Guidelines for Autonomic Service Agents
draft-ietf-anima-asa-guidelines-05
The information below is for an old version of the document.
| Document | Type | Active Internet-Draft (anima WG) | |
|---|---|---|---|
| Authors | Brian E. Carpenter , Laurent Ciavaglia , Sheng Jiang , Peloso Pierre | ||
| Last updated | 2022-01-20 (Latest revision 2021-12-19) | ||
| Replaces | draft-carpenter-anima-asa-guidelines | ||
| Stream | Internet Engineering Task Force (IETF) | ||
| Formats | plain text html xml htmlized pdfized bibtex | ||
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| Stream | WG state | Submitted to IESG for Publication | |
| Document shepherd | Toerless Eckert | ||
| Shepherd write-up | Show Last changed 2021-11-18 | ||
| IESG | IESG state | IESG Evaluation::Revised I-D Needed | |
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| Responsible AD | Robert Wilton | ||
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draft-ietf-anima-asa-guidelines-05
Network Working Group B. E. Carpenter
Internet-Draft Univ. of Auckland
Intended status: Informational L. Ciavaglia
Expires: 22 June 2022 Rakuten Mobile
S. Jiang
Huawei Technologies Co., Ltd
P. Peloso
Nokia
19 December 2021
Guidelines for Autonomic Service Agents
draft-ietf-anima-asa-guidelines-05
Abstract
This document proposes guidelines for the design of Autonomic Service
Agents for autonomic networks. Autonomic Service Agents, together
with the Autonomic Network Infrastructure, the Autonomic Control
Plane and the Generic Autonomic Signaling Protocol constitute base
elements of a so-called autonomic networking ecosystem.
Discussion Venue
This note is to be removed before publishing as an RFC.
Discussion of this document takes place on the ANIMA mailing list
(anima@ietf.org), which is archived at
https://mailarchive.ietf.org/arch/browse/anima/
(https://mailarchive.ietf.org/arch/browse/anima/).
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 https://datatracker.ietf.org/drafts/current/.
Internet-Drafts are draft documents valid for a maximum of six months
and may be updated, replaced, or obsoleted by other documents at any
time. It is inappropriate to use Internet-Drafts as reference
material or to cite them other than as "work in progress."
This Internet-Draft will expire on 22 June 2022.
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Copyright Notice
Copyright (c) 2021 IETF Trust and the persons identified as the
document authors. All rights reserved.
This document is subject to BCP 78 and the IETF Trust's Legal
Provisions Relating to IETF Documents (https://trustee.ietf.org/
license-info) in effect on the date of publication of this document.
Please review these documents carefully, as they describe your rights
and restrictions with respect to this document. Code Components
extracted from this document must include Revised BSD License text as
described in Section 4.e of the Trust Legal Provisions and are
provided without warranty as described in the Revised BSD License.
Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 3
2. Logical Structure of an Autonomic Service Agent . . . . . . . 5
3. Interaction with the Autonomic Networking Infrastructure . . 6
3.1. Interaction with the security mechanisms . . . . . . . . 6
3.2. Interaction with the Autonomic Control Plane . . . . . . 6
3.3. Interaction with GRASP and its API . . . . . . . . . . . 7
3.4. Interaction with policy mechanisms . . . . . . . . . . . 8
4. Interaction with Non-Autonomic Components . . . . . . . . . . 8
5. Design of GRASP Objectives . . . . . . . . . . . . . . . . . 9
6. Life Cycle . . . . . . . . . . . . . . . . . . . . . . . . . 10
6.1. Installation phase . . . . . . . . . . . . . . . . . . . 11
6.1.1. Installation phase inputs and outputs . . . . . . . . 12
6.2. Instantiation phase . . . . . . . . . . . . . . . . . . . 12
6.2.1. Operator's goal . . . . . . . . . . . . . . . . . . . 13
6.2.2. Instantiation phase inputs and outputs . . . . . . . 13
6.2.3. Instantiation phase requirements . . . . . . . . . . 14
6.3. Operation phase . . . . . . . . . . . . . . . . . . . . . 15
7. Coordination and Data Models . . . . . . . . . . . . . . . . 15
7.1. Coordination between Autonomic Functions . . . . . . . . 15
7.2. Coordination with Traditional Management Functions . . . 16
7.3. Data Models . . . . . . . . . . . . . . . . . . . . . . . 16
8. Robustness . . . . . . . . . . . . . . . . . . . . . . . . . 16
9. Security Considerations . . . . . . . . . . . . . . . . . . . 18
10. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 19
11. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . 19
12. References . . . . . . . . . . . . . . . . . . . . . . . . . 19
12.1. Normative References . . . . . . . . . . . . . . . . . . 19
12.2. Informative References . . . . . . . . . . . . . . . . . 20
Appendix A. Change log . . . . . . . . . . . . . . . . . . . . . 22
Appendix B. Terminology . . . . . . . . . . . . . . . . . . . . 24
Appendix C. Example Logic Flows . . . . . . . . . . . . . . . . 25
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 29
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1. Introduction
This document proposes guidelines for the design of Autonomic Service
Agents (ASAs) in the context of an Autonomic Network (AN) based on
the Autonomic Network Infrastructure (ANI) outlined in the ANIMA
reference model [RFC8993]. This infrastructure makes use of the
Autonomic Control Plane (ACP) [RFC8994] and the Generic Autonomic
Signaling Protocol (GRASP) [RFC8990]. A general introduction to this
environment may be found at [IPJ], which also includes explanatory
diagrams, and a summary of terminology is in Appendix B.
This document is a contribution to the description of an autonomic
networking ecosystem, recognizing that a deployable autonomic network
needs more than just ACP and GRASP implementations. Such an
autonomic network must achieve management tasks that a Network
Operations Center (NOC) cannot readily achieve manually, such as
continuous resource optimization or automated fault detection and
repair. These tasks, and other management automation goals, are
described at length in [RFC7575]. The net result should be
significant improvement of operational metrics. To achieve this, the
autonomic networking ecosystem must include at least a library of
ASAs and corresponding GRASP technical objective definitions. A
GRASP objective [RFC8990] is a data structure whose main contents are
a name and a value. The value consists of a single configurable
parameter or a set of parameters of some kind.
