An auto-configurable, and, adaptable, metric-driven cluster-head organisation for hybrid multi-hop routing

Migas, Nikos and Buchanan, William J (2006) An auto-configurable, and, adaptable, metric-driven cluster-head organisation for hybrid multi-hop routing. In: Engineering of Computer Based Systems, 2006. ECBS 2006. 13th Annual IEEE International Symposium and Workshop on. IEEE Computer Society, pp. 8-22. ISBN 0-7695-2546-6

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Multi-hop ad-hoc routing is a challenging issue, because of the dynamic network topology, and limited capabilities of resource-constrained mobile devices. This paper proposes a metric-driven clustering organisation of participating nodes which provides an effective way to reduce network overhead, in contrast to traditional flooding methods. This novel method creates a network backbone for data routing and location management, which is composed of the fittest nodes. The key metrics are: mobility, buffering capabilities, throughput, network state, utilisation, and battery reserves. The paper presents the overall agent-based model, and describes the adaptability of the cluster-head metrics, and the automated reconfigurability of an ad-hoc network

Item Type: Book Section
ISBN: 0-7695-2546-6
Additional Information: ("(c) 2006 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.")
Uncontrolled Keywords: Multi-hop ad-hoc routing; network topology; resource constrained mobile devices; metric-driven clustering; nodes; flooding; data routing; mobility; buffering; network state; utilisation; agent-based model; cluster-head metrics;
University Divisions/Research Centres: Faculty of Engineering, Computing and Creative Industries > School of Computing
Dewey Decimal Subjects: 600 Technology > 620 Engineering > 621 Electronic & mechanical engineering > 621.3 Electrical & electronic engineering > 621.38 Electronics & Communications engineering
000 Computer science, information & general works > 000 Computer science, knowledge & systems > 004 Data processing & computer science
Library of Congress Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Item ID: 3961
Depositing User: Professor Bill Buchanan
Date Deposited: 23 Dec 2010 11:42
Last Modified: 18 Dec 2013 13:43

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