Internet DRAFT - draft-liu-anima-grasp-distribution
draft-liu-anima-grasp-distribution
ANIMA WG B. Liu
INTERNET-DRAFT Huawei Technologies
Intended Status: Standard Track X. Xiao
Expires: June 14, 2020 A. Hecker
MRC, Huawei Technologies
S. Jiang
Huawei Technologies
Z. Despotovic
MRC, Huawei Technologies
December 12, 2019
Information Distribution in Autonomic Networking
draft-liu-anima-grasp-distribution-13
Abstract
This document proposes a solution for information distribution in
autonomic networks. Information distribution is categorized into two
different modes: 1) instantaneous distribution; 2) publication for
retrieval. In the former case, the information is sent, propagates
and is disposed of after reception. In the latter case, information
needs to be stored in the network.
The capabilities to distribute information are basic and fundamental
needs for an autonomous network (cf. ANI [I-D.ietf-anima-reference-
model]). This document describes typical use cases of information
distribution in ANI and requirements to ANI, such that rich
information distribution can be natively supported. The document
proposes extensions to the autonomic nodes and suggests an
implementation based on GRASP extensions as a protocol on the wire.
Status of this Memo
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The list of current Internet-Drafts can be accessed at
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http://www.ietf.org/1id-abstracts.html
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Copyright and License Notice
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Table of Contents
1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . 3
2. Terminology . . . . . . . . . . . . . . . . . . . . . . . . . . 3
3. Requirements of Enriched Information Distribution . . . . . . . 4
4. Node Behaviors . . . . . . . . . . . . . . . . . . . . . . . . 5
4.1 Instant Information Distribution (IID) Sub-module . . . . . 5
4.2 Asynchronous Information Distribution (AID) Sub-module . . . 6
4.3 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . 10
5. Extending GRASP for Information Distribution . . . . . . . . . 10
5.1 Realizing Instant P2P Transmission . . . . . . . . . . . . . 10
5.2 Realizing Instant Selective Flooding . . . . . . . . . . . . 11
5.3 Realizing Subscription as An Event . . . . . . . . . . . . . 11
5.4 Un_Subscription Objective Option . . . . . . . . . . . . . . 12
5.5 Publishing Objective Option . . . . . . . . . . . . . . . . 12
6. Security Considerations . . . . . . . . . . . . . . . . . . . . 13
7. IANA Considerations . . . . . . . . . . . . . . . . . . . . . . 13
8. References . . . . . . . . . . . . . . . . . . . . . . . . . . 13
8.1 Normative References . . . . . . . . . . . . . . . . . . . . 13
8.2 Informative References . . . . . . . . . . . . . . . . . . . 13
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . . 14
Appendix A. Real-world Use Cases of Information Distribution . . . 15
Appendix B. Information Distribution Module in ANI . . . . . . . . 18
Appendix C. Asynchronous Information Distribution Integrated
with GRASP APIs . . . . . . . . . . . . . . . . . . . . . 18
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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
between AFs.
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 parties, i.e. two nodes.
2) One-to-Many Communication: information exchanges involve an
information source and multiple receivers.
The approaches to information distribution can be chiefly 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
preconfiguration is required, as nodes interested in this
information must be already known to all nodes in the sense that
any receiving node must be able to decide, to which nodes this
data is to be sent.
2) An asynchronous mode (delayed pull): here, a source publishes
the content in some form 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 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 publisher, needs to be able to
determine the node, where the information (or its metadata) can be
stored.
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 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
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information distribution mechanisms they want to use for which type
of information, according to their own preferences (e.g. semantic
routing table, etc.)
This document first analyzes requirements for information
distribution in autonomic networks (Section 3) and then discuss the
relevant node behavior (Section 4). After that, the required GRASP
extensions are formally introduced (Section 5).
2. Terminology
The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
"SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this
document are to be interpreted as described in RFC 2119 [RFC2119].
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3. Requirements for Information Distribution in ANI
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 simplest case, the information can be sent:
1) at once (in one packet, in one flow),
2) straightaway (send-and-forget),
3) to all nodes.
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 Appendix B.
A more complex scenario arises, if only 1) and 2) hold, but the
information only concerns a subset of nodes. Then, some kind of
selection becomes 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 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.
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
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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 description of the content and,
possibly, its location. The fetching can then be implemented in
different, appropriate ways, if necessary as a complex transport
session.
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 or publish 2) look for or
subscribe to 3) store 4) fetch/retrieve 5) instantaneously push
information elements.
