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

Mariusz Jacyno, Seth Bullock, Michael Luck, Terry Payne

    Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

    7 Citations (Scopus)

    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.
    Original languageUndefined/Unknown
    Title of host publicationProceedings of the Sixth International Joint Conference on Autonomous Agents and Multi-agent Systems (AAMAS 2007)
    EditorsEdmund Durfee, Makoto Yokoo, Michael Huhns, Ohn Shehory
    PublisherAssociation for Computing Machinery (ACM)
    Pages1251-1253
    Number of pages3
    DOIs
    Publication statusPublished - 2007

    Bibliographical note

    Event dates: May 14-18, 2007

    Keywords

    • agents, decentralized control, self-organisation, complex systems, emergence

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