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Authors: Valery Katerinchuk 1 ; Andreas Albrecht 2 and Kathleen Steinhöfel 1

Affiliations: 1 King’s College London, United Kingdom ; 2 Middlesex University London, United Kingdom

Keyword(s): Energy Efficiency, Wired Networks, Multiple Multicast Requests, Multicast Routing, Simulated Annealing, Genetic Algorithm, Hybrid Algorithm, Partially Mixed Crossover.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Computational Intelligence ; Evolutionary Computing ; Soft Computing

Abstract: Energy-efficient multicast routing algorithms have predominantly focused on wireless or ad-hoc mobile networks. However, since the turn of the century the need for energy efficient approaches to routing in wired networks has been steadily rising. In this paper, we introduce an objective function for multicast routing in wired networks taking energy consumption into consideration. A number of hybrid Genetic and Simulated Annealing based algorithms have been shown to be able to find better solutions to the multicast routing problem compared to solely Genetic or Simulated Annealing based algorithms. Our approach adapts a population-based hybrid algorithm for routing multiple simultaneous multicast requests. We examine the performance in terms of energy efficiency against solutions found by Logarithmic Simulated Annealing and Genetic based algorithms. We find that the hybrid approach, in 87% of instances, was able to find superior solutions, and in 96% of instances, solutions superior or equal to the best solution given by either Simulated Annealing or Genetic approaches. The extent of the improvement however varied greatly from a few hundred to within ten Joules, with the improvement on the best solution ranging from 5.6 to 531.5 Joules. (More)

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Paper citation in several formats:
Katerinchuk, V.; Albrecht, A. and Steinhöfel, K. (2014). Energy-efficient Multicast Routing by using Genetic Local Search. In Proceedings of the 6th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-758-015-4; ISSN 2184-433X, pages 740-746. DOI: 10.5220/0004926907400746

@conference{icaart14,
author={Valery Katerinchuk. and Andreas Albrecht. and Kathleen Steinhöfel.},
title={Energy-efficient Multicast Routing by using Genetic Local Search},
booktitle={Proceedings of the 6th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2014},
pages={740-746},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004926907400746},
isbn={978-989-758-015-4},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 6th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - Energy-efficient Multicast Routing by using Genetic Local Search
SN - 978-989-758-015-4
IS - 2184-433X
AU - Katerinchuk, V.
AU - Albrecht, A.
AU - Steinhöfel, K.
PY - 2014
SP - 740
EP - 746
DO - 10.5220/0004926907400746

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