Internet DRAFT - draft-pentikousis-nmrg-andr
draft-pentikousis-nmrg-andr
NMRG K. Pentikousis
Internet-Draft EICT
Intended status: Informational M. Sifalakis
Expires: November 5, 2015 University of Basel
J. Nobre
Federal University of Rio Grande do Sul
May 4, 2015
Autonomic Networking Definitions Revisited
draft-pentikousis-nmrg-andr-02
Abstract
This document revisits the autonomic networking terminology
established in peer-reviewed literature, aiming to contribute to the
ongoing discussion in the IRTF NMRG about how to move forward with
standardizing various autonomic networking aspects.
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 2
1.1. Motivation . . . . . . . . . . . . . . . . . . . . . . . 2
1.2. Scope . . . . . . . . . . . . . . . . . . . . . . . . . . 3
2. Definitions . . . . . . . . . . . . . . . . . . . . . . . . . 3
3. Operational Considerations and Outlook . . . . . . . . . . . 5
3.1. New Deployment Models . . . . . . . . . . . . . . . . . . 6
3.2. Programmable Network Elements and Functions . . . . . . . 6
3.3. Autonomic Planes . . . . . . . . . . . . . . . . . . . . 6
3.4. DevOps . . . . . . . . . . . . . . . . . . . . . . . . . 7
3.5. Autonomic Monitoring . . . . . . . . . . . . . . . . . . 7
4. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . 8
5. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 9
6. Security Considerations . . . . . . . . . . . . . . . . . . . 9
7. Informative References . . . . . . . . . . . . . . . . . . . 9
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 12
1. Introduction
The IRTF Network Management Research Group (NMRG) has been working on
a set of definitions for autonomic networking. Defining and agreeing
on autonomic networking terminology is not an easy task as discussed
in [TAN]. In general, autonomic operation is associated with a range
of properties, such as self-configuration, self-healing, self-
optimization, and self-protection [ACDawn]. It is worth pointing out
that although there is some implicit consensus within the autonomic
computing community on the key properties/attributes of an autonomic
system, in the autonomic networking community this is not necessarily
the case. In the past, the common ground between different projects
and different contexts of operation was the presence of self-*
properties, without converging to a minimum set or different levels
of autonomic behavior, or where this behavior needs to be manifested.
1.1. Motivation
Behringer et al. [I-D.irtf-nmrg-autonomic-network-definitions]
describe a set of design goals and non-goals for autonomic networking
and introduce a model reference architecture in the context of future
IETF standardization [I-D.behringer-autonomic-control-plane].
Prior to this effort at NMRG, autonomic networking has been the focus
of several research projects. For example, Bouabene et al. [ANA]
detail an autonomic network architecture (ANA). Nguengang et al.
[UMFSpec] propose a unified management framework (UMF) which has
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autonomic properties and functions at its core. Chaparadza et al.
[SelfFI] introduce an elegant and "standardizable" [sic] generic
autonomic networking architecture (GANA) which they propose to be
adopted as a reference model. GANA was indeed further elaborated
under the auspices of ETSI as a group specification [GANA].
Jennings et al. [TAM07] discuss the challenges one must deal with
when applying autonomic principles to network management. This
includes translation from business rules to resources/services to be
provided, contextual changes in the network, adaptation of the
management control loops, and verification of dynamic models for
machine learning purposes. Samaan and Karmouch [SK09] analyze the
requirements and the main contributions for the building blocks of
autonomic network management systems, describe a classification
methodology which compares previously proposed architectures, suggest
a reference framework, and point to a set of research challenges.
This list of earlier work in only indicative of the breadth of
research in this area over the last decade. However, standardization
remains an open question and deployment has been limited to specific
mechanisms only [I-D.irtf-nmrg-an-gap-analysis].
1.2. Scope
We concur with Behringer et al.
[I-D.irtf-nmrg-autonomic-network-definitions] that for most of the
work in IETF it suffices to define autonomic behaviour at the node
level. However, recent standardization efforts in the IETF, such as,
for example, I2RS [I-D.ietf-i2rs-problem-statement], SFC [RFC7498],
ABNO [RFC7491], SUPA [I-D.pentikousis-supa-mapping], and LIME to name
a few, and new IRTF research groups such as SDNRG and NFVRG, indicate
that NMRG should perhaps dig a bit deeper into the definitions for
autonomic networking that will be of tangible benefit to the
researcher and practitioner communities alike. In particular, one
could reconsider the aspects of defining node-level autonomicity
only.
