Understanding decentralised control of resource allocation in a minimal multi-agent system


Jacyno, Mariusz, Bullock, Seth, Luck, Michael and Payne, Terry (2007) Understanding decentralised control of resource allocation in a minimal multi-agent system. At the 6th International Joint Conference on Autonomous Agents and Multi-agent Systems, Hawaii, USA,

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Description/Abstract

Utility computing exemplifies a novel kind of solution to the increasing scale and complexity of modern IT systems. Here, the “on-demand” provisioning of computing resources is managed via a population of independent software agents that query and negotiate with one another in an open system of resource providers and consumers that has no fixed organisation and is free to change and grow organically. Where centralised executive control of agent activity is relaxed or removed, such systems have the potential to deliver scalable, flexible computing. However, major design and control challenges must be overcome if multi-agent systems are to achieve efficient, decentralised resource allocation that delivers reliable and robust performance. In this paper we introduce a minimally complex multi-agent system, where individual agents rely on simple, local strategies to perform resource allocation. We explore the relationship between local and global behaviour as system size, load, heterogeneity and reliability are varied. We identify generic feedbacks underlying system behaviour that must be balanced if decentralised control is to become an effective technique for preserving stable functionality across utility computing infrastructures.

Item Type: Conference or Workshop Item (Poster)
Additional Information: Event Dates: 2007
Keywords: agents, decentralized control, self-organisation, complex systems, emergence
Divisions: Faculty of Physical Sciences and Engineering > Electronics and Computer Science > Agents, Interactions & Complexity
ePrint ID: 263384
Date Deposited: 06 Feb 2007
Last Modified: 29 Mar 2014 13:10
Projects:
Amorphous computation, random graphs and complex biological networks
Funded by: EPSRC (EP/D00232X/1)
1 January 2006 to 30 September 2010
Further Information:Google Scholar
URI: http://eprints.soton.ac.uk/id/eprint/263384

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