Internet DRAFT - draft-ietf-anima-grasp-distribution
draft-ietf-anima-grasp-distribution
Network Working Group S. Jiang
Internet-Draft BUPT
Intended status: Standards Track A. Hecker
Expires: 11 September 2023 B. Liu
X. Xiao
X. Zheng
Huawei Technologies
Y. Zhang
Individual
10 March 2023
Information Distribution over GRASP
draft-ietf-anima-grasp-distribution-07
Abstract
This document analyzes the Information distribution models in the
Autonomic Networks that are based on the ANI. Most of instantaneous
modes and their requirements have been met by GRASP already.
However, in order to effectively support the asynchronous information
distribution modes, which is newly described in this document,
several new GRASP extensions are defined. This document also
describes the corresponding behaviors on processing these new
extensions.
Status of This Memo
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Copyright Notice
Copyright (c) 2023 IETF Trust and the persons identified as the
document authors. All rights reserved.
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 3
2. Requirements Language . . . . . . . . . . . . . . . . . . . . 3
3. Use Cases of Information Distribution . . . . . . . . . . . . 3
3.1. Service-Based Architecture (SBA) in 3GPP . . . . . . . . 3
3.2. In-Network Computing (INC) . . . . . . . . . . . . . . . 5
3.3. Vehicle-to-Everything (V2X) Communications . . . . . . . 6
3.4. Smart Home . . . . . . . . . . . . . . . . . . . . . . . 7
4. Analysis of Information Distribution Modes and
Requirements . . . . . . . . . . . . . . . . . . . . . . 8
4.1. General Modes of Information Distribution . . . . . . . . 8
4.2. ANI Requirements on Information Distribution . . . . . . 9
4.3. Gaps of current GRASP Protocol . . . . . . . . . . . . . 10
5. New GRASP Extensions for the Conditional Information
Distribution . . . . . . . . . . . . . . . . . . . . . . 10
5.1. Un-solicited Synchronization Message . . . . . . . . . . 10
5.2. Selective-Flooding Option . . . . . . . . . . . . . . . . 11
5.3. Subscription Objective Option . . . . . . . . . . . . . . 11
5.4. Unsubscription Objective Option . . . . . . . . . . . . . 12
5.5. Publishing Objective Option . . . . . . . . . . . . . . . 12
6. Processing Behaviors on Autonomic Nodes . . . . . . . . . . . 13
6.1. Instant Information Distribution (IID) Sub-module . . . . 13
6.1.1. Instant P2P Communication . . . . . . . . . . . . . . 13
6.1.2. Instant Flooding Communication . . . . . . . . . . . 13
6.2. Asynchronous Information Distribution (AID) Sub-module . 14
6.2.1. Information Storage . . . . . . . . . . . . . . . . . 14
6.2.2. Event Queue . . . . . . . . . . . . . . . . . . . . . 17
6.3. Bulk Information Transfer . . . . . . . . . . . . . . . . 18
7. Security Considerations . . . . . . . . . . . . . . . . . . . 20
8. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 20
9. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . 20
10. Contributors . . . . . . . . . . . . . . . . . . . . . . . . 21
11. References . . . . . . . . . . . . . . . . . . . . . . . . . 21
11.1. Normative References . . . . . . . . . . . . . . . . . . 21
11.2. Informative References . . . . . . . . . . . . . . . . . 22
Appendix A. Asynchronous ID Integrated with GRASP APIs . . . . . 23
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 23
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1. Introduction
In Autonomic Networks [RFC7575], Autonomic Service Agents (ASAs)
[RFC8993]running on autonomic nodes constantly exchange information,
e.g. control/management signaling or data exchanging among ASAs. The
Autonomic Network Infrastructure (ANI) [RFC8993] provides generic
support for these ASAs, mostly by GeneRic Autonomic Signaling
Protocol (GRASP)[RFC8990]. This document introduces some important
and typical use cases and analyzes their information distribution
modes. Although most of instantaneous information distribution modes
and their requirements have been met by GRASP already, asynchronous
information distribution modes need new functions to support. In
publishing for retrieval mode, information needs to be stored and re-
distribute on-demand; additionally, conflict resolution is also
needed when stored information is updated with information from
multiple sources.
This document defines a series of GRASP extensions in order to
support such information distribution mode. This document also
describes the corresponding behaviors on processing them.
