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Locating object efficiently in a distributed computing system using ant colony optimisation

Li, J.B. and Fung, C.C. (2008) Locating object efficiently in a distributed computing system using ant colony optimisation. In: 2nd IEEE International Conference on Digital Ecosystems and Technologies, IEEE-DEST 2008, 26-29 Feb. 2008, Phitsanulok, Thailand pp. 59-64.

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Link to Published Version: http://dx.doi.org/10.1109/DEST.2008.4635191
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Abstract

Digital Ecosystems reply on efficient computing and communication infrastructures. One way to improve computation efficiency is to utilise distributed computing systems. In an object-based distributed system, the use of location-independent naming scheme can improve the system's transparency, scalability and reliability. Names however need to be resolved prior to pass messages between the objects. This paper reports the use of a distributed Ant Colony Optimisation algorithms (ACO) to improve the efficiency of searching objects in a distributed computing system. The ACO algorithm is designed for an Adaptive RandoMised Structured search network termed ARMS. The approach provides name resolution by forwarding a query through neighbouring nodes. The performance of ARMS is compared to Chord, a well-known structured network. Simulation studies have shown ARMS is superior to Chord as ARMS requires a shorter path in query forwarding.

Publication Type: Conference Paper
Murdoch Affiliation: School of Information Technology
Publisher: IEEE
Copyright: (c) 2008 IEEE.
Notes: Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
URI: http://researchrepository.murdoch.edu.au/id/eprint/576
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