Network Working Group                                      X. Xiao (Ed.)
Internet-Draft                                  MRC, Huawei Technologies
Intended status: Standards Track                                  B. Liu
Expires: 14 January 2023                             Huawei Technologies
                                                               A. Hecker
                                                MRC, Huawei Technologies
                                                                S. Jiang
                                                     Huawei Technologies
                                                            13 July 2022

                  Information Distribution over GRASP


   Autonomic network infrastructure (ANI) is a generic platform for
   tenant applications (i.e.  AFs).  As we will see in some examplery
   use cases, AFs may not only require communication capability
   supported from the infrastructure side, but also the capability the
   infrastructure can hold and re-distribute information on-demand.
   This document proposes a set of solutions for information
   distribution in the ANI.  Information distribution is categorized
   into two different modes: 1) instantaneous distribution and 2)
   publishing for retrieval.  In the former case, the information is
   sent, propagated and disposed of after reception.  In the latter
   case, information needs to be stored in the network; additionally,
   conflict resolution is also needed when information stored in the
   network is updated with proposals from two different AFs.

   The capability of information distribution is a fundamental need for
   an autonomous network ([RFC7575]).  This document describes typical
   use cases of information distribution in ANI and requirements to ANI,
   such that abundant ways of information distribution can be natively
   supported.  This draft proposes a series of extensions to the
   autonomic nodes and suggests an implementation based on GRASP
   ([RFC8990]) extensions as a protocol on the wire.

Status of This Memo

   This Internet-Draft is submitted in full conformance with the
   provisions of BCP 78 and BCP 79.

   Internet-Drafts are working documents of the Internet Engineering
   Task Force (IETF).  Note that other groups may also distribute
   working documents as Internet-Drafts.  The list of current Internet-
   Drafts is at

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Table of Contents

   1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   3
   2.  Use Cases of Information Distribution . . . . . . . . . . . .   4
     2.1.  Service-Based Architecture (SBA) in 3GPP  . . . . . . . .   4
     2.2.  In-Network Computing (INC)  . . . . . . . . . . . . . . .   6
   3.  Vehicle-to-Everything (V2X) Communications  . . . . . . . . .   7
   4.  General Requirements of Information Distribution in ANI . . .   8
   5.  Node Behaviors  . . . . . . . . . . . . . . . . . . . . . . .  11
     5.1.  Instant Information Distribution (IID) Sub-module . . . .  11
       5.1.1.  Instant P2P Communication . . . . . . . . . . . . . .  11
       5.1.2.  Instant Flooding Communication  . . . . . . . . . . .  11
     5.2.  Asynchronous Information Distribution (AID) Sub-module  .  12
       5.2.1.  Information Storage . . . . . . . . . . . . . . . . .  12
       5.2.2.  Event Queue . . . . . . . . . . . . . . . . . . . . .  14
     5.3.  Bulk Information Transfer . . . . . . . . . . . . . . . .  16
     5.4.  Summary . . . . . . . . . . . . . . . . . . . . . . . . .  18
   6.  Extending GRASP for Information Distribution  . . . . . . . .  18
     6.1.  Realizing Instant P2P Transmission  . . . . . . . . . . .  18
     6.2.  Realizing Instant Selective Flooding  . . . . . . . . . .  19
     6.3.  Realizing Bulk Information Transfer . . . . . . . . . . .  19
     6.4.  Realizing Subscription as An Event  . . . . . . . . . . .  19
     6.5.  Un_Subscription Objective Option  . . . . . . . . . . . .  20
     6.6.  Publishing Objective Option . . . . . . . . . . . . . . .  20
   7.  Security Considerations . . . . . . . . . . . . . . . . . . .  20
   8.  IANA Considerations . . . . . . . . . . . . . . . . . . . . .  21
   9.  Acknowledgements  . . . . . . . . . . . . . . . . . . . . . .  21

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   10. Contributors  . . . . . . . . . . . . . . . . . . . . . . . .  21
   11. References  . . . . . . . . . . . . . . . . . . . . . . . . .  21
     11.1.  Normative References . . . . . . . . . . . . . . . . . .  21
     11.2.  Informative References . . . . . . . . . . . . . . . . .  22
   Appendix A.  Open Issues [RFC Editor: To Be removed before becoming
           RFC]  . . . . . . . . . . . . . . . . . . . . . . . . . .  23
   Appendix B.  Closed Issues [RFC Editor: To Be removed before
           becoming RFC] . . . . . . . . . . . . . . . . . . . . . .  23
   Appendix C.  Change log [RFC Editor: To Be removed before becoming
           RFC]  . . . . . . . . . . . . . . . . . . . . . . . . . .  24
   Appendix D.  Information Distribution Module in ANI . . . . . . .  24
   Appendix E.  Asynchronous ID Integrated with GRASP APIs . . . . .  24
   Authors' Addresses  . . . . . . . . . . . . . . . . . . . . . . .  25

1.  Introduction

   In an autonomic network, autonomic functions (AFs) running on
   autonomic nodes constantly exchange information, e.g.  AF control/
   management signaling or AF data exchange.  This document discusses
   the information distribution capability of such exchanges among AFs.
   Many use cases can be abstracted to this model.  In the following
   sections, we will see that the information distribution capability
   shall become a common denominator in future application scenarios.

   In general, depending on the number of participants, the information
   can be distributed in in the following scenarios:

   1)  Point-to-point (P2P) Communication: information is exchanged
      between two AFs.

   2)  One-to-Many Communication: information exchanges involve one
      source AF and multiple receiving AFs.

   Approaches of infrmation distribution can be mainly categorized into
   two basic modes:

   1)  An instantaneous mode (push): a source sends the actual content
      (e.g. control/management signaling, synchronization data and so
      on) to all interested receiver(s) immediately.  Generally, some
      preconfigurations are required, where nodes interested in this
      information must be already known to all nodes because any source
      AF must be able to decide, to which AFs the data is to be sent.

