Guidelines for Autonomic Service Agents
draft-carpenter-anima-asa-guidelines-03
The information below is for an old version of the document.
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|---|---|---|---|
| Authors | Brian E. Carpenter , Laurent Ciavaglia , Sheng Jiang , Peloso Pierre | ||
| Last updated | 2017-10-25 | ||
| Replaced by | draft-ietf-anima-asa-guidelines, RFC 9222 | ||
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draft-carpenter-anima-asa-guidelines-03
Network Working Group B. Carpenter
Internet-Draft Univ. of Auckland
Intended status: Informational L. Ciavaglia
Expires: April 28, 2018 Nokia
S. Jiang
Huawei Technologies Co., Ltd
P. Peloso
Nokia
October 25, 2017
Guidelines for Autonomic Service Agents
draft-carpenter-anima-asa-guidelines-03
Abstract
This document proposes guidelines for the design of Autonomic Service
Agents for autonomic networks. It is based on the Autonomic Network
Infrastructure outlined in the ANIMA reference model, making use of
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.
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This Internet-Draft will expire on April 28, 2018.
Copyright Notice
Copyright (c) 2017 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
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carefully, as they describe your rights and restrictions with respect
to this document. Code Components extracted from this document must
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the Trust Legal Provisions and are provided without warranty as
described in the Simplified BSD License.
Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 2
2. Logical Structure of an Autonomic Service Agent . . . . . . . 3
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 . . . . . . . . . . . 5
3.4. Interaction with Intent mechanism . . . . . . . . . . . . 6
4. Design of GRASP Objectives . . . . . . . . . . . . . . . . . 6
5. Life Cycle . . . . . . . . . . . . . . . . . . . . . . . . . 7
5.1. Installation phase . . . . . . . . . . . . . . . . . . . 8
5.1.1. Installation phase inputs and outputs . . . . . . . . 9
5.2. Instantiation phase . . . . . . . . . . . . . . . . . . . 9
5.2.1. Operator's goal . . . . . . . . . . . . . . . . . . . 10
5.2.2. Instantiation phase inputs and outputs . . . . . . . 10
5.2.3. Instantiation phase requirements . . . . . . . . . . 11
5.3. Operation phase . . . . . . . . . . . . . . . . . . . . . 11
6. Coordination . . . . . . . . . . . . . . . . . . . . . . . . 12
7. Robustness . . . . . . . . . . . . . . . . . . . . . . . . . 12
8. Security Considerations . . . . . . . . . . . . . . . . . . . 13
9. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 14
10. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . 14
11. References . . . . . . . . . . . . . . . . . . . . . . . . . 14
11.1. Normative References . . . . . . . . . . . . . . . . . . 14
11.2. Informative References . . . . . . . . . . . . . . . . . 14
Appendix A. Change log [RFC Editor: Please remove] . . . . . . . 16
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 16
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].
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].
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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."
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
be multi-threaded so that it can 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."
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 ASAs.
2. Logical Structure of an Autonomic Service Agent
As mentioned above, all but the simplest ASAs will be multi-threaded
programs.
A typical ASA will have a main thread that performs various initial
housekeeping actions such as:
o Obtain authorization credentials.
o Register the ASA with GRASP.
o Acquire relevant policy Intent.
o Define data structures for relevant GRASP objectives.
o Register with GRASP those objectives that it will actively manage.
o Launch a self-monitoring thread.
o Enter its main loop.
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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. Examples of such threads
include:
o A background thread to repeatedly flood an objective to the AN, so
that any ASA can receive the objective's latest value.
o A thread to accept incoming synchronization requests for an
objective managed by this ASA.
o A thread to accept incoming negotiation requests for an objective
managed by this ASA, and then to conduct the resulting negotiation
with the counterpart ASA.
o A thread to 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 blocking other threads
unnecessarily.
Note: If the programming environment does not support multi-
threading, an 'event loop' style of implementation could be adopted,
in which case each of the above threads would be implemented as an
event handler called in turn by the main loop. In this case, the
GRASP API (Section 3.3) must provide non-blocking calls. If
necessary, the GRASP session identifier will be used to distinguish
simultaneous negotiations.
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
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 Intent 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
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self-monitoring thread should detect it, fix it if possible, and in
the worst case restart the entire ASA.
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 clients of the ACP.
It 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.
