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Autonomic Networking Use Case for Distributed Detection of SLA Violations
draft-irtf-nmrg-autonomic-sla-violation-detection-02

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This is an older version of an Internet-Draft that was ultimately published as RFC 8316.
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Authors Jéferson Campos Nobre , Lisandro Zambenedetti Granville , Alexander Clemm , Alberto Gonzalez Prieto
Last updated 2015-11-08 (Latest revision 2015-05-07)
RFC stream Internet Research Task Force (IRTF)
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draft-irtf-nmrg-autonomic-sla-violation-detection-02
Network Management Research Group                               J. Nobre
Internet-Draft                                              L. Granville
Intended status: Informational   Federal University of Rio Grande do Sul
Expires: November 8, 2015                                       A. Clemm
                                                               A. Prieto
                                                           Cisco Systems
                                                             May 7, 2015

     Autonomic Networking Use Case for Distributed Detection of SLA
                               Violations
          draft-irtf-nmrg-autonomic-sla-violation-detection-02

Abstract

   This document describes a use case for autonomic networking in
   distributed detection of Service Level Agreement (SLA) violations.
   It is one of a series of use cases intended to illustrate
   requirements for autonomic networking.

Status of This Memo

   This Internet-Draft is submitted in full conformance with the
   provisions of BCP 78 and BCP 79.

   Internet-Drafts are working documents of the Internet Engineering
   Task Force (IETF).  Note that other groups may also distribute
   working documents as Internet-Drafts.  The list of current Internet-
   Drafts is at http://datatracker.ietf.org/drafts/current/.

   Internet-Drafts are draft documents valid for a maximum of six months
   and may be updated, replaced, or obsoleted by other documents at any
   time.  It is inappropriate to use Internet-Drafts as reference
   material or to cite them other than as "work in progress."

   This Internet-Draft will expire on November 8, 2015.

Copyright Notice

   Copyright (c) 2015 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
   (http://trustee.ietf.org/license-info) in effect on the date of
   publication of this document.  Please review these documents
   carefully, as they describe your rights and restrictions with respect
   to this document.  Code Components extracted from this document must

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   include Simplified BSD License text as described in Section 4.e of
   the Trust Legal Provisions and are provided without warranty as
   described in the Simplified BSD License.

Table of Contents

   1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   2
   2.  Current Approaches  . . . . . . . . . . . . . . . . . . . . .   3
   3.  Problem Statement . . . . . . . . . . . . . . . . . . . . . .   4
   4.  Benefits of an Autonomic Solution . . . . . . . . . . . . . .   4
   5.  Intended User and Administrator Experience  . . . . . . . . .   5
   6.  Analysis of Parameters and Information Involved . . . . . . .   5
     6.1.  Device Based Self-Knowledge and Decisions . . . . . . . .   6
     6.2.  Interaction with other devices  . . . . . . . . . . . . .   6
   7.  Comparison with current solutions . . . . . . . . . . . . . .   6
   8.  Related IETF Work . . . . . . . . . . . . . . . . . . . . . .   6
   9.  Acknowledgements  . . . . . . . . . . . . . . . . . . . . . .   7
   10. IANA Considerations . . . . . . . . . . . . . . . . . . . . .   7
   11. Security Considerations . . . . . . . . . . . . . . . . . . .   7
   12. References  . . . . . . . . . . . . . . . . . . . . . . . . .   8
     12.1.  Normative References . . . . . . . . . . . . . . . . . .   8
     12.2.  Informative References . . . . . . . . . . . . . . . . .   8
   Authors' Addresses  . . . . . . . . . . . . . . . . . . . . . . .   9

1.  Introduction

   The Internet has been growing dramatically in terms of size and
   capacity, and accessibility in the last years.  Besides that, the
   communication requirements of distributed services and applications
   running on top of the Internet have become increasingly strict.  That
   is the case due to the impact of disrespecting such requirements
   (e.g., latency in trading can have a high cost).  Thus, those
   requirements are included in SLA specifications (examples of service
   fulfillment clauses can be found on [RFC7297]).  Violations on these
   requirements usually present significant financial loss, which can by
   divided in two types.  First, there is the loss incurred by the
   service users (e.g., the trader) and the loss incurred by the service
   provider in terms of penalties for not meeting the service.  Thus,
   the service level requirements of critical network services have
   become a key concern for network administrators.  To ensure that SLAs
   are not being violated, service levels need to be constantly
   monitored at the network infrastructure layer.  To that end, network
   measurements must take place.

