filter operation.  */
          if (op is comparison && size(mask) != 1) {
              error(...);
              return false;
          }
          /*  Iterate over the components in mask  */
          foreach item in mask
          {



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              if (target.traverse)    /*  traverse subtree.  */
                  rv |= (*component.traverse)(component, item, op, 0);
              else                    /*  leaf node, at last.  */
                  if (op is comparison)
                      return (*target.compare)(target, mask, op);
                  else
                      return (*target.action)(target, mask, op);
          } /* foreach */

          return rv;
      }  /* std_traverse */


  Here is a bare skeleton of an array-type dictionary's traversal proc.

      int array_traverse(node, mask, op, filter)
          Treenode    node;   /* current node */
          ASN         mask;   /* internal ASN.1 form */
          enum opset  op;     /* what to do */
          Filter      filter; /* unused in this routine */
      {
          Treenode    target;
          boolean     rv = false;
          extern Treenode NullItem;

          /*  Didn't find that key.  */
          if (mask.tag != this array's iteration tag)
              return false;

          if (op == BEGIN && filter == null) {
              error(...);
              return 1;
          }

          /*  The implementation of this loop is the major trick!  */
          /*  Needs to stop after first filter success on BEGIN.  */
          foreach target in node {
              if (filter == null ||           /*  if no filter, or */
                  ExecFilter(target, filter)) /* if it succeeds  */
                  rv |= (target.traverse*)(target, mask, op, 0);
          }
      }  /* array_traverse */

  Object-oriented programming languages, such as C++, Modula, and Ada,
  are well suited to this style of implementation.  There should be no
  particular difficulty with using a conventional language such as C or
  Pascal, however.




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III. OBTAINING A COPY OF THE ASN.1 SPECIFICATION

  Copies of ISO Standard ASN.1 (Abstract Syntax Notation 1) are
  available from the following source.  It comes in two parts; both are
  needed:

      IS 8824 -- Specification (meaning, notation)
      IS 8825 -- Encoding Rules (representation)

  They are available from:

      Omnicom Inc.
      115 Park St, S.E.          (new address as of March, 1987)
      Vienna, VA  22180
      (703) 281-1135




































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