There must also be tools to deploy and oversee ASAs, and integration
with existing operational mechanisms [RFC8368]. However, this
document focuses on the design of ASAs, with some reference to
implementation and operational aspects.
There is a considerable literature about autonomic agents with a
variety of proposals about how they should be characterized. Some
examples are [DeMola06], [Huebscher08], [Movahedi12] and [GANA13].
However, for the present document, the basic definitions and goals
for autonomic networking given in [RFC7575] apply. According to RFC
7575, an Autonomic Service Agent is "An agent implemented on an
autonomic node that implements an autonomic function, either in part
(in the case of a distributed function) or whole."
ASAs must be distinguished from other forms of software component.
They are components of network or service management; they do not in
themselves provide services to end users. They do however provide
management services to network operators and administrators. For
example, the services envisaged for network function virtualisation
[RFC8568] or for service function chaining [RFC7665] might be managed
by an ASA rather than by traditional configuration tools.
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Another example is that an existing script running within a router to
locally monitor or configure functions or services could be upgraded
to an ASA that could communicate with peer scripts on neighboring or
remote routers. A high-level API will allow such upgraded scripts to
take full advantage of the secure ACP and the discovery, negotiation
and synchronization features of GRASP. Familiar tasks such as
configuring an Interior Gateway Protocol (IGP) on neighboring routers
or even exchanging IGP security keys could be performed securely in
this way. This document mainly addresses issues affecting quite
complex ASAs, but the most useful ones may in fact be rather simple
developments from existing scripts.
The reference model [RFC8993] for autonomic networks explains further
the functionality of ASAs by adding "[An ASA is] a process that makes
use of the features provided by the ANI to achieve its own goals,
usually including interaction with other ASAs via the GRASP protocol
[RFC8990] or otherwise. Of course, it also interacts with the
specific targets of its function, using any suitable mechanism.
Unless its function is very simple, the ASA will need to handle
overlapping asynchronous operations. It may therefore be a quite
complex piece of software in its own right, forming part of the
application layer above the ANI."
As mentioned, there will certainly be simple ASAs that manage a
single objective in a straightforward way and do not need
asynchronous operations. In nodes where computing power and memory
space are limited, ASAs should run at a much lower frequency than the
primary workload, so CPU load should not be a big issue, but memory
footprint in a constrained node is certainly a concern. ASAs
installed in constrained devices will have limited functionality. In
such cases, many aspects of the current document do not apply.
However, in the general case, an ASA may be a relatively complex
software component that will in many cases control and monitor
simpler entities in the same or remote host(s). For example, a
device controller that manages tens or hundreds of simple devices
might contain a single ASA.
The remainder of this document offers guidance on the design of
complex ASAs. Some of the material may be familiar to those
experienced in distributed fault-tolerant and real-time control
systems.
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2. Logical Structure of an Autonomic Service Agent
As mentioned above, all but the simplest ASAs will need to support
asynchronous operations. Different programming environments support
asynchronicity in different ways. In this document, we use an
explicit multi-threading model to describe operations. Alternatives
are discussed in connection with the GRASP API in Section 3.3.
A typical ASA will have a main thread that performs various initial
housekeeping actions such as:
* Obtain authorization credentials, if needed.
* Register the ASA with GRASP.
* Acquire relevant policy parameters.
* Define data structures for relevant GRASP objectives.
* Register with GRASP those objectives that it will actively manage.
* Launch a self-monitoring thread.
* Enter its main loop.
The logic of the main loop will depend on the details of the
autonomic function concerned. Whenever asynchronous operations are
required, extra threads may be launched. Examples of such threads
include:
* Repeatedly flood an objective to the AN, so that any ASA can
receive the objective's latest value.
* Accept incoming synchronization requests for an objective managed
by this ASA.
* Accept incoming negotiation requests for an objective managed by
this ASA, and then conduct the resulting negotiation with the
counterpart ASA.
* Manage subsidiary non-autonomic devices directly.
These threads should all either exit after their job is done, or
enter a wait state for new work, to avoid wasting system resources.
According to the degree of parallelism needed by the application,
some of these threads might be launched in multiple instances. In
particular, if negotiation sessions with other ASAs are expected to
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be long or to involve wait states, the ASA designer might allow for
multiple simultaneous negotiating threads, with appropriate use of
queues and locks to maintain consistency.
The main loop itself could act as the initiator of synchronization
requests or negotiation requests, when the ASA needs data or
resources from other ASAs. In particular, the main loop should watch
for changes in policy parameters that affect its operation. It
should also do whatever is required to avoid unnecessary resource
consumption, for example by limiting its frequency of execution.
The self-monitoring thread is of considerable importance. Autonomic
service agents must never fail. To a large extent this depends on
careful coding and testing, with no unhandled error returns or
exceptions, but if there is nevertheless some sort of failure, the
self-monitoring thread should detect it, fix it if possible, and in
the worst case restart the entire ASA.
Appendix C presents some example logic flows in informal pseudocode.
3. Interaction with the Autonomic Networking Infrastructure
3.1. Interaction with the security mechanisms
An ASA by definition runs in an autonomic node. Before any normal
ASAs are started, such nodes must be bootstrapped into the autonomic
network's secure key infrastructure, typically in accordance with
[RFC8995]. This key infrastructure will be used to secure the ACP
(next section) and may be used by ASAs to set up additional secure
interactions with their peers, if needed.
Note that the secure bootstrap process itself may include special-
purpose ASAs that run in a constrained insecure mode.
3.2. Interaction with the Autonomic Control Plane
In a normal autonomic network, ASAs will run as clients of the ACP,
which will provide a fully secured network environment for all
communication with other ASAs, in most cases mediated by GRASP (next
section).
Note that the ACP formation process itself may include special-
purpose ASAs that run in a constrained insecure mode.
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3.3. Interaction with GRASP and its API
GRASP [RFC8990] is likely to run as a separate process with its API
[RFC8991] available in user space. Thus, ASAs may operate without
special privilege, unless they need it for other reasons. The ASA's
view of GRASP is built around GRASP objectives (Section 5), defined
as data structures containing administrative information such as the
objective's unique name, and its current value. The format and size
of the value is not restricted by the protocol, except that it must
be possible to serialise it for transmission in Concise Binary Object
Representation (CBOR) [RFC8949], subject only to GRASP's maximum
message size as discussed in Section 5.