This document revisits the autonomic networking definitions proposed
earlier in the peer-reviewed literature Section 2, and relates them
with recent developments aiming to assist in the definition of a
coherent terminology in this emerging area of standardization at the
IETF.
2. Definitions
After some thorough analysis and discussion, Schmid et al. [TAN] put
forward the following definition, which captures in a concrete and
concise manner the essence of autonomicity:
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An Autonomic System is a system that operates and serves its
purpose by managing its own self without external intervention
even in case of environmental changes.
Note that the authors explicitly define autonomicity at the system
level, not at the node level. They go on to list the minimum set of
properties that an autonomic system should possess. Namely, an
autonomic system is
o automatic, i.e. it can "self-control its internal functions and
operations"
o adaptive, i.e. it can change its "configuration, state and
functions", and
o aware, i.e. it can "monitor its operational context".
In principle, an autonomic system could wholly replaces a non-
autonomic one. In practice, however, real-world deployments will
include legacy network elements and services as well as new autonomic
ones.
A salient paper in the autonomic networking area is [FOCALE], in
which Strassner et al. lay the foundation for an autonomic network
architecture. We will not delve into the details of FOCALE, but we
do note that the authors define three types of managed components
according to their autonomic capabilities. In the remainder of this
document we consider that FOCALE "components" equate to network
resources as defined in [RFC7426], i.e. each network resource is a
"physical or virtual component available within a system", and expand
these definitions further.
In this sense, legacy equipment can be seen as autonomically unaware
resources, and can only be managed using traditional mechanisms. In
practice, field equipment could be upgraded to support certain
autonomic features, thus becoming autonomically-aware managed network
resources. This type of network element would typically require a
mediation layer as suggested in [FOCALE] or at the very least certain
system software updates. Finally, a deployment could include fully
autonomically-enabled network resources. FOCALE explicitly aims to
"accommodate legacy components" and foresees the deployment of an
autonomic manager "that orchestrates the behaviour of other autonomic
components in the system."
Figure 1 illustrates a simple sketch of an autonomic networking
control loop, based on Fig. 2 of [FOCALE]. In short, an autonomic
manager gathers data from the managed resource(s), evaluates the
current state, compares it with the desired one, and configures the
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managed resource as necessary. As illustrated, this simple system
possess the minimum set of properties introduced above.
+---------------------+
(Maintenance Loop) | Actual vs. desired | Autonomic manager
+-------------->| state evaluation |
| | and decision making |
| +---------o-----------+
v |
+----------------+ | New configuration
| Data gathering | | (Adjustment Loop)
+----------------+ |
^ v
| +------------------+
+----------------o Managed resource |
+------------------+
Figure 1: Simple sketch of an autonomic networking control loop
All three types of network resources (i.e. autonomically-unaware,
autonomically-aware, and autonomically-enabled) need to be managed.
One viable approach is proposed by Nguengang et al. [UMFSpec] who
describe an architecture based on the definition of two types of
management systems depending on the capacity of the underlying nodes,
namely an Enhanced Legacy Management System (ELMS) or a future
management system. In this context, it is worth considering the
approaches taken in other disciplines. For example, in aviation,
auto-navigation systems solve this challenge by means of distributed
consensus among an odd-number of controllers/managers that
independently carry out the tasks of data gathering and state
evaluation, and then make an election for each decision. On the
other hand, biologically-inspired systems have emergent coordination
(of managers) following principles such as entropy or mass action.
Finally, autonomic properties are highly desirable in the context of
new mobile architectures. For example, Barth and Kuehn [SON4G]
discuss the need for self-* properties in the context of small cell
deployments in 3GPP 4G/LTE, while Hamalainen et al. [LTESON] provide
a comprehensive guide and handy references to the efforts in 3GPP
along these lines.
3. Operational Considerations and Outlook
This section briefly describes emerging operational considerations
that in the authors' view should be taken into account as we move
forward with autonomic networking standardization in the IETF and
IRTF context.
