Internet DRAFT - draft-carpenter-anima-asa-guidelines
draft-carpenter-anima-asa-guidelines
Network Working Group B. E. Carpenter
Internet-Draft Univ. of Auckland
Intended status: Informational L. Ciavaglia
Expires: 26 January 2021 Nokia
S. Jiang
Huawei Technologies Co., Ltd
P. Peloso
Nokia
25 July 2020
Guidelines for Autonomic Service Agents
draft-carpenter-anima-asa-guidelines-09
Abstract
This document proposes guidelines for the design of Autonomic Service
Agents for autonomic networks, as a contribution to describing an
autonomic ecosystem. It is based on the Autonomic Network
Infrastructure outlined in the ANIMA reference model, using the
Autonomic Control Plane and the Generic Autonomic Signaling Protocol.
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
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This Internet-Draft will expire on 26 January 2021.
Copyright Notice
Copyright (c) 2020 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/
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Please review these documents carefully, as they describe your rights
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and restrictions with respect to this document. Code Components
extracted from this document must include Simplified BSD License text
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provided without warranty as described in the Simplified BSD License.
Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 2
2. Logical Structure of an Autonomic Service Agent . . . . . . . 4
3. Interaction with the Autonomic Networking Infrastructure . . 5
3.1. Interaction with the security mechanisms . . . . . . . . 5
3.2. Interaction with the Autonomic Control Plane . . . . . . 5
3.3. Interaction with GRASP and its API . . . . . . . . . . . 6
3.4. Interaction with policy mechanism . . . . . . . . . . . . 7
4. Interaction with Non-Autonomic Components . . . . . . . . . . 7
5. Design of GRASP Objectives . . . . . . . . . . . . . . . . . 8
6. Life Cycle . . . . . . . . . . . . . . . . . . . . . . . . . 9
6.1. Installation phase . . . . . . . . . . . . . . . . . . . 9
6.1.1. Installation phase inputs and outputs . . . . . . . . 10
6.2. Instantiation phase . . . . . . . . . . . . . . . . . . . 11
6.2.1. Operator's goal . . . . . . . . . . . . . . . . . . . 11
6.2.2. Instantiation phase inputs and outputs . . . . . . . 12
6.2.3. Instantiation phase requirements . . . . . . . . . . 12
6.3. Operation phase . . . . . . . . . . . . . . . . . . . . . 13
7. Coordination between Autonomic Functions . . . . . . . . . . 14
8. Coordination with Traditional Management Functions . . . . . 14
9. Robustness . . . . . . . . . . . . . . . . . . . . . . . . . 14
10. Security Considerations . . . . . . . . . . . . . . . . . . . 15
11. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 16
12. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . 16
13. References . . . . . . . . . . . . . . . . . . . . . . . . . 16
13.1. Normative References . . . . . . . . . . . . . . . . . . 16
13.2. Informative References . . . . . . . . . . . . . . . . . 17
Appendix A. Change log [RFC Editor: Please remove] . . . . . . . 19
Appendix B. Example Logic Flows . . . . . . . . . . . . . . . . 20
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 25
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 [I-D.ietf-anima-reference-model]. This
infrastructure makes use of the Autonomic Control Plane (ACP)
[I-D.ietf-anima-autonomic-control-plane] and the Generic Autonomic
Signaling Protocol (GRASP) [I-D.ietf-anima-grasp]. This document is
a contribution to the description of an autonomic ecosystem,
recognizing that a deployable autonomic network needs more than just
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ACP and GRASP implementations. It must achieve management goals that
a Network Operations Center (NOC) cannot achieve manually, including
at least a library of ASAs and corresponding GRASP objective
definitions. 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. 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.
The reference model [I-D.ietf-anima-reference-model] expands this by
adding that 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
[I-D.ietf-anima-grasp] 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. This will require either
a multi-threaded implementation, or a logically equivalent event loop
structure. It may therefore be a quite complex piece of software in
its own right, forming part of the application layer above the ANI."