As discussed in Section 2, GRASP is an asynchronous protocol, and
this document uses a multi-threading model to describe operations.
In many programming environments, an 'event loop' model is used
instead, in which case each thread would be implemented as an event
handler called in turn by the main loop. For this case, the GRASP
API must provide non-blocking calls and possibly support callbacks.
This topic is discussed in more detail in [RFC8991], and other
asynchronicity models are also possible. Whenever necessary, the
GRASP session identifier will be used to distinguish simultaneous
operations.
The GRASP API should offer the following features:
* Registration functions, so that an ASA can register itself and the
objectives that it manages.
* A discovery function, by which an ASA can discover other ASAs
supporting a given objective.
* A negotiation request function, by which an ASA can start
negotiation of an objective with a counterpart ASA. With this,
there is a corresponding listening function for an ASA that wishes
to respond to negotiation requests, and a set of functions to
support negotiating steps. Once a negotiation starts, it is a
symmetric process with both sides sending successive objective
values to each other until agreement is reached (or the
negotiation fails).
* A synchronization function, by which an ASA can request the
current value of an objective from a counterpart ASA. With this,
there is a corresponding listening function for an ASA that wishes
to respond to synchronization requests. Unlike negotiation,
synchronization is an asymmetric process in which the listener
sends a single objective value to the requester.
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* A flood function, by which an ASA can cause the current value of
an objective to be flooded throughout the AN so that any ASA can
receive it.
For further details and some additional housekeeping functions, see
[RFC8991].
The GRASP API is intended to support the various interactions
expected between most ASAs, such as the interactions outlined in
Section 2. However, if ASAs require additional communication between
themselves, they can do so using any desired protocol, such as a TLS
session over the ACP if that meets their needs. One option is to use
GRASP discovery and synchronization as a rendez-vous mechanism
between two ASAs, passing communication parameters such as a TCP port
number via GRASP. As noted above, the ACP should be used to secure
such communications.
3.4. Interaction with policy mechanisms
At the time of writing, the policy mechanisms for the ANI are
undefined. In particular, the use of declarative policies (aka
Intents) for the definition and management of ASA's behaviors remains
a research topic [I-D.irtf-nmrg-ibn-concepts-definitions].
In the cases where ASAs are defined as closed control loops, the
specifications defined in [ZSM009-1] regarding imperative and
declarative goal statements may be applicable.
In the ANI, policy dissemination is expected to operate by an
information distribution mechanism (e.g. via GRASP [RFC8990]) that
can reach all autonomic nodes, and therefore every ASA. However,
each ASA must be capable of operating "out of the box" in the absence
of locally defined policy, so every ASA implementation must include
carefully chosen default values and settings for all policy
parameters.
4. Interaction with Non-Autonomic Components
An ASA, to have any external effects, must also interact with non-
autonomic components of the node where it is installed. For example,
an ASA whose purpose is to manage a resource must interact with that
resource. An ASA whose purpose is to manage an entity that is
already managed by local software must interact with that software.
For example, if such management is performed by NETCONF [RFC6241],
the ASA must interact with the NETCONF server as an independent
NETCONF client in the same node to avoid any inconsistency between
configuration changes delivered via NETCONF and configuration changes
made by the ASA.
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In an environment where systems are virtualized and specialized using
techniques such as network function virtualization or network
slicing, there will be a design choice whether ASAs are deployed once
per physical node or once per virtual context. A related issue is
whether the ANI as a whole is deployed once on a physical network, or
whether several virtual ANIs are deployed. This aspect needs to be
considered by the ASA designer.
5. Design of GRASP Objectives
The general rules for the format of GRASP objectives, their names,
and IANA registration are given in [RFC8990]. Additionally, that
document discusses various general considerations for the design of
objectives, which are not repeated here. However, note that the
GRASP protocol, like HTTP, does not provide transactional integrity.
In particular, steps in a GRASP negotiation are not idempotent. The
design of a GRASP objective and the logic flow of the ASA should take
this into account. One approach, which should be used when possible,
is to design objectives with idempotent semantics. If this is not
possible, typically if an ASA is allocating part of a shared resource
to other ASAs, it needs to ensure that the same part of the resource
is not allocated twice. The easiest way is to run only one
negotiation at a time. If an ASA is capable of overlapping several
negotiations, it must avoid interference between these negotiations.
Negotiations will always end, normally because one end or the other
declares success or failure. If this does not happen, either a
timeout or exhaustion of the loop count will occur. The definition
of a GRASP objective should describe a specific negotiation policy if
it is not self-evident.
GRASP allows a 'dry run' mode of negotiation, where a negotiation
session follows its normal course but is not committed at either end
until a subsequent live negotiation session. If 'dry run' mode is
defined for the objective, its specification, and every
implementation, must consider what state needs to be saved following
a dry run negotiation, such that a subsequent live negotiation can be
expected to succeed. It must be clear how long this state is kept,
and what happens if the live negotiation occurs after this state is
deleted. An ASA that requests a dry run negotiation must take
account of the possibility that a successful dry run is followed by a
failed live negotiation. Because of these complexities, the dry run
mechanism should only be supported by objectives and ASAs where there
is a significant benefit from it.
The actual value field of an objective is limited by the GRASP
protocol definition to any data structure that can be expressed in
Concise Binary Object Representation (CBOR) [RFC8949]. For some
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objectives, a single data item will suffice; for example an integer,
a floating point number or a UTF-8 string. For more complex cases, a
simple tuple structure such as [item1, item2, item3] could be used.
Since CBOR is closely linked to JSON, it is also rather easy to
define an objective whose value is a JSON structure. The formats
acceptable by the GRASP API will limit the options in practice. A
generic solution is for the API to accept and deliver the value field
in raw CBOR, with the ASA itself encoding and decoding it via a CBOR
library.
The maximum size of the value field of an objective is limited by the
GRASP maximum message size. If the default maximum size specified by
[RFC8990] is not enough, the specification of the objective must
indicate the required maximum message size, both for unicast and
multicast messages.