In the following cases, situations depicting diverse information
distribution needs are discussed.
1) Long Communication Intervals. The actual sending of the
information is not necessarily instantaneous with some event.
Advanced AFs may involve into longer jobs/tasks (e.g. database
lookup, authentication 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 interest in common
information. 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 dynamics, 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
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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.
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 Appendix A.
4. 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.
4.1 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.
4.1.1 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 mention 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.
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4.1.2 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. 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 Matching Condition: a set of matching rules such as addresses
of recipients, node features and so on.
o 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.
4.2 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
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two modules are described in the following sections.
4.2.1 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
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. Otherwise, a bulk
data transmission is needed. For that, there are multiple ways to
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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-04].
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.
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.
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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.
4.2.2 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
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
data.
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.
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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.
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.
4.3 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,
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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 B.
5. Extending GRASP for Information Distribution
5.1 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,
objective]
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).
5.2 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
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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 Realizing Subscription as An Event
In fragmentary CDDL, a Subscription Objective Option follows the
pattern:
subscription-objection-option = [SUBSCRIPTION, 2, 2, subobj]
objective-name = SUBSCRIPTION
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 Un_Subscription Objective Option
In fragmentary CDDL, a Un_Subscribe Objective Option follows the
pattern:
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.
5.5 Publishing Objective Option
In fragmentary CDDL, a Publish Objective Option follows the pattern:
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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
data.
6. Security Considerations
The distribution source authentication could be done at multiple
layers:
o Outer layer authentication: the GRASP communication is within
ACP (Autonomic Control Plane,
[I-D.ietf-anima-autonomic-control-plane]). This is the default
GRASP behavior.
o 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.
7. IANA Considerations
TBD.
8. References
8.1 Normative References
[I-D.ietf-anima-grasp]
Bormann, D., Carpenter, B., and B. Liu, "A Generic
Autonomic Signaling Protocol (GRASP)", draft-ietf-
animagrasp-15 (Standard Track), October 2017.
8.2 Informative References
[RFC7575] Behringer, M., "Autonomic Networking: Definitions and
Design Goals", RFC 7575, June 2015
[I-D.ietf-anima-autonomic-control-plane]
Eckert, T., Behringer, M., and S. Bjarnason, "An Autonomic
Control Plane (ACP)", draft-behringer-anima-autonomic-
control-plane-13, December 2017.
[I-D.ietf-anima-stable-connectivity-10]
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Eckert, T., Behringer, M., "Using Autonomic Control Plane
for Stable Connectivity of Network OAM", draft-ietf-anima-
stable-connectivity-10, February 2018.
[I-D.ietf-anima-reference-model]
Behringer, M., Carpenter, B., Eckert, T., Ciavaglia, L.,
Pierre P., Liu, B., Nobre, J., and J. Strassner, "A
Reference Model for Autonomic Networking", draft-ietf-
anima-reference-model-05, October 2017.
[I-D.du-anima-an-intent]
Du, Z., Jiang, S., Nobre, J., Ciavaglia, L., and M.
Behringer, "ANIMA Intent Policy and Format", draft-
duanima-an-intent-05 (work in progress), February 2017.
[I-D.ietf-anima-grasp-api]
Carpenter, B., Liu, B., Wang, W., and X. Gong, "Generic
Autonomic Signaling Protocol Application Program Interface
(GRASP API)", draft-ietf-anima-grasp-api-00 (work in
progress), December 2017.
[I-D.carpenter-anima-grasp-bulk-04]
Carpenter, B., Jiang, S., Liu, B., "Transferring Bulk Data
over the GeneRic Autonomic Signaling Protocol (GRASP)",
draft-carpenter-anima-grasp-bulk-04 (work in progress),
July 3, 2019
[3GPP.29.500]
3GPP, "Technical Realization of Service Based
Architecture", 3GPP TS 29.500 15.1.0, 09 2018
[3GPP.23.501]
3GPP, "System Architecture for the 5G System", 3GPP TS
23.501 15.2.0, 6 2018,
<http://www.3gpp.org/ftp/Specs/html-info/23501.htm>.
[3GPP.23.502]
3GPP, "Procedures for the 5G System", 3GPP TS 23.502
15.2.0, 6 2018, <http://www.3gpp.org/ftp/Specs/html-
info/23502.htm>.