There will certainly be very simple ASAs that manage a single
objective in a straightforward way and do not need asynchronous
operations. In such a case, many aspects of the current document do
not apply. However, in general a basic property of an ASA is that it
is a relatively complex software component that will in many cases
control and monitor simpler entities in the same host or elsewhere.
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 such
ASAs.
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2. Logical Structure of an Autonomic Service Agent
As mentioned above, all but the simplest ASAs will need to suport
asynchronous operations. Not all programming environments explicitly
support multi-threading. In that case, an 'event loop' style of
implementation should be adopted, in which case each thread would be
implemented as an event handler called in turn by the main loop. For
this, the GRASP API (Section 3.3) must provide non-blocking calls.
If necessary, the GRASP session identifier will be used to
distinguish simultaneous operations.
A typical ASA will have a main thread that performs various initial
housekeeping actions such as:
* Obtain authorization credentials.
* 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 will be launched, or events added to the
event loop. Examples 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 or events should all either exit after their job is
done, or enter a wait state for new work, to avoid blocking others
unnecessarily.
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According to the degree of parallelism needed by the application,
some of these threads or events might be launched in multiple
instances. In particular, if negotiation sessions with other ASAs
are expected to 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, such as including an arbitrary wait time in each cycle
of the main loop.
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 B 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 in accordance with
[I-D.ietf-anima-bootstrapping-keyinfra]. 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 users 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 [I-D.ietf-anima-grasp] is expected to run as a separate process
with its API [I-D.ietf-anima-grasp-api] 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 CBOR [RFC7049], which is no
restriction at all in practice.
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.
* 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.
* 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
[I-D.ietf-anima-grasp-api].
This 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. 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, either the ACP or in special cases
the autonomic key infrastructure will be used to secure such
communications.
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3.4. Interaction with policy mechanism
At the time of writing, the policy (or "Intent") mechanism for the
ANI is undefined and is regarded as a research topic. It is expected
to operate by an information distribution mechanism (e.g.
[I-D.liu-anima-grasp-distribution]) 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 directly with the NETCONF server in the same
node. This is stating the obvious, and the details are specific to
each case, but it has an important security implication. The ASA
might act as a loophole by which the managed entity could penetrate
the security boundary of the ANI. The ASA must be designed to avoid
such loopholes, and should if possible operate in an unprivileged
mode.
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.
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5. Design of GRASP Objectives
The general rules for the format of GRASP Objective options, their
names, and IANA registration are given in [I-D.ietf-anima-grasp].
Additionally that document discusses various general considerations
for the design of objectives, which are not repeated here. However,
we emphasize that the GRASP protocol does not provide transactional
integrity. In other words, if an ASA is capable of overlapping
several negotiations for a given objective, then the ASA itself must
use suitable locking techniques to avoid interference between these
negotiations. For example, 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. This might impact the design of the
objective as well as the logic flow of the ASA.
In particular, 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) [RFC7049]. For some
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.
Nothing prevents using other formats such as JSON, but this requires
the ASA to be capable of parsing and generating JSON. The formats
acceptable by the GRASP API will limit the options in practice. A
fallback 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.
Note that 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.
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6. Life Cycle
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, a more likely situation is that ASAs need to be
installed or updated dynamically, because of new requirements or
bugs. 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.
+--------------+
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
Before being able to instantiate and run ASAs, the operator must
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 ASA classes in a set of Installation Hosts.
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.
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The decoupling property allows controlling resources of a NE from a
remote ASA, i.e. an ASA installed on a host machine different from
the resources' NE.
The multiplicity property allows controlling multiple sets of
resources from a single ASA.
These three properties are very important in the context of the
installation phase as their variations condition how the ASA class
could be installed on the infrastructure.