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3.1. New Deployment Models
Strassner et al. [FOCALE] highlight that an important goal of
autonomics is "making the life of the user easier by changing the
focus from a computer-centric to a task-centric model". Deployment
of new network technologies is typically a time-consuming, labour-
intensive and cumbersome task. In the past, we have seen that if the
newly designed infrastructure cannot be managed satisfactorily,
adverse results such as service launch delays may be inevitable. As
we move forward with new deployment models which are oriented towards
softwarized and cloudified network functions, autonomic networking
principles may prove invaluable.
As per [TAN], autonomic systems are by design programmable, which
bodes well with the emerging deployment models which emphasize
agility and shorter technology introduction cycles. We argue that
autonomic networking definitions, goals and gap analysis within the
context of IETF standardization should take this more into
consideration. Further, recent initiatives such as SUPA
[I-D.pentikousis-supa-mapping] point towards infrastructures which
are managed through intent (generic policies), for instance, as
opposed to network element specific configuration.
3.2. Programmable Network Elements and Functions
Although the development of models such as FoRCES [RFC5812] coincided
with the core of the above-mentioned autonomic networking research
literature, by and large, the two areas did not cross-pollinate. It
appears that as SDN and NFV principles reach a wider audience of
researchers and practitioners, fully programmable network elements
and functions could be further introduced in autonomic networking
architectures. Indeed, moving towards a "task-centric model" relates
well with other efforts in IETF such as SFC [RFC7498]
3.3. Autonomic Planes
Recent work at the SDNRG [RFC7426] highlighted the need for the wider
SDN community to think in terms of control, management, and
operational planes comprehensiveness and complementarity. As we have
seen above, earlier work in autonomic networking has been primarily
focusing on management aspects (cf. [UMFSpec]), while recent work in
NMRG is focusing on standardizing an autonomic networking control
plane [I-D.behringer-autonomic-control-plane].
For an autonomic plane, there is the challenge on "which
functionality to place where". For example, one could consider an
architecture in which all three planes have autonomic features.
Alternatively, one could adopt a knowledge plane approach [KP2003]
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establishing a separate, virtual/logical plane. A way forward could
be to consider autonomics in NMRG in the context of programmable
networks and through a more comprehensive manner.
3.4. DevOps
John et al. [NSC] elaborate on the concept of continuous network
service delivery. In this context, the authors argue for the need of
programmable observation points which could be inserted in a dynamic
service chain on demand. They expect that future service provider
DevOps would require new management technologies "based on the
experience from data centers" thus "addressing the challenges of
dynamic service chaining". This bodes well with the model
illustrated in Figure 1 and we could expect more results in this
direction in the future.
3.5. Autonomic Monitoring
Network monitoring is related to the mechanisms employed to perform
measurements and collect the respective results. These mechanisms
are some of the most important tools employed by network
administrators. Monitoring results encompass metrics such as delay
(one-way or round-trip), jitter, throughput, packet loss, protocol/
application usage, among others. Results can be used in different
contexts, such as pre-deployment validation and measurement of in-
band live network performance characteristics, and by several
applications, such as intrusion detection and lawful interception.
Traditional (i.e., non-autonomic) monitoring mechanisms usually rely
on the predetermined production of measurements results. Thus, such
mechanisms are not able to dynamically adapt to different operational
conditions during runtime. On the other hand, autonomic monitoring
mechanisms are able to adjust themselves in order to optimize their
operation. This can be done using several techniques, such as
reinforcement learning and neural networks.
Several classifications have been proposed regarding autonomic
monitoring. Samaan and Karmouch [SK09] discuss a classification
methodology for autonomic monitoring methods in the context of an
analysis of current and future research directions of autonomic
network management. The authors provide a classification of
autonomic monitoring approaches considering the following classes:
active versus passive monitoring and distributed versus centralized
monitoring. The authors also comment on monitoring granularity
(measurements can be performed at the byte-, packet-, flow- or
aggregated-traffic levels); monitoring timing (fixed time, event-
based, and on-demand); and monitoring programmability (levels on what
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the monitoring mechanism itself can dynamically modify with respect
to its operation).
In the following we provide a set of literature pointers to
monitoring systems which exhibit autonomic features. Note that such
mechanisms exhibit different levels of autonomic monitoring
functionality and employ different techniques to support this
functionality.
Massie et al. [MCC04] proposed Ganglia, a scalable, distributed
system monitor tool for high-performance computing systems such as
clusters and grids. This system is based on a hierarchical design
targeted at federations of clusters and it relies on a multicast-
based listen/announce protocol to monitor state within network nodes.