   Network measurement mechanisms are performed through either active or
   passive measurement techniques.  In passive measurement, network
   conditions are checked in a non intrusive way because no monitoring
   traffic is created by the measurement process itself.  In the context

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   of IP Flow Information EXport (IPFIX) WG, several documents were
   produced to define passive measurement mechanisms (e.g., flow records
   specification [RFC3954]).  Active measurement, on the other hand, is
   intrusive because it injects synthetic traffic into the network to
   measure the network performance.  The IP Performance Metrics (IPPM)
   WG produced documents that describe active measurement mechanisms,
   such as: One-Way Active Measurement Protocol (OWAMP) [RFC4656], Two-
   Way Active Measurement Protocol (TWAMP) [RFC5357], and Cisco Service
   Level Assurance Protocol (SLA) [RFC6812].  Besides that, there are
   some mechanisms that do not fit into either active or passive
   categories, such as Performance and Diagnostic Metrics Destination
   Option (PDM) techniques [draft-elkins-ippm-pdm-option].

   Active measurement mechanisms usually offer better accuracy and
   privacy than passive measurement mechanisms.  Furthermore, active
   measurement mechanisms are able to detect end-to-end network
   performance problems in a fine-grained way (e.g., simulating the
   traffic that must be handled considering specific Service Level
   Objectives - SLOs).  As a result, active is preferred over passive
   measurement for SLA monitoring.  Measurement probes must be hosted in
   network devices and measurement sessions must be activated to compute
   the current network metrics (e.g., considering those described in
   [RFC4148]).  This activation should be dynamic in order to follow
   changes in network conditions, such as those related with routes
   being added or new customer demands.

   The activation of active measurement sessions (hosted in senders and
   responders considering the architecture described by Cisco [RFC6812])
   is expensive in terms of the resource consumption, e.g., CPU cycle
   and memory footprint, and monitoring functions compete for resources
   with other functions, including routing and switching.  Besides that,
   the activated sessions also increase the network load because of the
   injected traffic.  The resources required and traffic generated by
   the active measurement sessions are a function of the number of
   measured network destinations, i.e., with more destinations the
   larger will be the resources and the traffic needed to deploy the
   sessions.  Thus, to have a better monitoring coverage it is necessary
   to deploy more sessions what consequently turns increases consumed
   resources.  Otherwise, enabling the observation of just a small
   subset of all network flows can lead to an insufficient coverage.

2.  Current Approaches

   The current best practice in feasible deployments of active
   measurement solutions to distribute the available measurement
   sessions along the network consists in relying entirely on the human
   administrator expertise to infer which would be the best location to
   activate such sessions.  This is done through several steps.  First,

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   it is necessary to collect traffic information in order to grasp the
   traffic matrix.  Then, the administrator uses this information to
   infer which are the best destinations for measurement sessions.
   After that, the administrator activates sessions on the chosen subset
   of destinations considering the available resources.  This practice,
   however, does not scale well because it is still labor intensive and
   error-prone for the administrator to compute which sessions should be
   activated given the set of critical flows that needs to be measured.
   Even worse, this practice completely fails in networks whose critical
   flows are too short in time and dynamic in terms of traversing
   network path, like in modern cloud environments.  That is so because
   fast reactions are necessary to reconfigure the sessions and
   administrators are not just enough in computing and activating the
   new set of required sessions every time the network traffic pattern
   changes.  Finally, the current active measurements practice usually
   covers only a fraction of the network flows that should be observed,
   which invariably leads to the damaging consequence of undetected SLA
   violations.

3.  Problem Statement

   Management software can be embedded inside network devices to control
   the deployment of active measurement mechanisms.  In fact, this is
   done by some network equipment vendors, specially to avoid the
   starvation of the network devices (e.g., due to configuration errors
   and lack of experience from human administrators).  However, the
   current approach do not enhance the active measurement capabilities
   in important terms, such as scalability and efficiency.  For example,
   the number of local available measurements (and, consequently,
   detected SLA violations) is still bounded by the number of activated
   sessions.  Thus, if the number of SLA violation is greater than the
   number of available sessions, only a fraction of the violations will
   be observed.  Also, devices cannot share resources and knowledge
   about the networking infrastructures in order to take advantage of
   remote management information (e.g., measurement results).

