Abstract
In this paper, we propose a new algorithm for job interchange in Computational Grids that consist of autonomous and equitable HPC sites, called Shaking-G. Originally developed for balancing the sharing of video files in P2P networks, we conceptually transfer and adapt the algorithm to the domain of job scheduling in Grids, building an integrated, load-adaptive two-tier job exchange strategy. We evaluate the performance of Shaking-G with real workload data in different experimental scenarios and show that it outperforms traditional non-Grid aware algorithms in setups without job interchange, fostering the benefits of collaboration between large HPC centers.
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