We propose a novel method for allocating multi-attribute computational resources via competing marketplaces. Trading agents, working on behalf of resource consumers and providers, choose to trade in resource markets where the re- sources being traded best align with their preferences and constraints. Market-exchange agents, in competition with each other, attempt to provide resource markets that attract traders, with the goal of maximising their profit. Because exchanges can only partially observe global supply and demand schedules, novel strategies are required to automate their search for market niches. Novel attribute-level selection (ALS) strategies are empirically analysed in simulated competitive market environments, and results suggest that using these strategies, market-exchanges can seek out market niches under a variety of environmental conditions. Copyright 2011 ACM.
|Title of host publication
|ACM International Conference Proceeding Series
|Published - 3 Aug 2011