An Incentive-Based Peer-to-Peer Grid Scheduling

In a grid commuting environment, resources are autonomous, wide-area distributed, and they are usually not free. These unique characteristics make scheduling in a self-sustainable and market-lime grid highly challenging. The goal of our work is to build such a global computational grid that every participant has enough incentive to stay and play in it. There are two parties in the grid: resources consumers and resource providers. Thus the performance objective of scheduling is two-fold: for consumers, high successful execution rate of jobs, and for providers, fair allocation of benefits. We propose an incentive-based grid scheduling, which is composed of a P2P decentralized scheduling framework and incentive-based scheduling algorithms. We present an incentive-based scheduling scheme, which utilizes a peer-to-peer decentralized scheduling framework, a set of local heuristic algorithms, and three market instruments of job announcement, price, and competition degree. The results show that our approach outperforms other scheduling schemes in optimizing incentives for both consumers and providers, leading to highly successful job execution and fair profit allocation.