   2)  An asynchronous mode (delayed pull): here, a source AF publishes
      the content in some forms in the network, which may later be
      looked for, found and retrieved by some endpoints in the AN.
      Here, depending on the size of the content, either the whole
      content or only its metadata might be published into the AN.  In

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      the latter case the metadata (e.g. a content descriptor, e.g. a
      key, and a location in the ANI) may be used for the actual
      retrieval.  Importantly, the source, i.e., here as a publisher,
      needs to be able to determine the location, where the information
      (or its metadata) can be stored.

   Note that in both cases, the total size of transferred information
   can be larger than the payload size of a single message of a used
   transport protocol (e.g., Synchronization and Flood messages in
   GRASP).  In this situation, this document also considers a case of
   bulk data transfer.  To avoid repetitive implementations by each AF
   developer, this document opts for a common support for information
   distribution implemented as a basic ANI capability.  Therefore, it
   will be available to all AFs.  In fact, GRASP already provides part
   of the capabilities.

   Regardless, an AF may still define and implement its own information
   distribution capability.  Such a capability may then be advertised
   using the common information distribution capability defined in this
   document.  Overall, ANI nodes and AFs may decide, which of the
   information distribution mechanisms they want to use for which type
   of information, according to their own preferences.

   This document first analyzes requirements for information
   distribution in autonomic networks (Section 4) and then discuss the
   relevant node behaviors (Section 5).  After that, the required GRASP
   extensions are formally introduced (Section 6).

   The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
   document are to be interpreted as described in RFC 2119 [RFC2119].

2.  Use Cases of Information Distribution

   In this section, we present some important use cases where
   information distribution is required and ACP's support is commanly

2.1.  Service-Based Architecture (SBA) in 3GPP

   In addition to Internet, carrier networks (i.e. wireless mobile
   networks) is another world-wide networking system.  The current
   architecture of 5G mobile networks from 3GPP has been defined to
   follow a service-based architecture (SBA) where any network function
   (NF) can dynamically interact with any other NF(s) when needed to
   compose a network service.  Note that one NF can simultaneously
   associate with multiple other NFs, instead of being physically wired
   as in the previous generations of mobile networks.  NFs communicate

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   with each other over service-based interface (SBI), which is also
   standardized by 3GPP [3GPP.23.501].

   To realize an SBA network system, detailed requirements are further
   defined to specify how NFs should interact with each other with
   information exchange over the SBI in corresponding 3GPP technical
   specifications.  We now list three services that are closely related
   to information distribution here.

   1)  NF Pub/Sub: Any NF should be able to expose its service status to
      the network and any NF should be able to subscribe the service
      status of an NF and get notified if the status is available.  A
      concrete example is that a session management function (SMF) can
      subscribe to the REGISTER notification from an access management
      function (AMF) if there is a new user equipment trying to access
      the mobile network [3GPP.23.502].

   2)  Network Exposure Function (NEF): A particular network function
      that is required to manage the event exposure and distributions.
      Specifically, SBA requires such a functionality to register
      network events from the other NFs (e.g.  AMF, SMF and so on),
      classify the events and properly handle event distributions
      accordingly in terms of different criteria (e.g. priorities)

   3)  Network Repository Function (NRF): A particular network function
      where all service status information is stored for the whole
      network.  An SBA network system requires all NFs to be stateless
      so as to improve the resilience as well as agility of providing
      network services.  Therefore, the information of the available NFs
      and the service status generated by those NFs will be globally
      stored in NRF as a repository of the system.  This clearly implies
      storage capability that keeps the information in the network and
      provides those information when needed.  A concrete example is
      that whenever a new NF comes up, it first of all registers itself
      at NRF with its profile.  When a network service requires a
      certain NF, it first inquires NRF to retrieve the availability
      information and decides whether or not there is an available NF or
      a new NF must be instantiated [3GPP.23.502].

   (Note: 3GPP adopted HTTP2.0/JSON as one option to implement the
   transmission protocol between defined NFs.)

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   Notice that how the control plane such as connectivity and trust
   shall be bootstrapped and maintained among NFs are not specified.  In
   fact, 3GPP only considers the necessary requirements and features of
   a 3GPP network shall present.  Hence, ACP and GRASP could be utilized
   as a specific solution and even further promoted to 3GPP if a
   majority consensus is reached among 3GPP participants.

2.2.  In-Network Computing (INC)

   In-network computing recently gets a lot of attentions
   [The-case-for-in-network-computing-on-demand].  INC improves the
   utilization of the computing resources in the network; INC also
   brings the processed results closer to the users, which may
   potentially improves the QoS of network services.

   Unlike existing network systems, INC deploys computing tasks directly
   in the network rather than pushing the tasks to endpoints outside the
   network.  Therefore, a network device is not just a transport device,
   but a mixture of forwarding, routing and computing.  The requires an
   INC-supported network device having storage by default.  Furthermore,
   computing agents deployed on network nodes will have to communicate
   with each other by exchanging information.  There are several typical
   applications, where information distribution capability is required,
   which are summarized below.

   1)  Data Backup: There can be multiple computing agents that are
      created to serve the same purpose(s).  In reality, the multiple
      agents can run for service resilience, load balancing and so on.
      This forms a service set.  The instances in the service set can be
      deployed at different locations in the network while they need to
      keep synchronizing their local states for global consistency.  In
      this case, the computing agents will have to constantly send and
      receive information across the network.

   2)  Data Aggregation: Multiple computing agents may process different
      computing tasks but the derived results have to be aggregated or
      combined.  Then a collective result can be derived.  In this case,
      different computing agents collaborate with each other, where
      information data are exchanged during the processing.  A popular
      example is distributed AI or federated learning applications,
      where data are stored at different places and model training with
      the local data is also done in a distributed way.  After that,
      trained models by distributed agents will have to be aggregated.
      Information distribution will be utlized heavily, combining with
      local storage.