4.  Benefits of an Autonomic Solution

   The use case considered here is the distributed autonomic detection
   of SLA violations.  The use of Autonomic Networking (AN) properties
   can help such detection through an efficient activation of
   measurement sessions [P2PBNM-Nobre-2012].  The problem to be solved
   by AN in the present use case is how to steer the process of
   measurement session activation by a complete solution that sets all
   necessary parameters for this activation to operate efficiently,
   reliably and securely, with no required human intervention, while
   allowing for their input.

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   We advocate for embedding Peer-to-Peer (P2P) technology in network
   devices in order to improve the measurement session activation
   decisions using autonomic loops.  The provisioning of the P2P
   management overlay should be transparent for the network
   administrator.  It would be possible to control the measurement
   session activation using local data and logic and to share
   measurement results among different network devices.

   An autonomic solution for the distributed detection of SLA violations
   can provide several benefits.  First, efficiency: this solution could
   optimize the resource consumption and avoid resource starvation on
   the network devices.  This optimization comes from different sources:
   sharing of measurement results, better efficiency in the probe
   activation decisions, etc.  Second, effectiveness: the number of
   detected SLA violations could be increased.  This increase is related
   with a better coverage of the network.  Third, the solution could
   decrease the time necessary to detect SLA violations.  Adaptivity
   features of an autonomic loop could capture faster the network
   dynamics than an human administrator.  Finally, the solution could
   help to reduce the workload of human administrator, or, at least, to
   avoid their need to perform operational tasks.

5.  Intended User and Administrator Experience

   The autonomic solution should not require the human intervention in
   the distributed detection of SLA violations.  Besides that, it could
   enable the control of SLA monitoring by less experienced human
   administrators.  However, some information may be provided from the
   human administrator.  For example, the human administrator may
   provide the SLOs regarding the SLA being monitored.  The
   configuration and bootstrapping of network devices using the
   autonomic solution should be minimal for the human administrator.
   Probably it would be necessary just to inform the address of a device
   which is already using the solution and the devices themselves could
   exchange configuration data.

6.  Analysis of Parameters and Information Involved

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   The active measurement model assumes that a typical infrastructure
   will have multiple network segments and Autonomous Systems (ASs), and
   a reasonably large number of several of routers and hosts.  It also
   considers that multiple SLOs can be in place in a given time.  Since
   interoperability in a heterogenous network is a goal, features found
   on different active measurement mechanisms (e.g. OWAMP, TWAMP, and
   IPSLA) and programability interfaces (e.g., Cisco's EEM and onePK)
   could be used for the implementation.  The autonomic solution should
   include and/or reference specific algorithms, protocols, metrics and
   technologies for the implementation of distributed detection of SLA
   violations as a whole.

6.1.  Device Based Self-Knowledge and Decisions

   Each device has self-knowledge about the local SLA monitoring.  This
   could be in the form of historical measurement data and SLOs.
   Besides that, the devices would have algorithms that could decide
   which probes should be activated in a given time.  The choice of
   which algorithm is better for a specific situation would be also
   autonomic.

6.2.  Interaction with other devices

   Network devices should share information about service level
   measurement results.  This information can speed up the detection of
   SLA violations and increase the number of detected SLA violations.
   In any case, it is necessary to assure that the results from remote
   devices have local relevancy.  The definition of network devices that
   exchange measurement data, i.e., management peers, creates a new
   topology.  Different approaches could be used to define this topology
   (e.g., correlated peers [P2PBNM-Nobre-2012]).  To bootstrap peer
   selection, each device should use its known endpoints neighbors
   (e.g., FIB and RIB tables) as the initial seed to get possible peers.

7.  Comparison with current solutions

   There is no standartized solution for distributed autonomic detection
   of SLA violations.  Current solutions are restricted to ad hoc
   scripts running on a per node fashion to automate some
   administrator's actions.  There some proposals for passive probe
   activation (e.g., DECON and CSAMP), but without the focus on
   autonomic features.  It is also mentioning a proposal from Barford et
   al. to detect and localize links which cause anomalies along a
   network path.