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.liu-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 4), 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 offers the following features:
o Registration functions, so that an ASA can register itself and the
objectives that it manages.
o A discovery function, by which an ASA can discover other ASAs
supporting a given objective.
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o 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.
o 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.
o 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.liu-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 as the value of a GRASP objective. As noted above, either the
ACP or in special cases the autonomic key infrastructure will be used
to secure such communications.
3.4. Interaction with Intent mechanism
At the time of writing, the Intent mechanism for the ANI is
undefined. It is expected to operate by an information distribution
mechanism 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 Intent, so every ASA implementation
must include carefully chosen default values and settings for all
parameters and choices that might depend on Intent.
4. 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
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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.
5. 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.
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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
5.1. 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.
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.
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5.1.1. 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).
5.2. 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).
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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).
5.2.1. 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]
5.2.2. 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:
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[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,
5.2.3. 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).
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:
o the coordination entities (see [I-D.ciavaglia-anima-coordination]
- Autonomic Functions Coordination)
o 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)
5.3. 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:
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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].
6. Coordination
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].
7. 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.
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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.
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. 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.
6. 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.
7. 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.
8. 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).
8. 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]. However, this does not
relieve ASAs of responsibility for security. In particular, when
ASAs configure or manage network elements outside the ACP, they must
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use secure techniques and carefully validate any incoming
information. 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.
9. IANA Considerations
This document makes no request of the IANA.
10. Acknowledgements
TBD.
11. References
11.1. Normative References
[I-D.ietf-anima-autonomic-control-plane]
Behringer, M., Eckert, T., and S. Bjarnason, "An Autonomic
Control Plane (ACP)", draft-ietf-anima-autonomic-control-
plane-12 (work in progress), October 2017.
[I-D.ietf-anima-bootstrapping-keyinfra]
Pritikin, M., Richardson, M., Behringer, M., Bjarnason,
S., and K. Watsen, "Bootstrapping Remote Secure Key
Infrastructures (BRSKI)", draft-ietf-anima-bootstrapping-
keyinfra-08 (work in progress), October 2017.
[I-D.ietf-anima-grasp]
Bormann, C., Carpenter, B., and B. Liu, "A Generic
Autonomic Signaling Protocol (GRASP)", draft-ietf-anima-
grasp-15 (work in progress), July 2017.
[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>.
11.2. 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.
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[GANA13] ETSI GS AFI 002, "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. and J. 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. Peloso, "Autonomic Functions
Coordination", draft-ciavaglia-anima-coordination-01 (work
in progress), March 2016.
[I-D.ietf-anima-reference-model]
Behringer, M., Carpenter, B., Eckert, T., Ciavaglia, L.,
Pierre, P., Liu, B., Nobre, J., and J. Strassner, "A
Reference Model for Autonomic Networking", draft-ietf-
anima-reference-model-05 (work in progress), October 2017.
[I-D.liu-anima-grasp-api]
Carpenter, B., Liu, B., Wang, W., and X. Gong, "Generic
Autonomic Signaling Protocol Application Program Interface
(GRASP API)", draft-liu-anima-grasp-api-05 (work in
progress), October 2017.
[I-D.peloso-anima-autonomic-function]
Pierre, P. and L. Ciavaglia, "A Day in the Life of an
Autonomic Function", draft-peloso-anima-autonomic-
function-01 (work in progress), March 2016.
[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.
[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>.
Carpenter, et al. Expires April 28, 2018 [Page 15]
Internet-Draft ASA Guidelines October 2017
[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>.
Appendix A. Change log [RFC Editor: Please remove]
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
Authors' Addresses
Brian Carpenter
Department of Computer Science
University of Auckland
PB 92019
Auckland 1142
New Zealand
Email: brian.e.carpenter@gmail.com
Carpenter, et al. Expires April 28, 2018 [Page 16]
Internet-Draft ASA Guidelines October 2017
Laurent Ciavaglia
Nokia
Villarceaux
Nozay 91460
FR
Email: laurent.ciavaglia@nokia.com
Sheng Jiang
Huawei Technologies Co., Ltd
Q14, Huawei Campus, No.156 Beiqing Road
Hai-Dian District, Beijing, 100095
P.R. China
Email: jiangsheng@huawei.com
Pierre Peloso
Nokia
Villarceaux
Nozay 91460
FR
Email: pierre.peloso@nokia.com
Carpenter, et al. Expires April 28, 2018 [Page 17]