   Clearly, AFs running on network nodes in ANI are the abstraction of
   the INC use case.  AFs can be deployed for both scenarios above.

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3.  Vehicle-to-Everything (V2X) Communications

   The connected Autonomous Driving (AD) vehicles market is driving the
   evolution of the Internet of Vehicles (IoV) (or Vehicular IoT) and is
   growing at a five-year compound annual growth rate of 45%, which is
   10 times as fast as the overall car market.  V2X communication is an
   inevitable enabling technology that connects vehicles to networks,
   where value-added services can be provided and enhance the
   functionalities of a vehicle.  In this section, we introduce some use
   cases that will be closely relevant to information distribution in an

   1)  Real-time and High Definition Maps (HDM): In the era of
      autonomous driving, a digital map not only means for navigation,
      but real-time and detailed information is required when driving a
      vehicle.  Real-time situational awareness is essential for
      autonomous vehicles especially at critical road segments in cases
      of changing road conditions (e.g. new traffic cone detected by
      another vehicle some time ago).  In addition, the relevant high
      definition local maps have to be available with support from
      infrastructure side.  In this regards, a digital map should not be
      considered static information stored on the vehicle, which is
      spontaneously updated in a periodical manner.  Instead, it shall
      be considered a dynamic distribution based on information
      aggregated from the local area and such a distribution shall
      consider latency requirement.  Clearly, the infrastructure side
      shall be able to hold the information in the network sufficiently
      close to the relevant area.

   2)  In-car Infotaiment: This is another popular use case where in-car
      data demands will increase significantly in the near future.
      Today, users their mobile phone to access Internet for retrieving
      data for work or entertainment purposes.  There is already a
      concensus among OTTs, carriers and car manufacturers that vehicle
      will become the center of information for passengers onboard.  For
      entertainment, typical scenarios can be stereo HD video streaming
      and online gaming; for business purposes, examples can be mobile
      conference.  This therefore requires the infrastructure side to be
      able to schedule and deliver requested information/data to the
      users with quality-of-service (QoS) considerations.

   3)  Software Update: Software components of connected cars will be
      remotely maintained in future.  Therefore, software update has to
      be supported by the infrastructure side.  Although this can be
      done by centralized solution where all vehicles access to a
      central clouds, in terms of load balancing and efficiency,
      prepared update components can be stored in the network and
      delivered to endpoints in a distributed manner.

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   Note that there could be different modes to support the potential use
   cases above.  The first mode is that vehicles are not part of the ACP
   while simply accessing the edge nodes that are part of the ACP using
   information distribution to provide infomration required by the
   vechicles.  The second mode is more radical where the vehciles also
   belong to the part of ACP while a dynamic ACP topology consisting of
   wireless link connectivity could exist.  The latter scenario may
   further require all entities (both at the network side and the end
   point side) must be able to establlish a trust layer relying on the
   security mechanism with BRSKI.

4.  General Requirements of Information Distribution in ANI

   According to the introduced use cases, the question of information
   distribution in an autonomic network can be discussed through
   particular use cases or more generally.  Depending on the situation
   it can be quite simple or might require more complex provisions.

   Indeed, in the most general case, the information can be sent:

   1)  at once (in one or multiple packets, in one flow),

   2)  straightaway (send-and-forget),

   3)  to all nodes.

   For the first scenario, presuming 1), 2) and 3) hold, information
   distribution in smaller or scarce topologies can be implemented using
   broadcast, i.e. unconstrained flooding.  For reasons well-understood,
   this approach has its limits in larger and denser networks.  In this
   case, a graph can be constructed such that it contains every node
   exactly once (e.g. a spanning tree), still allowing to distribute any
   information to all nodes straightaway.  Multicast tree construction
   protocols could be used in this case.  There are reasonable use cases
   for such scenarios, as presented in Section 2.

   Secondly, a more complex scenario arises, if only 1) and 2) hold, but
   the information only concerns a subset of nodes.  Then, some kinds of
   selection become required, to which nodes the given information
   should be distributed.  Here, a further distinction is necessary;
   notably, if the selection of the target nodes is with respect to the
   nature or position of the node, or whether it is with respect to the
   information content.  If the first, some knowledge about the node
   types, its topological position, etc (e.g. the routing information
   within ANI) can be used to distinguish nodes accordingly.  For
   instance, edge nodes and forwarding nodes can be distinguished in
   this way.  If the distribution scope is primarily to be defined by
   the information elements, then a registration / join / subscription

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   or label distribution mechanism is unavoidable.  This would be the
   case, for instance, if the AFs can be dynamically deployed on nodes,
   and the information is majorily destined to the AFs.  Then, depending
   on the current AF deployment, the distribution scope must be adjusted
   as well.

   Thirdly, if only 1) holds, but the information content might be
   required again and again, or might not yet be fully available, then
   more complex mechanisms might be required to store the information
   within the network for later, for further redistribution, and for
   notification of interested nodes.  Examples for this include
   distribution of reconfiguration information for different AF
   instances, which might not require an immediate action, but only an
   eventual update of the parameters.  Also, in some situations, there
   could be a significant delay between the occurrence of a new event
   and the full content availability (e.g. if the processing requires a
   lot of time).

   Finally, none of the three might hold.  Then, along with the
   subscription and notification, the actual content might be different
   from its metadata, i.e. some descriptions of the content and,
   possibly, its location.  The fetching can then be implemented in
   different, appropriate ways, if necessary as a complex transport

   In essence, as flooding is usually not an option, and the interest of
   nodes for particular information elements can change over time, ANI
   should support autonomics also for the information distribution.

