Abstract
This paper addresses the task allocation problem in open, dynamic grid or service-oriented environments. In such environments, both grid/service providers and consumers can be modeled as intelligent agents. These agents can leave off and enter into an open environment freely at any time. Task allocation under time constraints becomes a critical issue in such environments since it is difficult to apply a central controller during the allocation process due to the openness of environments as well as decentralized natures of agents. This paper proposes a negotiation-based method for task allocation under time constraints in an open, dynamic grid environment, where both consumer and provider agents can enter into or leave off the environment freely. In this method, there is no central controller, and agents negotiate with each other for task allocation based only on local views. The experimental results show that the proposed method can outperform state-of-art methods in terms of success rate of task allocation and total profit obtained from the allocated tasks by agents under different time constraints.
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