Using a set of programmable interfaces, Ganglia follows a passive
distributed monitoring approach where monitoring programmability is
left to the applications.
Song et al. [SQZ06] proposed NetQuest, a centralized monitoring
control of active measurement mechanisms with self-programmability
features. NetQuest models the selection of monitoring
functionalities and uses Bayesian experimental design concepts to
define the solution parameters.
Duarte et al. [DNGT11] proposed ManP2P-ng, a system focused in
materializing distributed self-healing features through the use of
P2P management overlays and high-level descriptions called workplans.
Workplans are used to set up the self-healing parameters regarding
managed devices and management peers. The self-healing service is
composed of independent monitoring and healing services.
Sekar et al. [SRWZKA08] proposed CSAMP, a centralized optimization
engine for system-wide flow monitoring. The main features of CSAMP
are the use of traffic information to steer flow sampling and hash-
based packet selection through a centralized engine for the
distribution of measurement responsibilities across routers.
Pietro et al. [PHCN10] proposed DECON, a decentralized coordination
system aimed at assigning passive monitoring probes. DECON uses
traffic information from probes seeing a particular ow to decide
which one shoud do the actual monitoring. After that, messages are
sent back to probes communicating the decision.
4. Acknowledgements
This document would not have been possible without the stimulating
discussion during the NMRG meeting at IETF 90 in Toronto. Many
thanks to all participants.
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5. IANA Considerations
This memo includes no request to IANA.
6. Security Considerations
This document does not propose a new network architecture or protocol
and as such does not have any impact on the security of the Internet.
Autonomic networking introduces a range of opportunities for formal
verification techniques which could increase trustworthiness,
although this is clearly beyond the scope of this first version of
this document. Interested readers should consult [ACSec] for an
early exploration of the issues at hand in the context of autonomic
computing.
7. Informative References
[ACDawn] Ganek, A. G., and T. A. Corbi, "The dawning of the
autonomic computing era", IBM systems Journal, 42(1), 5-18
, 2003.
[ACSec] Chess, D. M., Palmer, C. C., and S. R. White, "Security in
an autonomic computing environment", IBM systems Journal,
42(1), 107-118 , 2003.
[ANA] Bouabene, G., Jelger, C., Tschudin, C., Schmid, S.,
Keller, A., and M. May, "The autonomic network
architecture (ANA)", Journal on Selected Areas in
Communications, 28(1), 4-14 IEEE, 2003.
[DNGT11] Duarte, P. A. P. R., Nobre, J. C., Granville, L. Z.,
Tarouco, L. M. R., "A P2P-Based Self-Healing Service for
Network Maintenance", Proceedings of the 12th IFIP/IEEE
International Symposium on Integrated Network Management
(IM) IEEE, 2011.
[FOCALE] Strassner, J., Agoulmine, N., and E. Lehtihet, "FOCALE: A
novel autonomic networking architecture", Proc. Latin
American Autonomic Computing Symposium (LAACS), Campo
Grande, Brazil, July 2006.
[GANA] 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.
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[I-D.behringer-autonomic-control-plane]
Behringer, M., Bjarnason, S., BL, B., and T. Eckert, "An
Autonomic Control Plane", draft-behringer-autonomic-
control-plane-00 (work in progress), June 2014.
[I-D.ietf-i2rs-problem-statement]
Atlas, A., Nadeau, T., and D. Ward, "Interface to the
Routing System Problem Statement", draft-ietf-i2rs-
problem-statement-06 (work in progress), January 2015.
[I-D.irtf-nmrg-an-gap-analysis]
Jiang, S., Carpenter, B., and M. Behringer, "General Gap
Analysis for Autonomic Networking", draft-irtf-nmrg-an-
gap-analysis-05 (work in progress), March 2015.
[I-D.irtf-nmrg-autonomic-network-definitions]
Behringer, M., Pritikin, M., Bjarnason, S., Clemm, A.,
Carpenter, B., Jiang, S., and L. Ciavaglia, "Autonomic
Networking - Definitions and Design Goals", draft-irtf-
nmrg-autonomic-network-definitions-07 (work in progress),
March 2015.
[I-D.pentikousis-supa-mapping]
Pentikousis, K. and D. Zhang, "Simplified Use of Policy
Abstractions (SUPA): Configuration and Policy Mapping",
draft-pentikousis-supa-mapping-04 (work in progress),
March 2015.