   This calls for autonomic mechanisms in the ANI, allowing
   participating nodes to 1) advertise/publish, 2) look for/subscribe to
   3) store, 4) fetch/retrieve and 5) instantaneously push data

   In the following cases, situations depicting complicated ways of
   information distribution are discussed.

   1)  Long Communication Intervals.  The actual sending of the
      information is not necessarily instantaneous with some events.
      Sophisticated AFs may involve into longer jobs/tasks (e.g.
      database lookup, validations, etc.) when processing requests, and
      might not be able to reply immediately.  Instead of actively
      waiting for the reply, a better way for an interested AF might be
      to get notified, when the reply is finally available.

   2)  Common Interest Distribution.  AFs may share information that is

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      a common interest.  For example, the network intent will be
      distributed to network nodes enrolled, which is usually one-to-
      many scenario.  Intent distribution can also be performed by an
      instant flooding (e.g. via GRASP) to every network node.  However,
      because of network changes, not every node can be just ready at
      the moment when the network intent is broadcast.  Also, a flooding
      often does not cover all network nodes as there is usually a
      limitation on the hop number.  In fact, nodes may join in the
      network sequentially.  In this situation, an asynchronous
      communication model could be a better choice where every (newly
      joining) node can subscribe the intent information and will get
      notified if it is ready (or updated).

   3)  Distributed Coordination.  With computing and storage resources
      on autonomic nodes, alive AFs not only consume but also generate
      data information.  An example is AFs coordinating with each other
      as distributed schedulers, responding to service requests and
      distributing tasks.  It is critical for those AFs to make correct
      decisions based on local information, which might be asymmetric as
      well.  AFs may also need synthetic/aggregated data information
      (e.g.  statistic info, like average values of several AFs, etc.)
      to make decisions.  In these situations, AFs will need an
      efficient way to form a global view of the network (e.g. about
      resource consumption, bandwidth and statistics).  Obviously,
      purely relying on instant communication model is inefficient,
      while a scalable, common, yet distributed data layer, on which AFs
      can store and share information in an asynchronous way, should be
      a better choice.

   4)  Collision Update.  Information data not only can be propagated
      and stored on network nodes in the network, they have to be
      conflict-free when information is updated especially when there is
      no central authority available.  For example, when two AFs try to
      propose different updates for the same piece of information that
      already exist in the network, a decision has to be made for how
      the existing information shall be updated.  Obviously, if this
      duty has to be handled by individual AFs, the implematation of an
      AF is too complicated.  Therefore, information distribution should
      consider conflict resultion and provides a set of general
      solutions for AFs in order to keep information conflict free.

   Therefore, for ANI, in order to support various communication
   scenarios, an information distribution module is required, and both
   instantaneous and asynchronous communication models should be
   supported.  Some real-world use cases are introduced in Section 2.

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5.  Node Behaviors

   In this section, how a node should behave in order to support the two
   identified modes of information distribution is discussed.  An ANI is
   a distributed system, so the information distribution module must be
   implemented in a distributed way as well.

5.1.  Instant Information Distribution (IID) Sub-module

   In this case, an information sender directly specifies the
   information receiver(s).  The instant information distribution sub-
   module will be the main element.

5.1.1.  Instant P2P Communication

   IID sub-module performs instant information transmission for ASAs
   running in an ANI.  In specific, IID sub-module will have to retrieve
   the address of the information receiver specified by an ASA, then
   deliver the information to the receiver.  Such a delivery can be done
   either in a connectionless or a connection-oriented way.

   Current GRASP provides the capability to support instant P2P
   synchronization for ASAs.  A P2P synchronization is a use case of P2P
   information transmission.  However, as mentioned in Section 3, there
   are some scenarios where one node needs to transmit some information
   to another node(s).  This is different to synchronization because
   after transmitting the information, the local status of the
   information does not have to be the same as the information sent to
   the receiver.  This is not directly support by existing GRASP.

5.1.2.  Instant Flooding Communication

   IID sub-module finishes instant flooding for ASAs in an ANI.  Instant
   flooding is for all ASAs in an ANI.  An information sender has to
   specify a special destination address of the information and
   broadcast to all interfaces to its neighbors.  When another IID sub-
   module receives such a broadcast, after checking its TTL, it further
   broadcast the message to the neighbors.  In order to avoid flooding
   storms in an ANI, usually a TTL number is specified, so that after a
   pre-defined limit, the flooding message will not be further broadcast

   In order to avoid unnecessary flooding, a selective flooding can be
   done where an information sender wants to send information to
   multiple receivers at once.  When doing this, sending information
   needs to contain criteria to judge on which interfaces the
   distributed information should and should not be sent.  Specifically,
   the criteria contain:

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   *  Matching Condition: a set of matching rules such as addresses of
      recipients, node features and so on.

   *  Action: what the node needs to do when the Matching Condition is
      fulfilled.  For example, the action could be forwarding or
      discarding the distributed message.

   Sent information must be included in the message distributed from the
   sender.  The receiving node reacts by first checking the carried
   Matching Condition in the message to decide who should consume the
   message, which could be either the node itself, some neighbors or
   both.  If the node itself is a recipient, Action field is followed;
   if a neighbor is a recipient, the message is sent accordingly.

   An exemplary extension to support selective flooding on GRASP is
   described in Section 5.

5.2.  Asynchronous Information Distribution (AID) Sub-module

   In asynchronous information distribution, sender(s) and receiver(s)
   are not immediately specified while they may appear in an
   asynchronous way.  Firstly, AID sub-module enables that the
   information can be stored in the network; secondly, AID sub-module
   provides an information publication and subscription (Pub/Sub)
   mechanism for ASAs.

   As sketched in the previous section, in general each node requires
   two modules: 1) Information Storage (IS) module and 2) Event Queue
   (EQ) module in the information distribution module.  Details of the
   two modules are described in the following sections.