A mapping from YANG to CBOR is defined by [I-D.ietf-core-yang-cbor].
Subject to the size limit defined for GRASP messages, nothing
prevents objectives using YANG in this way.
It is expected that the value field of many objectives will be
extended in service, to add additional information. This has
consequences for the robustness of ASAs, as discussed in Section 8.
6. Life Cycle
The ASA life cycle was discussed in
[I-D.peloso-anima-autonomic-function], from which the following text
was derived.
In simple cases, Autonomic functions could be permanent, in the sense
that ASAs are shipped as part of a product and persist throughout the
product's life. However, in complex cases, a more likely situation
is that ASAs need to be installed or updated dynamically, because of
new requirements or bugs. This section describes one approach to the
resulting life cycle.
Because continuity of service is fundamental to autonomic networking,
the process of seamlessly replacing a running instance of an ASA with
a new version needs to be part of the ASA's design. The implication
of service continuity on the design of ASAs can be illustrated along
the three main phases of the ASA life cycle, namely Installation,
Instantiation and Operation.
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+--------------+
Undeployed ------>| |------> Undeployed
| Installed |
+-->| |---+
Mandate | +--------------+ | Receives a
is revoked | +--------------+ | Mandate
+---| |<--+
| Instantiated |
+-->| |---+
set | +--------------+ | set
down | +--------------+ | up
+---| |<--+
| Operational |
| |
+--------------+
Figure 1: Life Cycle of an Autonomic Service Agent
6.1. Installation phase
We define "installation" to mean that a piece of software is loaded
into a device, along with any necessary libraries, but is not yet
activated.
Before being able to instantiate and run ASAs, the operator will
first provision the infrastructure with the sets of ASA software
corresponding to its needs and objectives. The provisioning of the
infrastructure is realized in the installation phase and consists in
installing (or checking the availability of) the pieces of software
of the different ASAs in a set of Installation Hosts. Installation
Hosts may be nodes of an autonomic network, or servers dedicated to
storing the software images of the different ASAs.
There are 3 properties applicable to the installation of ASAs:
* The dynamic installation property allows installing an ASA on
demand, on any hosts compatible with the ASA.
* The decoupling property allows controlling resources of an
autonomic node from a remote ASA, i.e. an ASA installed on a host
machine different from the autonomic node resources.
* The multiplicity property allows controlling multiple sets of
resources from a single ASA.
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These three properties are very important in the context of the
installation phase as their variations condition how the ASA could be
installed on the infrastructure.
6.1.1. Installation phase inputs and outputs
Inputs are:
* [ASA of a given type] specifies which ASAs to install.
* [Installation_target_Infrastructure] specifies the candidate
Installation Hosts.
* [ASA placement function] specifies how the installation phase will
meet the operator's needs and objectives for the provision of the
infrastructure. This function is only required in the decoupled
mode. It can be as simple as an explicit list of Installation
Hosts, or it could consist of operator-defined criteria and
constraints.
The main output of the installation phase is a [list of ASAs]
installed on [list of Installation Hosts]. This output is also
useful for the coordination function where it acts as a static
interaction map (see Section 7.1).
The condition to validate in order to pass to next phase is to ensure
that [list of ASAs] are well installed on [list of Installation
Hosts]. The state of the ASAs at the end of the installation phase
is installed (but not instantiated). A minimum set of primitives to
support the installation of ASAs could be: install(list of ASAs,
Installation_target_Infrastructure, ASA placement function), and
uninstall (list of ASAs).
6.2. Instantiation phase
We define "instantiation" as the operation of creating a single ASA
instance from the corresponding piece of installed software.
Once the ASAs are installed on the appropriate hosts in the network,
these ASAs may start to operate. From the operator viewpoint, an
operating ASA means the ASA manages the network resources as per the
objectives given. At the ASA local level, operating means executing
their control loop algorithm.
But right before that, there are two things to take into
consideration. First, there is a difference between (1) having a
piece of code available to run on a host and (2) having an agent
based on this piece of code running inside the host. Second, in a
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coupled case, determining which resources are controlled by an ASA is
straightforward (the ASA runs on the same autonomic node as the
resources it is controlling); in a decoupled mode determining this is
a bit more complex: a starting agent will have to either discover the
set of resources it ought to control, or such information has to be
communicated to the ASA.
The instantiation phase of an ASA covers both these aspects: starting
the agent code (when this does not start automatically) and
determining which resources have to be controlled (when this is not
straightforward).
6.2.1. Operator's goal
Through this phase, the operator wants to control its autonomic
network regarding at least two aspects:
1 determine the scope of autonomic functions by instructing which
network resources have to be managed by which autonomic function
(and more precisely by which release of the ASA software code,
e.g., version number or provider),
2 determine how the autonomic functions are organized by
instantiating a set of ASAs across one or more autonomic nodes and
instructing them accordingly about the other ASAs in the set as
necessary.
In this phase, the operator may also want to set goals for autonomic
functions, e.g., by configuring GRASP objectives.
The operator's goal can be summarized in an instruction to the ANIMA
ecosystem matching the following format, explained in detail in the
next sub-section:
[instances of ASAs of a given type] ready to control
[Instantiation_target_Infrastructure] with
[Instantiation_target_parameters]
6.2.2. Instantiation phase inputs and outputs
Inputs are:
* [instances of ASAs of a given type] that specifies which ASAs to
instantiate
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* [Instantiation_target_Infrastructure] that specifies which are the
resources to be managed by the autonomic function; this can be the
whole network or a subset of it like a domain, a physical segment
or even a specific list of resources,
* [Instantiation_target_parameters] that specifies which are the
GRASP objectives to be sent to ASAs (e.g., an optimization target)
Outputs are:
* [Set of ASAs - Resources relations] describing which resources are
managed by which ASA instances, this is not a formal message, but
a resulting configuration of a set of ASAs.
6.2.3. Instantiation phase requirements
The instructions described in Section 6.2 could be either:
* Sent to a targeted ASA. In the case, the receiving Agent will
have to manage the specified list of
[Instantiation_target_Infrastructure], with the
[Instantiation_target_parameters].
