DocumentCode
29397
Title
Cloning, Resource Exchange, and RelationAdaptation: An Integrative Self-Organisation Mechanism in a Distributed Agent Network
Author
Dayong Ye ; Minjie Zhang ; Sutanto, Danny
Author_Institution
Sch. of Comput. Sci. & Software Eng., Univ. of Wollongong, Wollongong, NSW, Australia
Volume
25
Issue
4
fYear
2014
fDate
Apr-14
Firstpage
887
Lastpage
897
Abstract
Self-organisation provides a suitable paradigm for developing self-managed complex distributed systems, such as grid computing and sensor networks. In this paper, an integrative self-organisation mechanism is proposed. Unlike current related studies, which propose only a single principle of self-organisation, this mechanism synthesises the three principles of self-organisation: cloning/spawning, resource exchange and relation adaptation. Based on this mechanism, an agent can autonomously generate new agents when it is overloaded, exchange resources with other agents if necessary, and modify relations with other agents to achieve a better agent network structure. In this way, agents can adapt to dynamic environments. The proposed mechanism is evaluated through a comparison with three other approaches, each of which represents state-of-the-art research in each of the three self-organisation principles. Experimental results demonstrate that the proposed mechanism outperforms the three approaches in terms of the profit of individual agents and the entire agent network, the load-balancing among agents, and the time consumption to finish a simulation run.
Keywords
distributed processing; multi-agent systems; resource allocation; agent network structure; autonomous agent generation; cloning principle; distributed agent network; grid computing; integrative self-organisation mechanism; load-balancing; relation adaptation principle; resource exchange principle; self-managed complex distributed systems; self-organisation principle; sensor networks; simulation run; spawning principle; Cloning; Equations; Layout; Mathematical model; Multi-agent systems; Nickel; Resource management; Distributed multi-agent system; reinforcement learning; self-organisation;
fLanguage
English
Journal_Title
Parallel and Distributed Systems, IEEE Transactions on
Publisher
ieee
ISSN
1045-9219
Type
jour
DOI
10.1109/TPDS.2013.120
Filename
6506072
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