5.2.1.  Information Storage

   IS module handles how to save and retrieve information for ASAs
   across the network.  The IS module uses a syntax to index
   information, generating the hash index value (e.g. a hash value) of
   the information and mapping the hash index to a certain node in ANI.
   Note that, this mechanism can use existing solutions.  Specifically,
   storing information in an ANIMA network will be realized in the
   following steps.

   1)  ASA-to-IS Negotiation.  An ASA calls the API provided by
      information distribution module (directly supported by IS sub-
      module) to request to store the information somewhere in the
      network.  The IS module performs various checks of the request
      (e.g. permitted information size).

   2)  Storing Peer Mapping.  The information block will be handled by

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      the IS module in order to calculate/map to a peer node in the
      network.  Since ANIMA network is a peer-to-peer network, a typical
      way is to use distributed hash table (DHT) to map information to a
      unique index identifier.  For example, if the size of the
      information is reasonable, the information block itself can be
      hashed, otherwise, some meta-data of the information block can be
      used to generate the mapping.

   3)  Storing Peer Negotiation Request.  Negotiation request of storing
      the information will be sent from the IS module to the IS module
      on the destination node.  The negotiation request contains
      parameters about the information block from the source IS module.
      According to the parameters as well as the local available
      resource, the requested storing peer will send feedback the source
      IS module.

   4)  Storing Peer Negotiation Response.  Negotiation response from the
      storing peer is sent back to the source IS module.  If the source
      IS module gets confirmation that the information can be stored,
      source IS module will prepare to transfer the information block;
      otherwise, a new storing peer must be discovered (i.e. going to
      step 7).

   5)  Information Block Transfer.  Before sending the information block
      to the storing peer that already accepts the request, the IS
      module of the source node will check if the information block can
      be afforded by one GRASP message.  If so, the information block
      will be directly sent by calling a GRASP API
      ([I-D.ietf-anima-grasp-api]).  Otherwise, a bulk data transmission
      is needed.  For that, there are multiple ways to do it.  The first
      option is to utilize one of existing protocols that is independent
      of the GRASP stack.  For example, a session connectivity can be
      established to the storing peer, and over the connection the bulky
      data can be transmitted part by part.  In this case, the IS module
      should support basic TCP-based session protocols such as HTTP(s)
      or native TCP.  The second option is to directly use GRASP itself
      for bulky data transferring [I-D.carpenter-anima-grasp-bulk].

   6)  Information Writing.  Once the information block (or a smaller
      block) is received, the IS module of the storing peer will store
      the data block in the local storage is accessible.

   7)  (Optional) New Storing Peer Discovery.  If the previously
      selected storing peer is not available to store the information
      block, the source IS module will have to identify a new
      destination node to start a new negotiation.  In this case, the
      discovery can be done by using discovery GRASP API to identify a
      new candidate, or more complex mechanisms can be introduced.

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   Similarly, Getting information from an ANI will be realized in the
   following steps.

   1)  ASA-to-IS Request.  An ASA accesses the IS module via the APIs
      exposed by the information distribution module.  The key/index of
      the interested information will be sent to the IS module.  An
      assumption here is that the key/index should be known to an ASA
      before an ASA can ask for the information.  This relates to the
      publishing/subscribing of the information, which are handled by
      other modules (e.g.  Event Queue with Pub/Sub supported by GRASP).

   2)  Storing Peer Mapping.  IS module maps the key/index of the
      requested information to a peer that stores the information, and
      prepares the information request.  The mapping here follows the
      same mechanism when the information is stored.

   3)  Retrieval Negotiation Request.  The source IS module sends a
      request to the storing peer and asks if such an information object
      is available.

   4)  Retrieval Negotiation Response.  The storing peer checks the key/
      index of the information in the request, and replies to the source
      IS module.  If the information is found and the information block
      can be afforded within one GRASP message, the information will be
      sent together with the response to the source IS module.

   5)  (Optional) New Destination Request.  If the information is not
      found after the source IS module gets the response from the
      originally identified storing peer, the source IS module will have
      to discover the location of the requested information.

   IS module can reuse distributed databases and key value stores like
   NoSQL, Cassandra, DHT technologies. storage and retrieval of
   information are all event-driven responsible by the EQ module.

5.2.2.  Event Queue

   The Event Queue (EQ) module is to help ASAs to publish information to
   the network and subscribe to interested information in asynchronous
   scenarios.  In an ANI, information generated on network nodes is an
   event labeled with an event ID, which is semantically related to the
   topic of the information.  Key features of EQ module are summarized
   as follows.

   1)  Event Group: An EQ module provides isolated queues for different

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      event groups.  If two groups of AFs could have completely
      different purposes, the EQ module allows to create multiple queues
      where only AFs interested in the same topic will be aware of the
      corresponding event queue.

   2)  Event Prioritization: Events can have different priorities in
      ANI.  This corresponds to how much important or urgent the event
      implies.  Some of them are more urgent than regular ones.
      Prioritization allows AFs to differentiate events (i.e.
      information) they publish or subscribe to.

   3)  Event Matching: an information consumer has to be identified from
      the queue in order to deliver the information from the provider.
      Event matching keeps looking for the subscriptions in the queue to
      see if there is an exact published event there.  Whenever a match
      is found, it will notify the upper layer to inform the
      corresponding ASAs who are the information provider and
      subscriber(s) respectively.

   The EQ module on every network node operates as follows.

   1)  Event ID Generation: If information of an ASA is ready, an event
      ID is generated according to the content of the information.  This
      is also related to how the information is stored/saved by the IS
      module introduced before.  Meanwhile, the type of the event is
      also specified where it can be of control purpose or user plane

   2)  Priority Specification: According to the type of the event, the
      ASA may specify its priority to say how this event is to be
      processed.  By considering both aspects, the priority of the event
      will be determined.