8.  Related IETF Work

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   The following paragraphs discuss related IETF work and are provided
   for reference.  This section is not exhaustive, rather it provides an
   overview of the various initiatives and how they relate to autonomic
   distributed detection of SLA violations.  1.  [LMAP]: The Large-Scale
   Measurement of Broadband Performance Working Group aims at the
   standards for performance management.  Since their mechanisms also
   consist in deploying measurement probes the autonomic solution could
   be relevant for LMAP specially considering SLA violation screening.
   Besides that, a solution to decrease the workload of human
   administrators in service providers is probably highly desirable.  2.
   [IPFIX]: IP Flow Information EXport (IPFIX) aims at the process of
   standardization of IP flows (i.e., netflows).  IPFIX uses measurement
   probes (i.e., metering exporters) to gather flow data.  In this
   context, the autonomic solution for the activation of active
   measurement probes could be possibly extended to address also passive
   measurement probes.  Besides that, flow information could be used in
   the decision making of probe activation.  3.  [ALTO]: The Application
   Layer Traffic Optimization Working Group aims to provide topological
   information at a higher abstraction layer, which can be based upon
   network policy, and with application-relevant service functions
   located in it.  Their work could be leveraged for the definition of
   the topology regarding the network devices which exchange measurement
   data.

9.  Acknowledgements

   We wish to acknowledge the helpful contributions, comments, and
   suggestions that were received from Mohamed Boucadair, Bruno Klauser,
   Eric Voit, and Hanlin Fang.

10.  IANA Considerations

   This memo includes no request to IANA.

11.  Security Considerations

   The bootstrapping of a new device follows the approach proposed on
   anima wg [draft-anima-boot], thus in order to exchange data a device
   should register first.  This registration could be performed by a
   "Registrar" device or a cloud service provided by the organization to
   facilitate autonomic mechanisms.  The new device sends its own
   credentials to the Registrar, and after successful authentication,
   receives domain information, to enable subsequent enrolment to the
   domain.  The Registrar sends all required information: a device name,
   domain name, plus some parameters for the operation.  Measurement
   data should be exchanged signed and encripted among devices since
   these data could carry sensible information about network
   infrastructures.  Some attacks should be considering when analyzing

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   the security of the autonomic solution.  Denial of service (DoS)
   attacks could be performed if the solution be tempered to active more
   local probe than the available resources allow.  Besides that,
   results could be forged by a device (attacker) in order to this
   device be considered peer of a specific device (target).  This could
   be done to gain information about a network.

12.  References

12.1.  Normative References

   [P2PBNM-Nobre-2012]
              Nobre, J., Granville, L., Clemm, A., and A. Prieto,
              "Decentralized Detection of SLA Violations Using P2P
              Technology, 8th International Conference Network and
              Service Management (CNSM)", 2012, <http://
              ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6379997>.

   [RFC4656]  Shalunov, S., Teitelbaum, B., Karp, A., Boote, J., and M.
              Zekauskas, "A One-way Active Measurement Protocol
              (OWAMP)", RFC 4656, September 2006.

   [RFC5357]  Hedayat, K., Krzanowski, R., Morton, A., Yum, K., and J.
              Babiarz, "A Two-Way Active Measurement Protocol (TWAMP)",
              RFC 5357, October 2008.

   [RFC6812]  Chiba, M., Clemm, A., Medley, S., Salowey, J., Thombare,
              S., and E. Yedavalli, "Cisco Service-Level Assurance
              Protocol", RFC 6812, January 2013.

   [RFC7297]  Boucadair, M., Jacquenet, C., and N. Wang, "IP
              Connectivity Provisioning Profile (CPP)", RFC 7297, July
              2014.

   [draft-anima-boot]
              Pritikin, M., Behringer, M., and S. Bjarnason, "draft-
              pritikin-anima-bootstrapping-keyinfra", draft-pritikin-
              anima-bootstrapping-keyinfra-01 (work in progress),
              February 2015.

   [draft-elkins-ippm-pdm-option]
              Elkins, N., Hamilton, R., and M. Ackermann, "draft-elkins-
              ippm-pdm-option", draft-elkins-ippm-pdm-option-02 (work in
              progress), September 2014.

12.2.  Informative References

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   [RFC3954]  Claise, B., "Cisco Systems NetFlow Services Export Version
              9", RFC 3954, October 2004.

   [RFC4148]  Stephan, E., "IP Performance Metrics (IPPM) Metrics
              Registry", BCP 108, RFC 4148, August 2005.

Authors' Addresses

   Jeferson Campos Nobre
   Federal University of Rio Grande do Sul
   Porto Alegre
   Brazil

   Email: jcnobre@inf.ufrgs.br

   Lisandro Zambenedetti Granvile
   Federal University of Rio Grande do Sul
   Porto Alegre
   Brazil

   Email: granville@inf.ufrgs.br

   Alexander Clemm
   Cisco Systems
   San Jose
   USA

   Email: alex@cisco.com

   Alberto Gonzalez Prieto
   Cisco Systems
   San Jose
   USA

   Email: albertgo@cisco.com

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