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A policy-based framework for autonomic reconfiguration management in heterogeneous networks

Published: 03 December 2008 Publication History

Abstract

This paper presents a policy-based framework to approach the issue of autonomous reconfiguration management in heterogeneous networks. In contrast to existing policy-based approaches, the proposed framework addresses the management issue from a new perspective through posing it as a problem of learning from current network behavior, while creating and updating policies dynamically in response to changing reconfiguration requirements, and this task is implemented by Reinforcement Learning methodology. A two-layer policy model is used to mapping users and operators' higher level goals into network level objectives. The autonomic reconfiguration procedures for policy creation, storage, evaluation are also presented in detail. Illustrative examples analysis and simulation results demonstrate the performance of the proposed work.

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  • (2015)Artificial Intelligence-Based Techniques for Emerging Heterogeneous Network: State of the Arts, Opportunities, and ChallengesIEEE Access10.1109/ACCESS.2015.24671743(1379-1391)Online publication date: 2015
  • (2014)Adapting policy-based management of Future Networks using collaborative filtering techniques2014 IEEE 19th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD)10.1109/CAMAD.2014.7033239(224-228)Online publication date: Dec-2014
  • (2013)A dynamic governance framework for efficient orchestration of hetnet empowerment mechanisms2013 International Conference on Smart Communications in Network Technologies (SaCoNeT)10.1109/SaCoNeT.2013.6654593(1-5)Online publication date: Jun-2013

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      cover image ACM Conferences
      MUM '08: Proceedings of the 7th International Conference on Mobile and Ubiquitous Multimedia
      December 2008
      227 pages
      ISBN:9781605581927
      DOI:10.1145/1543137
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      Published: 03 December 2008

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      Author Tags

      1. adaptive policies
      2. autonomic communications
      3. policy-based management
      4. reconfigurable systems
      5. reinforcement learning

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      View all
      • (2015)Artificial Intelligence-Based Techniques for Emerging Heterogeneous Network: State of the Arts, Opportunities, and ChallengesIEEE Access10.1109/ACCESS.2015.24671743(1379-1391)Online publication date: 2015
      • (2014)Adapting policy-based management of Future Networks using collaborative filtering techniques2014 IEEE 19th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD)10.1109/CAMAD.2014.7033239(224-228)Online publication date: Dec-2014
      • (2013)A dynamic governance framework for efficient orchestration of hetnet empowerment mechanisms2013 International Conference on Smart Communications in Network Technologies (SaCoNeT)10.1109/SaCoNeT.2013.6654593(1-5)Online publication date: Jun-2013

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