* Broadcast to all ASAs. In this case, the ASAs would collectively
determine from the list which Agent(s) would handle which
[Instantiation_target_Infrastructure], with the
[Instantiation_target_parameters].
These instructions may be grouped as a specific data structure,
referred to as an ASA Instance Mandate. The specification of such an
ASA Instance Mandate is beyond the scope of this document.
The conclusion of this instantiation phase is a set of ASA instances
ready to operate. These ASA instances are characterized by the
resources they manage, the metrics being monitored and the actions
that can be executed (like modifying certain parameters values). The
description of the ASA instance may be defined in an ASA Instance
Manifest data structure. The specification of such an ASA Instance
Manifest is beyond the scope of this document.
The ASA Instance Manifest does not only serve informational purposes
such as acknowledgement of successful instantiation to the operator,
but is also necessary for further autonomic operations with:
* coordinated entities (see Section 7.1)
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* collaborative entities with purposes such as to establish
knowledge exchange (some ASAs may produce knowledge or monitor
metrics that would be useful for other ASAs)
6.3. Operation phase
During the Operation phase, the operator can:
* Activate/Deactivate ASAs: enable/disable their autonomic loops.
* Modify ASAs targets: set different technical objectives.
* Modify ASAs managed resources: update the instance mandate to
specify a different set of resources to manage (only applicable to
decoupled ASAs).
During the Operation phase, running ASAs can interact with other
ASAs:
* in order to exchange knowledge (e.g. an ASA providing traffic
predictions to a load balancing ASA)
* in order to collaboratively reach an objective (e.g. ASAs
pertaining to the same autonomic function will collaborate, e.g.,
in the case of a load balancing function, by modifying link
metrics according to neighboring resource loads)
During the Operation phase, running ASAs are expected to apply
coordination schemes as per Section 7.1.
7. Coordination and Data Models
7.1. Coordination between Autonomic Functions
Some autonomic functions will be completely independent of each
other. However, others are at risk of interfering with each other -
for example, two different optimization functions might both attempt
to modify the same underlying parameter in different ways. In a
complete system, a method is needed of identifying ASAs that might
interfere with each other and coordinating their actions when
necessary. This issue is considered in detail in
[I-D.ciavaglia-anima-coordination].
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7.2. Coordination with Traditional Management Functions
Some ASAs will have functions that overlap with existing
configuration tools and network management mechanisms such as command
line interfaces, DHCP, DHCPv6, SNMP, NETCONF, and RESTCONF. This is
of course an existing problem whenever multiple configuration tools
are in use by the NOC. Each ASA designer will need to consider this
issue and how to avoid clashes and inconsistencies. Some specific
considerations for interaction with OAM tools are given in [RFC8368].
As another example, [RFC8992] describes how autonomic management of
IPv6 prefixes can interact with prefix delegation via DHCPv6. The
description of a GRASP objective and of an ASA using it should
include a discussion of any such interactions.
7.3. Data Models
Management functions often include a shared data model, quite likely
to be expressed in a formal notation such as YANG. This aspect
should not be an afterthought in the design of an ASA. To the
contrary, the design of the ASA and of its GRASP objectives should
match the data model; as noted in Section 5, YANG serialized as CBOR
may be used directly as the value of a GRASP objective.
8. Robustness
It is of great importance that all components of an autonomic system
are highly robust. Although ASA designers should aim for their
component to never fail, it is more important to design the ASA to
assume that failures will happen and to gracefully recover from those
failures when they occur. Hence, this section lists various aspects
of robustness that ASA designers should consider:
1. If despite all precautions, an ASA does encounter a fatal error,
it should in any case restart automatically and try again. To
mitigate a loop in case of persistent failure, a suitable pause
should be inserted before such a restart. The length of the
pause depends on the use case.
2. If a newly received or calculated value for a parameter falls
out of bounds, the corresponding parameter should be either left
unchanged or restored to a safe value.
3. If a GRASP synchronization or negotiation session fails for any
reason, it may be repeated after a suitable pause. The length
of the pause depends on the use case.
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4. If a session fails repeatedly, the ASA should consider that its
peer has failed, and cause GRASP to flush its discovery cache
and repeat peer discovery.
5. In any case, it may be prudent to repeat discovery periodically,
depending on the use case.
6. Any received GRASP message should be checked. If it is wrongly
formatted, it should be ignored. Within a unicast session, an
Invalid message (M_INVALID) may be sent. This function may be
provided by the GRASP implementation itself.
7. Any received GRASP objective should be checked. Basic
formatting errors like invalid CBOR will likely be detected by
GRASP itself, but the ASA is responsible for checking the
precise syntax and semantics of a received objective. If it is
wrongly formatted, it should be ignored. Within a negotiation
session, a Negotiation End message (M_END) with a Decline option
(O_DECLINE) should be sent. An ASA may log such events for
diagnostic purposes.
8. On the other hand, the definitions of GRASP objectives are very
likely to be extended, using the flexibility of CBOR or JSON.
Therefore, ASAs should be able to deal gracefully with unknown
components within the values of objectives. The specification
of an objective should describe how unknown components are to be
handled (ignored, logged and ignored, or rejected as an error).
9. If an ASA receives either an Invalid message (M_INVALID) or a
Negotiation End message (M_END) with a Decline option
(O_DECLINE), one possible reason is that the peer ASA does not
support a new feature of either GRASP or of the objective in
question. In such a case the ASA may choose to repeat the
operation concerned without using that new feature.
10. All other possible exceptions should be handled in an orderly
way. There should be no such thing as an unhandled exception
(but see point 1 above).
At a slightly more general level, ASAs are not services in
themselves, but they automate services. This has a fundamental
impact on how to design robust ASAs. In general, when an ASA
observes a particular state (1) of operations of the services/
resources it controls, it typically aims to improve this state to a
better state, say (2). Ideally, the ASA is built so that it can
ensure that any error encountered can still lead to returning to (1)
instead of a state (3) which is worse than (1). One example instance
of this principle is "make-before-break" used in reconfiguration of
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routing protocols in manual operations. This principle of operations
can accordingly be coded into the operation of an ASA. The GRASP dry
run option mentioned in Section 5 is another tool helpful for this
ASA design goal of "test-before-make".
