Title :
Optimisation strategies for distributed computing using an adaptive randomised structured network
Author :
Fung, Chun-che ; Li, Jia-bin
Author_Institution :
Sch. of Inf. Technol., Murdoch Univ., Murdoch, WA
Abstract :
One way to improve computational efficiency for complex engineering applications is to utilise distributed computing. In such distributed system, accessing objects through location-independent names can improve the systempsilas transparency, scalability and reliability. Names however need to be resolved prior to passing the messages between the objects. This paper reports an Adaptive RandoMised Structured search network termed ARMS, which utilises a distributed ant colony optimisation algorithms (ACO) to improve the efficiency of searching in a distributed environment. The paper further investigates different kinds of optimisation strategies in order to improve search efficiency. Simulation studies have shown ARMS is superior to Chord, a well-known structured network, under various performance measures.
Keywords :
distributed algorithms; object-oriented programming; adaptive randomised structured network; ant colony optimisation algorithms; distributed computing; distributed searching algorithm; naming models; object-based distributed systems; Adaptive systems; Ant colony optimization; Arm; Cybernetics; Distributed computing; Information technology; Machine learning; Object oriented modeling; Peer to peer computing; Scalability; Distributed searching algorithm; Naming models; Object-based distributed systems; Randomised structured network;
Conference_Titel :
Machine Learning and Cybernetics, 2008 International Conference on
Conference_Location :
Kunming
Print_ISBN :
978-1-4244-2095-7
Electronic_ISBN :
978-1-4244-2096-4
DOI :
10.1109/ICMLC.2008.4621082