2. Requirements Language
The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
"SHOULD", "SHOULD NOT", "RECOMMENDED", "NOT RECOMMENDED", "MAY", and
"OPTIONAL" in this document are to be interpreted as described in BCP
14 [RFC2119] [RFC8174] when, and only when, they appear in all
capitals, as shown here.
This document uses terminology defined in [RFC7575].
3. Use Cases of Information Distribution
In this section, we present some important use cases where
information distribution is required and Autonomic Control Plane
(ACP) [RFC8994] support is commonly needed.
3.1. Service-Based Architecture (SBA) in 3GPP
In addition to Internet, carrier network (i.e. wireless mobile
networks) is another world-wide networking system. The current
architecture of 5G system defined by 3GPP follows a service-based
architecture (SBA) where a network function (NF) can dynamically
request a network service from another NF(s) when needed. Note that
one NF can flexibly associate with multiple other NFs, instead of
being physically wired to each other in a static way. NFs
communicate with each other over service-based interface (SBI), which
is also standardized by 3GPP [3GPP.23.501].
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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) Service Exposure and Subscription: SBA requires that a NF can
subscribe a particular service from another NF. This enables a NF
to be notified when interested information occur. To achieve
that, information (e.g., events, results, profiles, and statuses
etc.) have to be stored first, and after that, whenever the
information is requested, it has to be delivered properly to the
requesting NF [TS23.502].
2) 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 firstly 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 there is an available NF, if not, a new NF
must be instantiated [TS23.502].
3) Network Data Analysis Function (NWDAF): Data science technology
is being quickly adopted in many industries, including 3GPP as
well. It is a promising tool to retrieve valuable information
from a large amount of data that is usually hard to be done by
human being manually. NWDAF is a new NF added in to a 3GPP
system. It is a NF dedicated to analyze the data collected from a
network domain, which may consist of several sub-domains. Because
of the importance of data-driven operations, distributed NWDAFs
could exist in different domains in a 3GPP network, and among
them, data storage and transferring will be needed because
different sets of data are required for different tasks/purposes
assigned to those NWDAFs in different domains. For example, if
NWDAF uses machine learning techniques, the data required to train
a neural network model will be different [TS23.501].
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Notice that how the connectivity and trust among different NFs shall
be bootstrapped and maintained by the control plane 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 promoted to 3GPP.
3.2. 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 utilized heavily, combining with
local storage.
Clearly, ASAs running on network nodes in ANI are the abstraction of
the INC use case. ASAs can be deployed for both scenarios above.
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3.3. 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 faster than 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
ANI.
1) Real-time and High Definition Maps (HDM): In the era of
autonomous driving, a digital map is not only 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 regard, 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 Infotainment: 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
consensus 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 information required by the
vehicles. The second mode is more radical where the vehicles 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 establish a trust layer relying on the
security mechanism with Bootstrapping Remote Secure Key
Infrastructure (BRSKI) [RFC8995].
3.4. Smart Home
Smart homes are designed to make home life much easier. Smart homes
refer to a convenient home setup in which appliances and devices can
be remotely controlled from anywhere using a mobile or other network
device over an Internet connection. Devices in the smart home are
connected over the Internet, allowing users to remotely control
functions such as home security access, temperature, lighting, and a
home theater. Smart home has considerable business prospects, and
many Internet giants are investing in them, such as Amazon, Goolge
and Apple. With the development of Internet technology, smart home
user experience getting better and better. In this section, we
present some use cases that are closely related to information
distribution in an ANI.
1) Control Information: The control equipment often sends control
information to specific devices in real time. For example, smart
home with lighting control enables homeowners to reduce
electricity use and benefit from energy-related cost savings. The
control device sends an adjustment instruction to specific lights
according to the ambient brightness in real-time.
2) Multi-Device Collaboration: Media and entertainment, which covers
integrated entertainment systems in the home, including access and
sharing of digital content on different devices, has proved to be
the most prolific. Multi-device collaboration means that multiple
devices work together to complete a service. In this case,
distributed shared objects allow automatic synchronization of
state or digital content between two or more devices. For
example, users watch videos on tablets and/or TVs, and use their
mobile phones to comment on and reply to the videos. In this way,
concurrency, collaboration, and complementarity can be achieved.
In this case, devices have to synchronize the information to the
selected receivers. Compared with broadcast, sending information
only to specific devices can save network traffic and improve
network utilization.
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4. Analysis of Information Distribution Modes and Requirements
According to the specific uses cases described in last section, this
section summarizes the requirements of the use cases as a couple of
general information distribution modes. Then in Section 4.3 , it
described current gaps of GRASP protocol that could not fully support
the distribution modes.
