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

Peter R. LEWIS, Paul MARROW, Xin YAO

Research output: Journal PublicationsJournal Article (refereed)peer-review

28 Citations (Scopus)


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. © 2009 The Author(s).
Original languageEnglish
Pages (from-to)143-171
Number of pages29
JournalAutonomous Agents and Multi-Agent Systems
Issue number2
Early online date28 Oct 2009
Publication statusPublished - Sept 2010
Externally publishedYes

Bibliographical note

This work is partially supported by a UK EPSRC/BT CASE studentship project on “Autonomic Solutions for Virtualised ICT Systems” and an EPSRC project (No. GR/T10671/01) on “Market Based Control of Complex Computational Systems”.


  • Coevolution
  • Decentralised systems
  • Load balancing
  • Market-based control
  • Resource allocation
  • Self-interested agents


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