   3)  Event Enqueue: Given the event ID, event group and its priority,
      a queue is identified locally if all criteria can be satisfied.
      If there is such a queue, the event will be simply added into the
      queue, otherwise a new queue will be created to accommodate such
      an event.

   4)  Event Propagation: The published event will be propagated to the
      other network nodes in the ANIMA domain.  A propagation algorithm
      can be employed to optimize the propagation efficiency of the
      updated event queue states.

   5)  Event Match and Notification: While propagating updated event
      states, EQ module in parallel keeps matching published events and
      its interested consumers.  Once a match is found, the provider and
      subscriber(s) will be notified for final information retrieval.

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   The category of event priority is defined as the following.  In
   general, there are two event types:

   1)  Network Control Event: This type of events are defined by the ANI
      for operational purposes on network control.  A pre-defined
      priority levels for required system messages is suggested.  For
      highest level to lowest level, the priority value ranges from
      NC_PRIOR_HIGH to NC_PRIOR_LOW as integer values.  The NC_PRIOR_*
      values will be defined later according to the total number system
      events required by the ANI.

   2)  Custom ASA Event: This type of events are defined by the ASAs of
      users.  This specifies the priority of the message within a group
      of ASAs, therefore it is only effective among ASAs that join the
      same message group.  Within the message group, a group header/
      leader has to define a list of priority levels ranging from
      CUST_PRIOR_HIGH to CUST_PRIOR_LOW.  Such a definition completely
      depends on the individual purposes of the message group.  When a
      system message is delivered, its event type and event priority
      value have to be both specified.

   Event contains the address where the information is stored, after a
   subscriber is notified, it directly retrieves the information from
   the given location.

5.3.  Bulk Information Transfer

   In both cases discussed previously, they are limited to distributing
   GRASP Objective Options contained in messages that cannot exceed the
   GRASP maximum message size of 2048 bytes.  This places a limit on the
   size of data that can be transferred directly in a GRASP message such
   as a Synchronization or Flood operation for instantaneous information

   There are scenarios in autonomic networks where this restriction is a
   problem.  One example is the distribution of network policy in
   lengthy formats such as YANG or JSON.  Another case might be an
   Autonomic Service Agent (ASA) uploading a log file to the Network
   Operations Center (NOC).  A third case might be a supervisory system
   downloading a software upgrade to an autonomic node.  A related case
   might be installing the code of a new or updated ASA to a target

   Naturally, an existing solution such as a secure file transfer
   protocol or secure HTTP might be used for this.  Other management
   protocols such as syslog [RFC5424] or NETCONF [RFC6241] might also be
   used for related purposes, or might be mapped directly over GRASP.
   The present document, however, applies to any scenario where it is

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   preferable to re-use the autonomic networking infrastructure itself
   to transfer a significant amount of data, rather than install and
   configure an additional mechanism.

   The node behavior is to use the GRASP Negotiation process to transfer
   and acknowledge multiple blocks of data in successive negotiation
   steps, thereby overcoming the GRASP message size limitation.  The
   emphasis is placed on simplicity rather than efficiency, high
   throughput, or advanced functionality.  For example, if a transfer
   gets out of step or data packets are lost, the strategy is to abort
   the transfer and try again.  In an enterprise network with low bit
   error rates, and with GRASP running over TCP, this is not considered
   a serious issue.  Clearly, a more sophisticated approach could be
   designed but if the application requires that, existing protocols
   could be used, as indicated in the preceding paragraph.

   As for any GRASP operation, the two participants are considered to be
   Autonomic Service Agents (ASAs) and they communicate using a specific
   GRASP Objective Option, containing its own name, some flag bits, a
   loop count, and a value.  In bulk transfer, we can model the ASA
   acting as the source of the transfer as a download server, and the
   destination as a download client.  No changes or extensions are
   required to GRASP itself, but compared to a normal GRASP negotiation,
   the communication pattern is slightly asymmetric:

   1)  The client first discovers the server by the GRASP discovery
      mechanism (M_DISCOVERY and M_RESPONSE messages).

   2)  The client then sends a GRASP negotiation request (M_REQ_NEG
      message).  The value of the objective expresses the requested item
      (e.g., a file name - see the next section for a detailed example).

   3)  The server replies with a negotiation step (M_NEGOTIATE message).
      The value of the objective is the first section of the requested
      item (e.g., the first block of the requested file as a raw byte

   4)  The client replies with a negotiation step (M_NEGOTIATE message).
      The value of the objective is a simple acknowledgement (e.g., the
      text string 'ACK').

   The last two steps repeat until the transfer is complete.  The server
   signals the end by transferring an empty byte string as the final
   value.  In this case the client responds with a normal end to the
   negotiation (M_END message with an O_ACCEPT option).

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   Errors of any kind are handled with the normal GRASP mechanisms, in
   particular by an M_END message with an O_DECLINE option in either
   direction.  In this case the GRASP session terminates.  It is then
   the client's choice whether to retry the operation from the start, as
   a new GRASP session, or to abandon the transfer.  The block size must
   be chosen such that each step does not exceed the GRASP message size
   limit of 2048 bits.

5.4.  Summary

   In summary, the general requirements for the information distribution
   module on each autonomic node are realized by two sub-modules
   handling instant communications and asynchronous communications,
   respectively.  For instantaneous mode, node requirements are simple,
   calling for support for additional signaling.  With minimum efforts,
   reusing the existing GRASP is possible.

   For asynchronous mode, information distribution module uses new
   primitives on the wire, and implements an event queue and an
   information storage mechanism.  An architectural consideration on ANI
   with the information distribution module is briefly discussed in
   Appendix D.