4.1. General Modes of Information Distribution
In a network (either in an Autonomic Network or any other networks),
the way of distributing information could be modeled from the
following two dimensions.
One dimension is from the perspective of the information distribution
participants, there are two categories as below:
1) Point-to-point (P2P) Communication: information is exchanged
between two nodes.
2) Point-to-Multi point (P2MP) Communication: information exchanges
involve one source node and multiple receiving nodes.
The other dimension is from the timing perspective, also categoried
as two modes as below:
1) Instantaneous mode: a source node 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
node must be able to decide, to which node the data is to be sent.
2) Asynchronous mode: here, a source node publishes the content in
some forms in the network, which may later be looked for, found
and retrieved by some other nodes. Here, depending on the size of
the content, either the whole content or only its metadata might
be published into the network. In the latter case the metadata
(e.g. a content descriptor, e.g. a key, and a location in the
network) 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.
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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). This document also gives support for bulk data transfer in
Section 6.3.
4.2. ANI Requirements on Information Distribution
In ANI, on top of the general information distribution modes
described in Section 4.1 , there are also ASA-level specific
requirements of distributing information as the following:
1) Long Communication Intervals. The actual sending of the
information is not necessarily instantaneous with some events.
Sophisticated ASAs 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 ASA might be
to get notified, when the reply is finally available.
2) Common Interest Distribution. ASAs may share information that is
a common interest. For example, the network intent [RFC9316]
needs to be distributed to network nodes enrolled, which is
usually P2MP mode. 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 mode 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
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on autonomic nodes, alive ASAs not only consume but also generate
data information. An example is ASAs coordinating with each other
as distributed schedulers, responding to service requests and
distributing tasks. It is critical for those ASAs to make correct
decisions based on local information, which might be asymmetric as
well. ASAs may also need synthetic/aggregated data information
(e.g. statistic info, like average values of several ASAs, etc.)
to make decisions. In these situations, ASAs 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 mode is inefficient, while
a scalable, common, yet distributed data layer, on which ASAs 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 ASAs 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 ASAs, the implementation of
an ASA is too complicated. Therefore, information distribution
should consider conflict resolution and provides a set of general
solutions for ASAs in order to keep information conflict free.
4.3. Gaps of current GRASP Protocol
As most of instantaneous information distribution modes and their
requirements have been met by GRASP already, asynchronous information
distribution modes need new functions to be supported. In publishing
for retrieval mode, information needs to be stored and re-distribute
on-demand; additionally, conflict resolution is also needed when
stored information is updated with information from multiple sources.
To extend GRASP to support the ASA requirements, some extensions are
defined in Section 5 .
5. New GRASP Extensions for the Conditional Information Distribution
5.1. Un-solicited Synchronization Message
In fragmentary CDDL, an Un-solicited Synchronization message follows
the pattern:
unsolicited_synch-message = [M_UNSOLIDSYNCH, session-id,
objective]
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A node SHOULD actively send a unicast Un-solicited Synchronization
message with the Synchronization data, to another node. This SHOULD
be sent to port GRASP_LISTEN_PORT at the destination address, which
could 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).
5.2. Selective-Flooding Option
Normal flooding mode has already been supported by GRASP. This
section defines a new Selective-Flooding option. Since GRASP is
based on CBOR (Concise Binary Object Representation) [RFC8949], the
format of the Selective-Flooding option is described in the Concise
Data Definition Language (CDDL) [RFC8610] as follows:
Selective-Flooding-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.
5.3. Subscription Objective Option
In fragmentary CDDL, a Subscription Objective Option follows the
pattern:
objective = [Subscription, 2, 2, subobj]
objective-name = Subscription
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objective-flags = 2
loop-count = 2
subobj = text
This option MAY be included in GRASP M_Synchronization, when
included, it means this message is for a subscription to a specific
object.
5.4. Unsubscription Objective Option
In fragmentary CDDL, a Unsubscription Objective Option follows the
pattern:
objective = [Unsubscription, 2, 2, unsubobj]
objective-name = Unsubscription
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.
5.5. Publishing Objective Option
In fragmentary CDDL, a Publishing Objective Option follows the
pattern:
objective = [Publishing, 2, 2, pubobj]
objective-name = Publishing
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 active delivery of a specific
object data.
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6. Processing Behaviors on Autonomic Nodes
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.
6.1. 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.