9. Security Considerations
ASAs are intended to run in an environment that is protected by the
Autonomic Control Plane [RFC8994], admission to which depends on an
initial secure bootstrap process such as BRSKI [RFC8995]. Such an
ACP can provide keying material for mutual authentication between
ASAs as well as confidential communication channels for messages
between ASAs. In some deployments, a secure partition of the link
layer might be used instead. However, this does not relieve ASAs of
responsibility for security. When ASAs configure or manage network
elements outside the ACP, potentially in a different physical node,
they must interact with other non-autonomic software components to
perform their management functions. The details are specific to each
case, but this has an important security implication. An ASA might
act as a loophole by which the managed entity could penetrate the
security boundary of the ANI. Thus, ASAs must be designed to avoid
loopholes such as passing on executable code, and should if possible
operate in an unprivileged mode. In particular, they must use secure
coding practices, e.g., carefully validate all incoming information
and avoid unnecessary elevation of privilege. This will apply in
particular when an ASA interacts with a management component such as
a NETCONF server.
A similar situation will arise if an ASA acts as a gateway between
two separate autonomic networks, i.e. it has access to two separate
ACPs. Such an ASA must also be designed to avoid loopholes and to
validate incoming information from both sides.
As appropriate to their specific functions, ASAs should take account
of relevant privacy considerations [RFC6973].
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The initial version of the autonomic infrastructure assumes that all
autonomic nodes are trusted by virtue of their admission to the ACP.
ASAs are therefore trusted to manipulate any GRASP objective, simply
because they are installed on a node that has successfully joined the
ACP. In the general case, a node may have multiple roles and a role
may use multiple ASAs, each using multiple GRASP objectives.
Additional mechanisms for the fine-grained authorization of nodes and
ASAs to manipulate specific GRASP objectives could be designed.
Independently of this, interfaces between ASAs and the router
configuration and monitoring services of the node can be subject to
authentication that provides more fine-grained authorization for
specific services. These additional authentication parameters could
be passed to an ASA during its instantiation phase.
10. IANA Considerations
This document makes no request of the IANA.
11. Acknowledgements
Valuable comments were received from Michael Behringer, Menachem
Dodge, Martin Dürst, Toerless Eckert, Thomas Fossati, Alex Galis,
Bing Liu, Michael Richardson, and Rob Wilton.
12. References
12.1. Normative References
[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>.
[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>.
[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>.
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12.2. Informative References
[DeMola06] De Mola, F. and R. Quitadamo, "An Agent Model for Future
Autonomic Communications", Proceedings of the 7th WOA 2006
Workshop From Objects to Agents 51-59, September 2006.
[GANA13] "Autonomic network engineering for the self-managing
Future Internet (AFI): GANA Architectural Reference Model
for Autonomic Networking, Cognitive Networking and Self-
Management.", April 2013,
<http://www.etsi.org/deliver/etsi_gs/
AFI/001_099/002/01.01.01_60/gs_afi002v010101p.pdf>.
[Huebscher08]
Huebscher, M. C. and J. A. McCann, "A survey of autonomic
computing - degrees, models, and applications", ACM
Computing Surveys (CSUR) Volume 40 Issue 3 DOI:
10.1145/1380584.1380585, August 2008.
[I-D.ciavaglia-anima-coordination]
Ciavaglia, L. and P. Pierre, "Autonomic Functions
Coordination", Work in Progress, Internet-Draft, draft-
ciavaglia-anima-coordination-01, 21 March 2016,
<https://datatracker.ietf.org/doc/html/draft-ciavaglia-
anima-coordination-01>.
[I-D.ietf-core-yang-cbor]
Veillette, M., Petrov, I., Pelov, A., Bormann, C., and M.
Richardson, "CBOR Encoding of Data Modeled with YANG",
Work in Progress, Internet-Draft, draft-ietf-core-yang-
cbor-17, 25 October 2021,
<https://datatracker.ietf.org/doc/html/draft-ietf-core-
yang-cbor-17>.
[I-D.irtf-nmrg-ibn-concepts-definitions]
Clemm, A., Ciavaglia, L., Granville, L. Z., and J.
Tantsura, "Intent-Based Networking - Concepts and
Definitions", Work in Progress, Internet-Draft, draft-
irtf-nmrg-ibn-concepts-definitions-06, 15 December 2021,
<https://datatracker.ietf.org/doc/html/draft-irtf-nmrg-
ibn-concepts-definitions-06>.
[I-D.peloso-anima-autonomic-function]
Pierre, P. and L. Ciavaglia, "A Day in the Life of an
Autonomic Function", Work in Progress, Internet-Draft,
draft-peloso-anima-autonomic-function-01, 21 March 2016,
<https://datatracker.ietf.org/doc/html/draft-peloso-anima-
autonomic-function-01>.
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[IPJ] Behringer, M., Bormann, C., Carpenter, B. E., Eckert, T.,
Campos Nobre, J., Jiang, S., Li, Y., and M. C. Richardson,
"Autonomic Networking Gets Serious", The Internet Protocol
Journal Volume: 24 , Issue: 3, ISSN 1944-1134, Page(s): 2
- 18, October 2021, <https://ipj.dreamhosters.com/wp-
content/uploads/2021/10/243-ipj.pdf>.
[Movahedi12]
Movahedi, Z., Ayari, M., Langar, R., and G. Pujolle, "A
Survey of Autonomic Network Architectures and Evaluation
Criteria", IEEE Communications Surveys & Tutorials Volume:
14 , Issue: 2 DOI: 10.1109/SURV.2011.042711.00078,
Page(s): 464 - 490, 2012.
[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>.
[RFC6973] Cooper, A., Tschofenig, H., Aboba, B., Peterson, J.,
Morris, J., Hansen, M., and R. Smith, "Privacy
Considerations for Internet Protocols", RFC 6973,
DOI 10.17487/RFC6973, July 2013,
<https://www.rfc-editor.org/info/rfc6973>.
[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>.
[RFC7665] Halpern, J., Ed. and C. Pignataro, Ed., "Service Function
Chaining (SFC) Architecture", RFC 7665,
DOI 10.17487/RFC7665, October 2015,
<https://www.rfc-editor.org/info/rfc7665>.
