Resource allocation in decentralised computational systems: an evolutionary market-based approach

Peter R. Lewis, Paul Marrow, Xin Yao

    Research output: Contribution to journalArticlepeer-review


    We present a novel market-based method, inspired by retail markets, for resource allocation in fully decentralised systems where agents are self-interested. Our market mechanism requires no coordinating node or complex negotiation. The stability of outcome allocations, those at equilibrium, is analysed and compared for three buyer behaviour models. In order to capture the interaction between self-interested agents, we propose the use of competitive coevolution. Our approach is both highly scalable and may be tuned to achieve specified outcome resource allocations. We demonstrate the behaviour of our approach in simulation, where evolutionary market agents act on behalf of service providing nodes to adaptively price their resources over time, in response to market conditions. We show that this leads the system to the predicted outcome resource allocation. Furthermore, the system remains stable in the presence of small changes in price, when buyers' decision functions degrade gracefully.
    Original languageEnglish
    Pages (from-to)143-171
    Number of pages29
    JournalAutonomous Agents and Multiagent Systems
    Issue number2
    Early online date29 Oct 2009
    Publication statusPublished - Sept 2010


    • decentralised systems
    • market-based control
    • coevolution
    • load balancing
    • resource allocation
    • self-interested agents


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