A Double Auction Mechanism for Resource Allocation on Grid Computing Systems

Considering dynamic, heterogeneous and autonomous characteristics of computing resources in grid computing systems and the flexibility and effectivity of economics methods applied to solve the problem of resource management, a double auction mechanism for resource allocation on grid computing systems is presented. Firstly, a market model of double auction is described, in which agents are utilized to represent the computational resource traders in the grid environment and are equipped with the reinforcement learning algorithm. Secondly, a double auction mechanism is presented, where the uniform-price auction is adopted aiming at CPU resources, and the transaction fee can be adjusted flexibly. Finally, the efficiency of the presented double auction mechanism is analyzed through experiments, and experimental results show that the presented mechanism is efficient, and the transaction price varies mildly.

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