6.1.1. 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. An extension to support instant P2P communication on
GRASP is described in Section 5. A node SHOULD send a M_UNSOLIDSYNCH
message to the GRASP_LISTEN_PORT of the corresponding node.
6.1.2. 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
again.
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. An exemplary extension to support
selective flooding on GRASP is described in Section 5.
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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:
* O_MATCH- CONDITION in Selective-Flooding-option: matching
condition, a set of matching rules such as addresses of
recipients, node features and so on.
* action in Selective-Flooding-option: what the node needs to do
when the Matching Condition is fulfilled. For example, the action
could be forwarding or dropping the distributed message.
Sent information must be included in the message with Selective-
Flooding-option distributed from the sender. The receiving node
reacts by first checking the carried O_MATCH- 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 in Selective-Flooding-option is followed; if a
neighbor is a recipient, the message is sent accordingly.
6.2. 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.
6.2.1. 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 should be realized in the
following steps.
1) ASA-to-IS Negotiation. An ASA calls the API provided by
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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 SHOULD be handled by
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 SHOULD 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 SHOULD be 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 SHOULD check if the information block
can be afforded by one GRASP message. If so, the information
block MUST be directly sent by calling a GRASP API ([RFC8991]).
Otherwise, a bulk data transmission is needed. It can utilize one
of existing protocols that is independent of the GRASP stack. 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.
6) Information Writing. Once the information block (or a smaller
block) is received, the IS module of the storing peer SHOULD store
the data block in the local storage.
7) (Optional) New Storing Peer Discovery. If the previously
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selected storing peer is not available to store the information
block, the source IS module MUST 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.
Similarly, Getting information from an ANI should 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 SHOULD 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 SHOULD map 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 SHOULD send
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 SHOULD
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 MUST
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.
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6.2.2. Event Queue
The Event Queue (EQ) module is to help ASAs to publish information to
the network and subscribe/unsubscribe to interested information in
asynchronous scenarios. Extensions to support information
publishing, subscription and unsubscripiton on GRASP are described in
Section 5. 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
event groups. If two groups of ASAs could have completely
different purposes, the EQ module allows to create multiple queues
where only ASAs interested in the same topic will be aware of the
corresponding event queue.
2) Event Prioritization: Events SHOULD 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 ASAs to differentiate events (i.e.
information) they publish, subscribe or unsubscribe 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 SHOULD be 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 SHOULD also be specified whether it is control
plane data or user plane data.
2) Priority Specification: According to the type of the event, the
ASA SHOULD 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,
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a queue SHOULD be identified locally if all criteria can be
satisfied. The event SHOULD be added into the queue, otherwise a
new queue will be created to accommodate such an event.
4) Event Propagation: The published event SHOULD be propagated to
the other network nodes in the ANIMA domain. A propagation
algorithm SHOULD 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 SHOULD keep matching published
events and its interested consumers. Once a match is found, the
provider and subscriber(s) SHOULD be notified for final
information retrieval.
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.
6.3. Bulk Information Transfer
In both cases discussed previously, they are limited to distributing
messages containing GRASP Objective Options 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
distribution.
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There are scenarios in autonomic networks where this restriction is a
problem. One case 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 node.
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
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.
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
string).
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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 SHOULD be repeated until the transfer is complete.
The server SHOULD signal 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).
Errors of any kind SHOULD be 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.
7. Security Considerations
The distribution source authentication could be done at multiple
layers:
* Outer layer authentication: the GRASP communication is within ACP
([RFC8994]). This is the default GRASP behavior.
* 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
This document defines a new GRASP message named "M_UNSOLIDSYNCH" and
a new option named "O_SELECTIVE_FLOOD" which need to be added to the
"GRASP Messages and Options" registry defined by [RFC8990]. And this
document defines three new GRASP Objectives, "Subscription",
"Unsubscription" and "Publishing" which need to be added to the
"GRASP Objective Names" .
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
group.
This document was produced using the xml2rfc tool [RFC7991].
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10. Contributors
Brian Carpenter
School of Computer Science
University of Auckland
PB 92019
Auckland 1142
New Zealand
Email: brian.e.carpenter@gmail.com
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,
<https://www.rfc-editor.org/info/rfc2119>.
[RFC5424] Gerhards, R., "The Syslog Protocol", RFC 5424,
DOI 10.17487/RFC5424, March 2009,
<https://www.rfc-editor.org/info/rfc5424>.