[RFC8368] Eckert, T., Ed. and M. Behringer, "Using an Autonomic
Control Plane for Stable Connectivity of Network
Operations, Administration, and Maintenance (OAM)",
RFC 8368, DOI 10.17487/RFC8368, May 2018,
<https://www.rfc-editor.org/info/rfc8368>.
[RFC8568] Bernardos, CJ., Rahman, A., Zuniga, JC., Contreras, LM.,
Aranda, P., and P. Lynch, "Network Virtualization Research
Challenges", RFC 8568, DOI 10.17487/RFC8568, April 2019,
<https://www.rfc-editor.org/info/rfc8568>.
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[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>.
[RFC8992] Jiang, S., Ed., Du, Z., Carpenter, B., and Q. Sun,
"Autonomic IPv6 Edge Prefix Management in Large-Scale
Networks", RFC 8992, DOI 10.17487/RFC8992, May 2021,
<https://www.rfc-editor.org/info/rfc8992>.
[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>.
[ZSM009-1] "Zero-touch network and Service Management (ZSM); Closed-
Loop Automation; Part 1: Enablers", June 2021,
<https://www.etsi.org/deliver/etsi_gs/
ZSM/001_099/00901/01.01.01_60/gs_ZSM00901v010101p.pdf>.
Appendix A. Change log
This section is to be removed before publishing as an RFC.
draft-ietf-anima-asa-guidelines-05, 2021-12-20:
* Clarified NETCONF wording.
* Removed <CODE BEGINS> on advice from IETF Trust
* Noted resource limits in constrained nodes
* Strengthened text on data integrity in resource management example
* Strengthen discussion of extensibility of GRASP objectives.
* Other editorial improvements from IETF Last Call reviews
draft-ietf-anima-asa-guidelines-04, 2021-11-20:
* Added terminology appendix
* Further clarified discussion of asynch operations
* Other editorial improvements from AD review
draft-ietf-anima-asa-guidelines-03, 2021-11-07:
* Added security consideration for gateway ASAs
* Cite IPJ article
draft-ietf-anima-asa-guidelines-02, 2021-09-13:
* Added note on maximum message size.
* Editorial fixes
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draft-ietf-anima-asa-guidelines-01, 2021-06-27:
* Incorporated shepherd's review comments
* Editorial fixes
draft-ietf-anima-asa-guidelines-00, 2020-11-14:
* Adopted by WG
* Editorial fixes
draft-carpenter-anima-asa-guidelines-09, 2020-07-25:
* Additional text on future authorization.
* Editorial fixes
draft-carpenter-anima-asa-guidelines-08, 2020-01-10:
* Introduced notion of autonomic ecosystem.
* Minor technical clarifications.
* Converted to v3 format.
draft-carpenter-anima-asa-guidelines-07, 2019-07-17:
* Improved explanation of threading vs event-loop
* Other editorial improvements.
draft-carpenter-anima-asa-guidelines-06, 2018-01-07:
* Expanded and improved example logic flow.
* Editorial corrections.
draft-carpenter-anima-asa-guidelines-05, 2018-06-30:
* Added section on relationshp with non-autonomic components.
* Editorial corrections.
draft-carpenter-anima-asa-guidelines-04, 2018-03-03:
* Added note about simple ASAs.
* Added note about NFV/SFC services.
* Improved text about threading v event loop model
* Added section about coordination with traditional tools.
* Added appendix with example logic flow.
draft-carpenter-anima-asa-guidelines-03, 2017-10-25:
* Added details on life cycle.
* Added details on robustness.
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* Added co-authors.
draft-carpenter-anima-asa-guidelines-02, 2017-07-01:
* Expanded description of event-loop case.
* Added note about 'dry run' mode.
draft-carpenter-anima-asa-guidelines-01, 2017-01-06:
* More sections filled in.
draft-carpenter-anima-asa-guidelines-00, 2016-09-30:
* Initial version
Appendix B. Terminology
This appendix summarises various acronyms and terminology used in the
document. Where no other reference is given, please consult
[RFC8993] or [RFC7575].
* Autonomic: Self-managing (self-configuring, self-protecting, self-
healing, self-optimizing), but allowing high-level guidance by a
central entity such as a NOC.
* Autonomic Function: A function that adapts on its own to a
changing environment.
* Autonomic Node: A node that employs autonomic functions.
* Autonomic Domain: A collection of autonomic nodes that
collaborate.
* ACP: Autonomic Control Plane [RFC8994].
* AN: Autonomic Network, which underlies an autonomic domain.
* ANI: Autonomic Network Infrastructure.
* ASA: Autonomic Service Agent. An agent installed on an autonomic
node that implements an autonomic function, either partially (in
the case of a distributed function) or completely.
* BRSKI: Bootstrapping Remote Secure Key Infrastructure [RFC8995].
* CBOR: Concise Binary Object Representation [RFC8949].
* GRASP: Generic Autonomic Signaling Protocol [RFC8990].
* GRASP API: GRASP Application Programming Interface [RFC8991].
* NOC: Network Operations Center [RFC8368].
* Objective: A GRASP technical objective is a data structure whose
main contents are a name and a value. The value consists of a
single configurable parameter or a set of parameters of some kind.
[RFC8990].
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Appendix C. Example Logic Flows
This appendix describes generic logic flows that combine to act as an
Autonomic Service Agent (ASA) for resource management. Note that
these are illustrative examples, and in no sense requirements. As
long as the rules of GRASP are followed, a real implementation could
be different. The reader is assumed to be familiar with GRASP
[RFC8990] and its conceptual API [RFC8991].
A complete autonomic function for a distributed resource will consist
of a number of instances of the ASA placed at relevant points in a
network. Specific details will of course depend on the resource
concerned. One example is IP address prefix management, as specified
in [RFC8992]. In this case, an instance of the ASA will exist in
each delegating router.
An underlying assumption is that there is an initial source of the
resource in question, referred to here as an origin ASA. The other
ASAs, known as delegators, obtain supplies of the resource from the
origin, and then delegate quantities of the resource to consumers
that request it, and recover it when no longer needed.