   In both cases, a scenario of bulk information transfer is considered
   where the retrieved information cannot be fitted in one GRASP
   message.  Based on GRASP Negotiation operation, multiple
   transmissions can be repeatedly done in order to transfer bulk
   informtion piece by piece.

6.  Extending GRASP for Information Distribution

6.1.  Realizing Instant P2P Transmission

   This could be a new message in GRASP.  In fragmentary CDDL, an Un-
   solicited Synchronization message follows the pattern:

      unsolicited_synch-message = [M_UNSOLIDSYNCH, session-id,

   A node MAY actively send a unicast Un-solicited Synchronization
   message with the Synchronization data, to another node.  This MAY be
   sent to port GRASP_LISTEN_PORT at the destination address, which
   might be obtained by GRASP Discovery or other possible ways.  The
   synchronization data are in the form of GRASP Option(s) for specific
   synchronization objective(s).

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6.2.  Realizing Instant Selective Flooding

   Since normal flooding is already supported by GRASP, this section
   only defines the selective flooding extension.

   In fragmentary CDDL, the selective flooding follows the pattern:

      selective-flood-option = [O_SELECTIVE_FLOOD, +O_MATCH-CONDITION,
      match-object, action]

         O_MATCH-CONDITION = [O_MATCH-CONDITION, Obj1, match-rule, Obj2]
         Obj1 = text

         match-rule = GREATER / LESS / WITHIN / CONTAIN

         Obj2 = text

         match-object = NEIGHBOR / SELF

         action = FORWARD / DROP

   The option field encapsulates a match-condition option which
   represents the conditions regarding to continue or discontinue flood
   the current message.  For the match-condition option, the Obj1 and
   Obj2 are to objects that need to be compared.  For example, the Obj1
   could be the role of the device and Obj2 could be "RSG".  The match
   rules between the two objects could be greater, less than, within, or
   contain.  The match-object represents of which Obj1 belongs to, it
   could be the device itself or the neighbor(s) intended to be flooded.
   The action means, when the match rule applies, the current device
   just continues flood or discontinues.

6.3.  Realizing Bulk Information Transfer

6.4.  Realizing Subscription as An Event

   In fragmentary CDDL, a Subscription Objective Option follows the

      subscription-objection-option = [SUBSCRIPTION, 2, 2, subobj]
      objective-name = SUBSCRIPTION

      objective-flags = 2

      loop-count = 2

      subobj = text

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   This option MAY be included in GRASP M_Synchronization, when
   included, it means this message is for a subscription to a specific

6.5.  Un_Subscription Objective Option

   In fragmentary CDDL, a Un_Subscribe Objective Option follows the

      Unsubscribe-objection-option = [UNSUBSCRIB, 2, 2, unsubobj]

      objective-name = SUBSCRIPTION

      objective-flags = 2

      loop-count = 2

      unsubobj = text

   This option MAY be included in GRASP M_Synchronization, when
   included, it means this message is for a un-subscription to a
   specific object.

6.6.  Publishing Objective Option

   In fragmentary CDDL, a Publish Objective Option follows the pattern:

      publish-objection-option = [PUBLISH, 2, 2, pubobj]

      objective-name = PUBLISH

      objective-flags = 2

      loop-count = 2

      pubobj = text

   This option MAY be included in GRASP M_Synchronization, when
   included, it means this message is for a publish of a specific object

7.  Security Considerations

   The distribution source authentication could be done at multiple

   *  Outer layer authentication: the GRASP communication is within ACP
      ([RFC8994]).  This is the default GRASP behavior.

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   *  Inner layer authentication: the GRASP communication might not be
      within a protected channel, then there should be embedded
      protection in distribution information itself.  Public key
      infrastructure might be involved in this case.

8.  IANA Considerations


9.  Acknowledgements

   Valuable comments were received from Zoran Despotovic, Brian
   Carpenter, Michael Richardson, Roland Bless, Mohamed Boucadair, Diego
   Lopez, Toerless Eckert and other participants in the ANIMA working

   This document was produced using the xml2rfc tool [RFC2629].

10.  Contributors

   Brian Carpenter
   School of Computer Science
   University of Auckland
   PB 92019
   Auckland 1142
   New Zealand

11.  References

11.1.  Normative References

   [RFC2119]  Bradner, S., "Key words for use in RFCs to Indicate
              Requirement Levels", BCP 14, RFC 2119,
              DOI 10.17487/RFC2119, March 1997,

   [RFC2629]  Rose, M., "Writing I-Ds and RFCs using XML", RFC 2629,
              DOI 10.17487/RFC2629, June 1999,

   [RFC8990]  Bormann, C., Carpenter, B., Ed., and B. Liu, Ed., "GeneRic
              Autonomic Signaling Protocol (GRASP)", RFC 8990,
              DOI 10.17487/RFC8990, May 2021,

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   [RFC8994]  Eckert, T., Ed., Behringer, M., Ed., and S. Bjarnason, "An
              Autonomic Control Plane (ACP)", RFC 8994,
              DOI 10.17487/RFC8994, May 2021,

11.2.  Informative References

              Carpenter, B., Jiang, S., and B. Liu, "Transferring Bulk
              Data over the GeneRic Autonomic Signaling Protocol
              (GRASP)", Work in Progress, Internet-Draft, draft-
              carpenter-anima-grasp-bulk-05, 9 January 2020,

              Du, Z., Jiang, S., Nobre, J., Ciavaglia, L., and M.
              Behringer, "ANIMA Intent Policy and Format", Work in
              Progress, Internet-Draft, draft-du-anima-an-intent-05, 14
              February 2017, <

              Carpenter, B., Liu, B., Wang, W., and X. Gong, "Generic
              Autonomic Signaling Protocol Application Program Interface
              (GRASP API)", Work in Progress, Internet-Draft, draft-
              ietf-anima-grasp-api-08, 14 November 2020,

   [RFC7575]  Behringer, M., Pritikin, M., Bjarnason, S., Clemm, A.,
              Carpenter, B., Jiang, S., and L. Ciavaglia, "Autonomic
              Networking: Definitions and Design Goals", RFC 7575,
              DOI 10.17487/RFC7575, June 2015,

   [RFC8933]  Housley, R., "Update to the Cryptographic Message Syntax
              (CMS) for Algorithm Identifier Protection", RFC 8933,
              DOI 10.17487/RFC8933, October 2020,

   [RFC8995]  Pritikin, M., Richardson, M., Eckert, T., Behringer, M.,
              and K. Watsen, "Bootstrapping Remote Secure Key
              Infrastructure (BRSKI)", RFC 8995, DOI 10.17487/RFC8995,
              May 2021, <>.