[5GAA.use.cases]
White Paper "Toward fully connected vehicles: Edge
computing for advanced automotive communications", 5GAA
<http://5gaa.org/news/toward-fully-connected-vehicles-
edge-computing-for-advanced-automotive-communications/>
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Authors' Addresses
Bing Liu
Huawei Technologies
Q27, Huawei Campus
No.156 Beiqing Road
Hai-Dian District, Beijing 100095
P.R. China
Email: leo.liubing@huawei.com
Sheng Jiang
Huawei Technologies
Q27, Huawei Campus
No.156 Beiqing Road
Hai-Dian District, Beijing 100095
P.R. China
Email: jiangsheng@huawei.com
Xun Xiao
Munich Research Center
Huawei technologies
Riesstr. 25, 80992, Muenchen, Germany
Emails: xun.xiao@huawei.com
Artur Hecker
Munich Research Center
Huawei technologies
Riesstr. 25, 80992, Muenchen, Germany
Emails: artur.hecker@huawei.com
Zoran Despotovic
Munich Research Center
Huawei technologies
Riesstr. 25, 80992, Muenchen, Germany
Emails: zoran.despotovic@huawei.com
Appendix A. Real-world Use Cases of Information Distribution
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The requirement analysis in Section 3 shows that generally
information distribution should be better of as an infrastructure
layer module, which provides to upper layer utilizations. In this
section, we review some use cases from the real-world where an
information distribution module with powerful functions do plays a
critical role there.
A.1 Service-Based Architecture (SBA) in 3GPP 5G
In addition to Internet, the telecommunication network (i.e. carrier
mobile wireless networks) is another world-wide networking system.
The architecture of the 5G mobile networks from 3GPP has been defined
to follow a service-based architecture (SBA) where any network
function (NF) can be dynamically associated 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 with each other over service-based interface (SBI),
which is also standardized by 3GPP [3GPP.23.501].
In order 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. We now list three
requirements that are 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)
[3GPP.23.502].
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
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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 CT adopted HTTP2.0/JSON to be the protocol communicating
between NFs, but autonomic networks can also load HTTP2.0 with in
ACP.)
A.2 Vehicle-to-Everything
Connected car is one of scenarios interested in automotive
manufacturers, carriers and vendors. 5G Automotive Alliance - an
industry collaboration organization defines many promising use cases
where services from car industry should be supported by the 5G mobile
network. Here we list two examples as follows [5GAA.use.cases].
1) Software/Firmware Update: Car manufacturers expect that the
software/firmware of their car products can be remotely
updated/upgraded via 5G network, instead of onsite visiting their
4S stores/dealers offline as nowadays. This requires the network
to provide a mechanism for vehicles to receive the latest software
updates during a certain period of time. In order to run such a
service for a car manufacturer, the network shall not be just like
a network pipe anymore. Instead, information data have to be
stored in the network, and delivered in a publishing/subscribing
fashion. For example, the latest release of a software will be
first distributed and stored at the access edges of the mobile
network, after that, the updates can be pushed by the car
manufacturer or pulled by the car owner as needed.
2) Real-time HD Maps: Autonomous driving clearly requires much
finer details of road maps. Finer details not only include the
details of just static road and streets, but also real-time
information on the road as well as the driving area for both local
urgent situations and intelligent driving scheduling. This asks
for situational awareness at critical road segments in cases of
changing road conditions. Clearly, a huge amount of traffic data
that are real-time collected will have to be stored and shared
across the network. This clearly requires the storage capability,
data synchronization and event notifications in urgent cases from
the network, which are still missing at the infrastructure layer.
A.3 Summary
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Through the general analysis and the concrete examples from the real-
world, we realize that the ways information are exchanged in the
coming new scenarios are not just short and instant anymore. More
advanced as well as diverse information distribution capabilities are
required and should be generically supported from the infrastructure
layer. Upper layer applications (e.g. ASAs in ANIMA) access and
utilize such a unified mechanism for their own services.
Appendix B. Information Distribution Module in ANI
This section describes how the information distribution module fits
into the ANI and what extensions of GRASP are required [I-D.ietf-
anima-grasp].
+-------------------+
| ASAs |
+-------------------+
^
|
v
+-------------Info-Dist. APIs--------------+
| +---------------+ +--------------------+ |
| | Instant Dist. | | Asynchronous Dist. | |
| +---------------+ +--------------------+ |
+------------------------------------------+
^
|
v
+---GRASP APIs----+
| ACP |
+-----------------+
Figure 1. Information Distribution Module and GRASP Extension.
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.
Appendix C. 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
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triggered and sent to EQ module, but also the information will be
retrieved by IS module at the same time.
o 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).
o 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.
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