Another assumption is there is a set of network wide policy
parameters, which the origin will provide to the delegators. These
parameters will control how the delegators decide how much resource
to provide to consumers. Thus, the ASA logic has two operating
modes: origin and delegator. When running as an origin, it starts by
obtaining a quantity of the resource from the NOC, and it acts as a
source of policy parameters, via both GRASP flooding and GRASP
synchronization. (In some scenarios, flooding or synchronization
alone might be sufficient, but this example includes both.)
When running as a delegator, it starts with an empty resource pool,
it acquires the policy parameters by GRASP synchronization, and it
delegates quantities of the resource to consumers that request it.
Both as an origin and as a delegator, when its pool is low it seeks
quantities of the resource by requesting GRASP negotiation with peer
ASAs. When its pool is sufficient, it hands out resource to peer
ASAs in response to negotiation requests. Thus, over time, the
initial resource pool held by the origin will be shared among all the
delegators according to demand.
In theory a network could include any number of origins and any
number of delegators, with the only condition being that each
origin's initial resource pool is unique. A realistic scenario is to
have exactly one origin and as many delegators as you like. A
scenario with no origin is useless.
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An implementation requirement is that resource pools are kept in
stable storage. Otherwise, if a delegator exits for any reason, all
the resources it has obtained or delegated are lost. If an origin
exits, its entire spare pool is lost. The logic for using stable
storage and for crash recovery is not included in the pseudocode
below, which focuses on communication between ASAs. Since GRASP
operations are not intrinsically idempotent, data integrity during
failure scenarios is the responsibility of the ASA designer. This is
a complex topic in its own right that is not discussed in the present
document.
The description below does not implement GRASP's 'dry run' function.
That would require temporarily marking any resource handed out in a
dry run negotiation as reserved, until either the peer obtains it in
a live run, or a suitable timeout occurs.
The main data structures used in each instance of the ASA are:
* The resource_pool, for example an ordered list of available
resources. Depending on the nature of the resource, units of
resource are split when appropriate, and a background garbage
collector recombines split resources if they are returned to the
pool.
* The delegated_list, where a delegator stores the resources it has
given to subsidiary devices.
Possible main logic flows are below, using a threaded implementation
model. The transformation to an event loop model should be apparent
- each thread would correspond to one event in the event loop.
The GRASP objectives are as follows:
* ["EX1.Resource", flags, loop_count, value] where the value depends
on the resource concerned, but will typically include its size and
identification.
* ["EX1.Params", flags, loop_count, value] where the value will be,
for example, a JSON object defining the applicable parameters.
In the outline logic flows below, these objectives are represented
simply by their names.
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MAIN PROGRAM:
Create empty resource_pool (and an associated lock)
Create empty delegated_list
Determine whether to act as origin
if origin:
Obtain initial resource_pool contents from NOC
Obtain value of EX1.Params from NOC
Register ASA with GRASP
Register GRASP objectives EX1.Resource and EX1.Params
if origin:
Start FLOODER thread to flood EX1.Params
Start SYNCHRONIZER listener for EX1.Params
Start MAIN_NEGOTIATOR thread for EX1.Resource
if not origin:
Obtain value of EX1.Params from GRASP flood or synchronization
Start DELEGATOR thread
Start GARBAGE_COLLECTOR thread
good_peer = none
do forever:
if resource_pool is low:
Calculate amount A of resource needed
Discover peers using GRASP M_DISCOVER / M_RESPONSE
if good_peer in peers:
peer = good_peer
else:
peer = #any choice among peers
grasp.request_negotiate("EX1.Resource", peer)
#i.e., send negotiation request
Wait for response (M_NEGOTIATE, M_END or M_WAIT)
if OK:
if offered amount of resource sufficient:
Send M_END + O_ACCEPT #negotiation succeeded
Add resource to pool
good_peer = peer #remember this choice
else:
Send M_END + O_DECLINE #negotiation failed
sleep() #periodic timer suitable for application scenario
MAIN_NEGOTIATOR thread:
do forever:
grasp.listen_negotiate("EX1.Resource")
#i.e., wait for negotiation request
Start a separate new NEGOTIATOR thread for requested amount A
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NEGOTIATOR thread:
Request resource amount A from resource_pool
if not OK:
while not OK and A > Amin:
A = A-1
Request resource amount A from resource_pool
if OK:
Offer resource amount A to peer by GRASP M_NEGOTIATE
if received M_END + O_ACCEPT:
#negotiation succeeded
elif received M_END + O_DECLINE or other error:
#negotiation failed
else:
Send M_END + O_DECLINE #negotiation failed
#thread exits
DELEGATOR thread:
do forever:
Wait for request or release for resource amount A
if request:
Get resource amount A from resource_pool
if OK:
Delegate resource to consumer #atomic
Record in delegated_list #operation
else:
Signal failure to consumer
Signal main thread that resource_pool is low
else:
Delete resource from delegated_list
Return resource amount A to resource_pool
SYNCHRONIZER thread:
do forever:
Wait for M_REQ_SYN message for EX1.Params
Reply with M_SYNCH message for EX1.Params
FLOODER thread:
do forever:
Send M_FLOOD message for EX1.Params
sleep() #periodic timer suitable for application scenario
Carpenter, et al. Expires 22 June 2022 [Page 28]
Internet-Draft ASA Guidelines December 2021
GARBAGE_COLLECTOR thread:
do forever:
Search resource_pool for adjacent resources
Merge adjacent resources
sleep() #periodic timer suitable for application scenario
Authors' Addresses
Brian Carpenter
School of Computer Science
University of Auckland
PB 92019
Auckland 1142
New Zealand
Email: brian.e.carpenter@gmail.com
Laurent Ciavaglia
Rakuten Mobile
Paris
France
Email: laurent.ciavaglia@rakuten.com
Sheng Jiang
Huawei Technologies Co., Ltd
Q14 Huawei Campus
156 Beiqing Road
Hai-Dian District
Beijing
100095
China
Email: jiangsheng@huawei.com
Pierre Peloso
Nokia
Villarceaux
91460 Nozay
France
Email: pierre.peloso@nokia.com
Carpenter, et al. Expires 22 June 2022 [Page 29]