6.1.1. Installation phase inputs and outputs
Inputs are:
[ASA class of type_x] that specifies which classes ASAs to install,
[Installation_target_Infrastructure] that specifies the candidate
Installation Hosts,
[ASA class placement function, e.g. under which criteria/
constraints as defined by the operator] that specifies how the
installation phase shall meet the operator's needs and objectives
for the provision of the infrastructure. In the coupled mode, the
placement function is not necessary, whereas in the decoupled
mode, the placement function is mandatory, even though it can be
as simple as an explicit list of Installation hosts.
The main output of the installation phase is an up-to-date directory
of installed ASAs which corresponds to [list of ASA classes]
installed on [list of installation Hosts]. This output is also
useful for the coordination function and corresponds to the static
interaction map (see next section).
The condition to validate in order to pass to next phase is to ensure
that [list of ASA classes] are well installed on [list of
installation Hosts]. The state of the ASA at the end of the
installation phase is: installed. (not instantiated). The following
commands or messages are foreseen: install(list of ASA classes,
Installation_target_Infrastructure, ASA class placement function),
and un-install (list of ASA classes).
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6.2. Instantiation phase
Once the ASAs are installed on the appropriate hosts in the network,
these ASA 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 coupled
case, determining which resources are controlled by an ASA is
straightforward (the determination is embedded), in a decoupled mode
determining this is a bit more complex (hence a starting agent will
have to either discover or be taught it).
The instantiation phase of an ASA covers both these aspects: starting
the agent piece of code (when this does not start automatically) and
determining which resources have to be controlled (when this is not
obvious).
6.2.1. Operator's goal
Through this phase, the operator wants to control its autonomic
network in two things:
1 determine the scope of autonomic functions by instructing which of
the network resources have to be managed by which autonomic
function (and more precisely which class e.g. 1. version X or
version Y or 2. provider A or provider B),
2 determine how the autonomic functions are organized by instructing
which ASAs have to interact with which other ASAs (or more
precisely which set of network resources have to be handled as an
autonomous group by their managing ASAs).
Additionally in this phase, the operator may want to set objectives
to autonomic functions, by configuring the ASAs technical objectives.
The operator's goal can be summarized in an instruction to the ANIMA
ecosystem matching the following pattern:
[ASA of type_x instances] ready to control
[Instantiation_target_Infrastructure] with
[Instantiation_target_parameters]
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6.2.2. Instantiation phase inputs and outputs
Inputs are:
[ASA of type_x instances] that specifies which are the ASAs to be
targeted (and more precisely which class e.g. 1. version X or
version Y or 2. provider A or provider B),
[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 technology segment
or even a specific list of resources,
[Instantiation_target_parameters] that specifies which are the
technical objectives to be set 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 4.2 could be either:
sent to a targeted ASA In which 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 which case, the ASAs would collectively
determine from the list which Agent(s) would handle which
[Instantiation_target_Infrastructure], with the
[Instantiation_target_parameters].
This set of instructions can be materialized through a message that
is named an Instance Mandate (description TBD).
The conclusion of this instantiation phase is a ready to operate ASA
(or interacting set of ASAs), then this (or those) ASA(s) can
describe themselves by depicting which are the resources they manage
and what this means in terms of metrics being monitored and in terms
of actions that can be executed (like modifying the parameters
values). A message conveying such a self description is named an
Instance Manifest (description TBD).
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Though the operator may well use such a self-description "per se",
the final goal of such a description is to be shared with other ANIMA
entities like:
* the coordination entities (see [I-D.ciavaglia-anima-coordination])
* collaborative entities in the purpose of establishing knowledge
exchanges (some ASAs may produce knowledge or even monitor metrics
that other ASAs cannot make by themselves why those would be
useful for their execution)
6.3. Operation phase
Note: This section is to be further developed in future revisions of
the document, especially the implications on the design of ASAs.
During the Operation phase, the operator can:
Activate/Deactivate ASA: meaning enabling those to execute their
autonomic loop or not.
Modify ASAs targets: meaning setting them different objectives.
Modify ASAs managed resources: by updating the instance mandate
which would specify different set of resources to manage (only
applicable to decouples ASAs).
