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Survivable topology design of hierarchical hybrid fibre-VDSL access networks using enhanced discrete binary PSO

Survivable topology design of hierarchical hybrid fibre-VDSL access networks using enhanced... As one of the most efficient access solutions, VDSL technology is becoming a highlight in the next generation fixed access networks. This paper addresses the topology design of hierarchical hybrid fibre-VDSL access networks, which is verified as an NP-hard problem. An effective strategy with two binary models is proposed to find a cost-effective and survivable network topology with adaptive metaheuristic-based algorithms in a short time. An enhanced discrete binary particle swarm optimisation (DBPSO) is developed and successfully implemented for this network planning problem, both for clustering and positioning. In terms of numerical results, the performance of the enhanced DBPSO is compared with some related approaches to simulated annealing, tabu search, genetic algorithms, ant colony optimisation and Yin?Yang optimisation. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Autonomous and Adaptive Communications Systems Inderscience Publishers

Survivable topology design of hierarchical hybrid fibre-VDSL access networks using enhanced discrete binary PSO

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Publisher
Inderscience Publishers
Copyright
Copyright © Inderscience Enterprises Ltd. All rights reserved
ISSN
1754-8632
eISSN
1754-8640
DOI
10.1504/IJAACS.2010.035547
Publisher site
See Article on Publisher Site

Abstract

As one of the most efficient access solutions, VDSL technology is becoming a highlight in the next generation fixed access networks. This paper addresses the topology design of hierarchical hybrid fibre-VDSL access networks, which is verified as an NP-hard problem. An effective strategy with two binary models is proposed to find a cost-effective and survivable network topology with adaptive metaheuristic-based algorithms in a short time. An enhanced discrete binary particle swarm optimisation (DBPSO) is developed and successfully implemented for this network planning problem, both for clustering and positioning. In terms of numerical results, the performance of the enhanced DBPSO is compared with some related approaches to simulated annealing, tabu search, genetic algorithms, ant colony optimisation and Yin?Yang optimisation.

Journal

International Journal of Autonomous and Adaptive Communications SystemsInderscience Publishers

Published: Jan 1, 2010

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