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              Tokusashi, Y., "The case for in-network computing on
              demand", DOI 10.1109/RECONFIG.2018.8641696, February 2019,

Appendix A.  Open Issues [RFC Editor: To Be removed before becoming RFC]

   1.  More reference to the use cases in the introduction.

   2.  Better explanation of the required context of the Connected-Car
       case: Not applicable unless the ACP will be extended to the car,
       which may not be desirable with the current ACP design, but maybe
       refocussing on an "autonomous fleet" use-case (e.g.: all cars
       operated by some taxi like service).

   3.  Consider use-case/example of firmware update.  By abstracting the
       location of the firmware from the name of the firmware, while
       providing a way to notify about it, this significantly supports
       distribution of firmware updates.  References to SUIT would

   4.  Issues discussed in

   5.  Rethink/refine terminology, e.g.: "module" seems to be too
       prescriptive.  Refine proposed extensions.

   6.  Provide more protocol behavior description instead of only
       implementation / software module architecture description.
       Reduce the latter or provide better justification for their
       presence due to explained interoperability requirements.

   7.  Better motivation in sections 1..4 of the proposed extensions

   8.  Consider moving examples from appendices into core-text . Ideally
       craft a single use-case showing/applying all extensions (most
       simple use case that uses them all).

   9.  Refine terminology to better match/reuse-the established
       terminology from the pre-existing ANIMA documents.

Appendix B.  Closed Issues [RFC Editor: To Be removed before becoming

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Appendix C.  Change log [RFC Editor: To Be removed before becoming RFC]

   draft-ietf-anima-grasp-distribution-00, 2020-02-25: File name changed
   following WG adoption. __Added appendix A&B for open/closed issues.
   The open issues were comments received during the adoption call.

Appendix D.  Information Distribution Module in ANI

   This appendix describes how the information distribution module fits
   into the ANI and what extensions of GRASP are required.


                      |       ASAs        |
       +-------------Info-Dist. APIs--------------+
       | +---------------+ +--------------------+ |
       | | Instant Dist. | | Asynchronous Dist. | |
       | +---------------+ +--------------------+ |
                      +---GRASP APIs----+
                      |      ACP        |

   As the Fig 1 shows, the information distribution module two sub-
   modules for instant and asynchronous information distributions,
   respectively, and provides APIs to ASAs.  Specific Behaviors of
   modules are described in Section 5.

   Figure E.1 Information Distribution Module and GRASP Extension.

Appendix E.  Asynchronous ID Integrated with GRASP APIs

   Actions triggered to the information distribution module will
   eventually invoke underlying GRASP APIs.  Moreover, EQ and IS modules
   are usually correlated.  When an AF(ASA) publishes information, not
   only such an event is translated and sent to EQ module, but also the
   information is indexed and stored simultaneously.  Similarly, when an
   AF(ASA) subscribes information, not only subscribing event is
   triggered and sent to EQ module, but also the information will be
   retrieved by IS module at the same time.

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   *  Storing and publishing information: This action involves both IS
      and EQ modules where a node that can store the information will be
      discovered first and related event will e published to the
      network.  For this, GRASP APIs discover(), synchronize() and
      flood() are combined to compose such a procedure.  In specific,
      discover() call will specific its objective being to "store_data"
      and the return parameters could be either an ASA_locator who will
      accept to store the data, or an error code indicating that no one
      could afford such data; after that, synchronize() call will send
      the data to the specified ASA_locator and the data will be stored
      at that node, with return of processing results like
      store_data_ack; meanwhile, such a successful event (i.e. data is
      stored successfully) will be flooded via a flood() call to
      interesting parties (such a multicast group existed).

   *  Subscribing and getting information: This action involves both IS
      and EQ modules as well where a node that is interested in a topic
      will subscribe the topic by triggering EQ module and if the topic
      is ready IS module will retrieve the content of the topic (i.e.
      the data).  GRASP APIs such as register_objective(), flood(),
      synchronize() are combined to compose the procedure.  In specific,
      any subscription action received by EQ module will be translated
      to register_objective() call where the interested topic will be
      the parameter inside of the call; the registration will be
      (selectively) flooded to the network by an API call of flood()
      with the option we extended in this draft; once a matched topic is
      found (because of the previous procedure), the node finding such a
      match will call API synchronize() to send the stored data to the

Authors' Addresses

   Xun Xiao
   MRC, Huawei Technologies
   Munich Research Center
   Huawei Technologies
   Riesstr. 25
   80992 Muenchen

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   Bing Liu
   Huawei Technologies
   Q5, Huawei Campus
   No.156 Beiqing Road
   Hai-Dian District, Beijing
   P.R. China

   Artur Hecker
   MRC, Huawei Technologies
   Munich Research Center
   Huawei Technologies
   Riesstr. 25
   80992 Muenchen

   Sheng Jiang
   Huawei Technologies
   Q27, Huawei Campus
   No.156 Beiqing Road
   Hai-Dian District, Beijing
   P.R. China

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