During the Operation phase, running ASAs can interact the one with
the other:
in order to exchange knowledge (e.g. an ASA providing traffic
predictions to load balancing ASA)
in order to collaboratively reach an objective (e.g. ASAs
pertaining to the same autonomic function targeted to manage a
network domain, these ASA will collaborate - in the case of a load
balancing one, by modifying the links metrics according to the
neighboring resources loads)
During the Operation phase, running ASAs are expected to apply
coordination schemes
then execute their control loop under coordination supervision/
instructions
The ASA life-cycle is discussed in more detail in "A Day in the Life
of an Autonomic Function" [I-D.peloso-anima-autonomic-function].
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7. 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 "Autonomic Functions
Coordination" [I-D.ciavaglia-anima-coordination].
8. 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, RESTCONF and YANG-based
solutions. 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, [I-D.ietf-anima-prefix-management] 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.
A related aspect is that management functions often include a 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 above, YANG
serialized as CBOR may be used directly as the value of a GRASP
objective.
9. Robustness
It is of great importance that all components of an autonomic system
are highly robust. In principle they must never fail. 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 hard 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.
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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.
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. 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. 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.
9. 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).
10. Security Considerations
ASAs are intended to run in an environment that is protected by the
Autonomic Control Plane [I-D.ietf-anima-autonomic-control-plane],
admission to which depends on an initial secure bootstrap process
[I-D.ietf-anima-bootstrapping-keyinfra]. In some deployments, a
secure partition of the link layer might be used instead
[I-D.carpenter-anima-l2acp-scenarios]. However, this does not
relieve ASAs of responsibility for security. In particular, when
ASAs configure or manage network elements outside the ACP, they must
use secure techniques and carefully validate any incoming
information. As noted above, this will apply in particular when an
ASA interacts with a management component such as a NETCONF server.
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As appropriate to their specific functions, ASAs should take account
of relevant privacy considerations [RFC6973].
Authorization of ASAs is a subject for future study. At present,
ASAs are trusted by virtue of being installed on a node that has
successfully joined the ACP. In the general case, a node may have
mutltiple roles and a role may use multiple ASAs, each using multiple
GRASP objectives. Additional mechanisms for the authorization of
nodes and ASAs to manipulate specific GRASP objectives could be
designed.
11. IANA Considerations
This document makes no request of the IANA.
12. Acknowledgements
Useful comments were received from Michael Behringer Toerless Eckert,
Alex Galis, Bing Liu, Michael Richardson, and other members of the
ANIMA WG.
13. References
13.1. Normative References
[I-D.ietf-anima-autonomic-control-plane]
Eckert, T., Behringer, M., and S. Bjarnason, "An Autonomic
Control Plane (ACP)", Work in Progress, Internet-Draft,
draft-ietf-anima-autonomic-control-plane-27, 2 July 2020,
<https://tools.ietf.org/html/draft-ietf-anima-autonomic-
control-plane-27>.
[I-D.ietf-anima-bootstrapping-keyinfra]
Pritikin, M., Richardson, M., Eckert, T., Behringer, M.,
and K. Watsen, "Bootstrapping Remote Secure Key
Infrastructures (BRSKI)", Work in Progress, Internet-
Draft, draft-ietf-anima-bootstrapping-keyinfra-41, 8 April
2020, <https://tools.ietf.org/html/draft-ietf-anima-
bootstrapping-keyinfra-41>.
[I-D.ietf-anima-grasp]
Bormann, C., Carpenter, B., and B. Liu, "A Generic
Autonomic Signaling Protocol (GRASP)", Work in Progress,
Internet-Draft, draft-ietf-anima-grasp-15, 13 July 2017,
<https://tools.ietf.org/html/draft-ietf-anima-grasp-15>.
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[RFC7049] Bormann, C. and P. Hoffman, "Concise Binary Object
Representation (CBOR)", RFC 7049, DOI 10.17487/RFC7049,
October 2013, <https://www.rfc-editor.org/info/rfc7049>.