[RFC6241] Enns, R., Ed., Bjorklund, M., Ed., Schoenwaelder, J., Ed.,
and A. Bierman, Ed., "Network Configuration Protocol
(NETCONF)", RFC 6241, DOI 10.17487/RFC6241, June 2011,
<https://www.rfc-editor.org/info/rfc6241>.
[RFC8174] Leiba, B., "Ambiguity of Uppercase vs Lowercase in RFC
2119 Key Words", BCP 14, RFC 8174, DOI 10.17487/RFC8174,
May 2017, <https://www.rfc-editor.org/info/rfc8174>.
[RFC8610] Birkholz, H., Vigano, C., and C. Bormann, "Concise Data
Definition Language (CDDL): A Notational Convention to
Express Concise Binary Object Representation (CBOR) and
JSON Data Structures", RFC 8610, DOI 10.17487/RFC8610,
June 2019, <https://www.rfc-editor.org/info/rfc8610>.
[RFC8949] Bormann, C. and P. Hoffman, "Concise Binary Object
Representation (CBOR)", STD 94, RFC 8949,
DOI 10.17487/RFC8949, December 2020,
<https://www.rfc-editor.org/info/rfc8949>.
[RFC8990] Bormann, C., Carpenter, B., Ed., and B. Liu, Ed., "GeneRic
Autonomic Signaling Protocol (GRASP)", RFC 8990,
DOI 10.17487/RFC8990, May 2021,
<https://www.rfc-editor.org/info/rfc8990>.
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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,
<https://www.rfc-editor.org/info/rfc8994>.
11.2. Informative References
[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,
<https://www.rfc-editor.org/info/rfc7575>.
[RFC7991] Hoffman, P., "The "xml2rfc" Version 3 Vocabulary",
RFC 7991, DOI 10.17487/RFC7991, December 2016,
<https://www.rfc-editor.org/info/rfc7991>.
[RFC8991] Carpenter, B., Liu, B., Ed., Wang, W., and X. Gong,
"GeneRic Autonomic Signaling Protocol Application Program
Interface (GRASP API)", RFC 8991, DOI 10.17487/RFC8991,
May 2021, <https://www.rfc-editor.org/info/rfc8991>.
[RFC8993] Behringer, M., Ed., Carpenter, B., Eckert, T., Ciavaglia,
L., and J. Nobre, "A Reference Model for Autonomic
Networking", RFC 8993, DOI 10.17487/RFC8993, May 2021,
<https://www.rfc-editor.org/info/rfc8993>.
[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, <https://www.rfc-editor.org/info/rfc8995>.
[RFC9316] Li, C., Havel, O., Olariu, A., Martinez-Julia, P., Nobre,
J., and D. Lopez, "Intent Classification", RFC 9316,
DOI 10.17487/RFC9316, October 2022,
<https://www.rfc-editor.org/info/rfc9316>.
[The-case-for-in-network-computing-on-demand]
Tokusashi, Y., "The case for in-network computing on
demand", DOI 10.1109/RECONFIG.2018.8641696, February 2019,
<https://ieeexplore.ieee.org/document/8641696>.
[TS23.501] 3GPP, "Technical Specification Group Services and System
Aspects; System architecture for the 5G System (5GS);
Stage 2 (Release 18)", December 2022.
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[TS23.502] 3GPP, "Technical Specification Group Services and System
Aspects; Procedures for the 5G System (5GS); Stage 2
(Release 18)", December 2022.
Appendix A. 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 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
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.
* 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
subscriber.
Authors' Addresses
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Sheng Jiang
Beijing University of Posts and Telecommunications
No. 10 Xitucheng Road
Haidian District
Beijing
100083
China
Email: shengjiang@bupt.edu.cn
Artur Hecker
Huawei Technologies
Munich Research Center
Huawei Technologies
Riesstr. 25
80992 Muenchen
Germany
Email: artur.hecker@huawei.com
Bing Liu
Huawei Technologies
Q5, Huawei Campus
No.156 Beiqing Road
Hai-Dian District, Beijing
100095
P.R. China
Email: leo.liubing@huawei.com
Xun Xiao
Huawei Technologies
Munich Research Center
Huawei Technologies
Riesstr. 25
80992 Muenchen
Germany
Email: xun.xiao@huawei.com
Xiuli Zheng
Huawei Technologies
Q27, Huawei Campus
No.156 Beiqing Road
Hai-Dian District, Beijing
100095
P.R. China
Email: zhengxiuli@huawei.com
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Yanyan Zhang
Individual
Texas
United States of America
Email: linna.purple@gmail.com
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