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Locating object efficiently in a distributed computing system using ant colony optimisation
Conference paper   Open access

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

J.B. Li and C.C. Fung
IEEE
2nd IEEE International Conference on Digital Ecosystems and Technologies, IEEE-DEST 2008 (Phitsanulok, Thailand, 26/02/2008–29/02/2008)
2008
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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.

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