13.2. 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.carpenter-anima-l2acp-scenarios]
Carpenter, B. and B. Liu, "Scenarios and Requirements for
Layer 2 Autonomic Control Planes", Work in Progress,
Internet-Draft, draft-carpenter-anima-l2acp-scenarios-02,
8 April 2020, <https://tools.ietf.org/html/draft-
carpenter-anima-l2acp-scenarios-02>.
[I-D.ciavaglia-anima-coordination]
Ciavaglia, L. and P. Peloso, "Autonomic Functions
Coordination", Work in Progress, Internet-Draft, draft-
ciavaglia-anima-coordination-01, 21 March 2016,
<https://tools.ietf.org/html/draft-ciavaglia-anima-
coordination-01>.
[I-D.ietf-anima-grasp-api]
Carpenter, B., Liu, B., Wang, W., and X. Gong, "Generic
Autonomic Signaling Protocol Application Program Interface
(GRASP API)", Work in Progress, Internet-Draft, draft-
ietf-anima-grasp-api-06, 12 June 2020,
<https://tools.ietf.org/html/draft-ietf-anima-grasp-api-
06>.
[I-D.ietf-anima-prefix-management]
Jiang, S., Du, Z., Carpenter, B., and Q. Sun, "Autonomic
IPv6 Edge Prefix Management in Large-scale Networks", Work
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in Progress, Internet-Draft, draft-ietf-anima-prefix-
management-07, 18 December 2017,
<https://tools.ietf.org/html/draft-ietf-anima-prefix-
management-07>.
[I-D.ietf-anima-reference-model]
Behringer, M., Carpenter, B., Eckert, T., Ciavaglia, L.,
and J. Nobre, "A Reference Model for Autonomic
Networking", Work in Progress, Internet-Draft, draft-ietf-
anima-reference-model-10, 22 November 2018,
<https://tools.ietf.org/html/draft-ietf-anima-reference-
model-10>.
[I-D.ietf-core-yang-cbor]
Veillette, M., Petrov, I., and A. Pelov, "CBOR Encoding of
Data Modeled with YANG", Work in Progress, Internet-Draft,
draft-ietf-core-yang-cbor-13, 4 July 2020,
<https://tools.ietf.org/html/draft-ietf-core-yang-cbor-
13>.
[I-D.liu-anima-grasp-distribution]
Liu, B., Xiao, X., Hecker, A., Jiang, S., and Z.
Despotovic, "Information Distribution in Autonomic
Networking", Work in Progress, Internet-Draft, draft-liu-
anima-grasp-distribution-13, 12 December 2019,
<https://tools.ietf.org/html/draft-liu-anima-grasp-
distribution-13>.
[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://tools.ietf.org/html/draft-peloso-anima-autonomic-
function-01>.
[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>.
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[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>.
Appendix A. Change log [RFC Editor: Please remove]
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:
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* 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.
* 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. Example Logic Flows
This appendix describes generic logic flows for 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
[I-D.ietf-anima-grasp] and its conceptual API
[I-D.ietf-anima-grasp-api].
A complete autonomic function for a resource would 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
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concerned. One example is IP address prefix management, as specified
in [I-D.ietf-anima-prefix-management]. In this case, an instance of
the ASA would 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.
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.
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 expires.
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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 consumers routers.
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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<CODE BEGINS>
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
do forever:
good_peer = none
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 M_REQ_NEG
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
else:
Send M_END + O_DECLINE #negotiation failed
sleep() #sleep time depends on application scenario
MAIN_NEGOTIATOR thread:
do forever:
grasp.listen_negotiate("EX1.Resource")
i.e., wait for M_REQ_NEG
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
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
Record in delegated_list
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() #sleep time depends on application scenario
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GARBAGE_COLLECTOR thread:
do forever:
Search resource_pool for adjacent resources
Merge adjacent resources
sleep() #sleep time depends on application scenario
<CODE ENDS>
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
Nokia
Villarceaux
91460 Nozay
France
Email: laurent.ciavaglia@nokia.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
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Email: pierre.peloso@nokia.com
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