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Authors: Pedro A. Aranda Gutierrez 1 ; David Wagner 2 ; Ilka Miloucheva 2 ; Christof Brandauer 3 and Ulrich Hofmann 3

Affiliations: 1 Telefonica R&D, Spain ; 2 Fraunhofer Institute, Schloss Birlinghoven, Germany ; 3 Salzburg Research, Austria

ISBN: 978-989-8111-14-2

Keyword(s): QoS measurement policy, policy repository, heterogeneous access IP network, learning component, reinforcement learning, supervised learning.

Related Ontology Subjects/Areas/Topics: Mobile Software and Services ; Telecommunication Software Systems, Tools and Languages ; Telecommunications ; Wireless Information Networks and Systems

Abstract: A challenge of today’s measurement architectures for QoS/SLA monitoring in heterogeneous network environment is enhanced intelligence in order to minimise measurements and derive automatically optimised measurement strategies for the network operators. Such optimisations can be done with different goals – avoid redundant measurements, sharing of measurements for different QoS monitoring goals and enhancement of measurement strategies considering QoS/SLA measurement requests. For automated optimisation of measurement strategies, QoS measurement policies are proposed whose parameters are adapted dynamically based on specified learning algorithms and rules. For the policy adaptation different kinds of learning can be used, as for instance reinforcement and supervised learning. The integration of the proposed policy based strategies into policy management architecture is discussed. A learning component collecting rules and algorithms for measurement policy adaptation is proposed which can be used by different tools of a policy management system. A graphical user interface (GUI) for a realistic policy based measurement scenario is discussed which aims to optimise the measurement strategies of the network operator. (More)

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Paper citation in several formats:
A. Aranda Gutierrez P.; Wagner D.; Miloucheva I.; Brandauer C.; Hofmann U. and (2007). POLICY BASED QOS MONITORING - Automated Learning Strategies for Policy Enhancement.In Proceedings of the Second International Conference on Wireless Information Networks and Systems - Volume 1: WINSYS, (ICETE 2007) ISBN 978-989-8111-14-2, pages 275-281. DOI: 10.5220/0002151402750281

@conference{winsys07,
author={Pedro {A. Aranda Gutierrez} and David Wagner and Ilka Miloucheva and Christof Brandauer and Ulrich Hofmann},
title={POLICY BASED QOS MONITORING - Automated Learning Strategies for Policy Enhancement},
booktitle={Proceedings of the Second International Conference on Wireless Information Networks and Systems - Volume 1: WINSYS, (ICETE 2007)},
year={2007},
pages={275-281},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002151402750281},
isbn={978-989-8111-14-2},
}

TY - CONF

JO - Proceedings of the Second International Conference on Wireless Information Networks and Systems - Volume 1: WINSYS, (ICETE 2007)
TI - POLICY BASED QOS MONITORING - Automated Learning Strategies for Policy Enhancement
SN - 978-989-8111-14-2
AU - A. Aranda Gutierrez, P.
AU - Wagner, D.
AU - Miloucheva, I.
AU - Brandauer, C.
AU - Hofmann, U.
PY - 2007
SP - 275
EP - 281
DO - 10.5220/0002151402750281

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