[KP2003] Clark, D. D., Partridge, C. , et al., "A Knowledge Plane
for the Internet", Proc. SIGCOMM, Karlsruhe, Germany ACM,
August 2003.
[LTESON] Hamalainen, S., Sanneck, H., and C. Sartori, "LTE Self-
Organising Networks (SON): Network Management Automation
for Operational Efficiency", John Wiley & Sons , 2012.
[MCC04] Massie, M.L. and Chun, B.N. and Culler, D.E., "The ganglia
distributed monitoring system: design, implementation, and
experience", Parallel Computing, vol. 30, no. 7, pp.
817-840 Elsevier, 2004.
[NSC] John, W., Pentikousis, K., et al., "Research directions in
network service chaining", Proc. SDN for Future Networks
and Services (SDN4FNS), Trento, Italy IEEE, November 2013.
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[PHCN10] di Pietro, A. and Huici, F. and Costantini, D. and
Niccolini, S., "DECON: Decentralized Coordination for
Large-Scale Flow Monitoring", Proceedings of the IEEE
Conference on Computer Communications (INFOCOM) Workshops
IEEE, 2010.
[RFC5812] Halpern, J. and J. Hadi Salim, "Forwarding and Control
Element Separation (ForCES) Forwarding Element Model", RFC
5812, March 2010.
[RFC7426] Haleplidis, E., Pentikousis, K., Denazis, S., Hadi Salim,
J., Meyer, D., and O. Koufopavlou, "Software-Defined
Networking (SDN): Layers and Architecture Terminology",
RFC 7426, January 2015.
[RFC7491] King, D. and A. Farrel, "A PCE-Based Architecture for
Application-Based Network Operations", RFC 7491, March
2015.
[RFC7498] Quinn, P. and T. Nadeau, "Problem Statement for Service
Function Chaining", RFC 7498, April 2015.
[SK09] Samaan, N. and A. Karmouch, "Towards Autonomic Network
Management: an Analysis of Current and Future Research
Directions", Communications Surveys & Tutorials, vol. 11,
no. 3, pp. 22-36 IEEE, 2009.
[SON4G] Barth, U., and E. Kuehn, "Self-organization in 4G mobile
networks: Motivation and vision", Proc. 7th International
Symposium on Wireless Communication Systems (ISWCS), York,
UK, pp. 731-735, IEEE, September 2010.
[SQZ06] Song, H. H., Qiu, L., Zhang, Y., "NetQuest: a flexible
framework for large-scale network measurement", ACM
SIGMETRICS Performance Evaluation Review, Vol. 34. No. 1.
ACM, 2006.
[SRWZKA08]
Sekar, V. and Reiter, M.K. and Willinger, W. and Zhang, H.
and Kompella, R.R. and Andersen, D. G., "CSAMP: a system
for network-wide flow monitoring", Proceedings of the 5th
USENIX Symposium on Networked Systems Design and
Implementation (NSDI) USENIX, 2008.
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[SelfFI] Chaparadza, R., Papavassiliou, S., et al., "Creating a
viable Evolution Path towards Self-Managing Future
Internet via a Standardizable Reference Model for
Autonomic Network Engineering", Future Internet Assembly
(pp. 136-147) IOS Press, 2009.
[TAM07] Jennings, B., van der Meer, s. et al., "Towards autonomic
management of communications networks", Communications
Magazine, vol. 45, no. 10, pp. 112-121 IEEE, 2007.
[TAN] Schmid, S., Sifalakis, M., and D. Hutchison, "Towards
autonomic networks", Proc. Autonomic Networking, LNCS
4195, pp. 1-11 Springer, 2006.
[UMFSpec] Nguengang, G. (ed.), et al., "UMF Specifications, Release
1", FP7-UNIVERSELF-Deliverable D2.1 , July 2011.
Authors' Addresses
Kostas Pentikousis
EICT GmbH
EUREF-Campus Haus 13
Torgauer Strasse 12-15
10829 Berlin
Germany
Email: k.pentikousis@eict.de
Manolis Sifalakis
University of Basel
Bernoullistrasse 16
4056 Basel
Switzerland
Email: sifalakis.manos@unibas.ch
Jeferson Campos Nobre
Federal University of Rio Grande do Sul
Institute of Informatics
Porto Alegre
Brazil
Email: jcnobre@inf.ufrgs.br
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