Software

Efficient Grid Task-Bundle Allocation Using Bargaining Based Self-Adaptive Auction

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Executive Summary

To address coordination and complexity issues, the authors formulate a grid task allocation problem as a bargaining based self-adaptive auction and propose the BarSAA grid task-bundle allocation algorithm. During the auction, prices are iteratively negotiated and dynamically adjusted until market equilibrium is reached. The BarSAA algorithm features decentralized bidding decision making in a heterogeneous distributed environment so that scheduler can offload its duty onto participating computing nodes and significantly reduces scheduling overheads. When a BarSAA auction converges, the equilibrium point is Pareto Optimal and achieves social efficient outcome and double-sided revenue maximization.

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