Abstract
P2P based high performance computing (HPC) system introduces many new and interesting problems. P2P environment is heterogeneous and asynchronous. At the same time, P2P platform is not stable. The joining and leaving of peers are random. These characteristics make the P2P based HPC platform have great difference to the traditional HPC platform and the global computing project. To achieve effective job scheduling on P2P based platform, this paper introduces a DHT based monitor and task management scheme. Further, we propose a data structure of distributed bidirectional Skiplist to keep the prediction session time. Our scheme distributes the task to the nodes which have longer online session time. With such scheme, we can reduce the migration of tasks among different nodes and improve the resource utilization of computing nodes. Finally, we use a real trace to demonstrate the efficiency of our algorithms and scheduling schemes.
This paper is supported by ChinaGrid project from Ministry of Education of China, the National High-Tech Research and Development Plan of China under grant No.2006AA01A115, and National Science Foundation of China under grant No.90412010, No.60433040 and NSFC/RGC Joint Research Foundation under grant No.60731160630.
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Zhang, H., Jin, H., Zhang, Q. (2009). Scheduling Strategy of P2P Based High Performance Computing Platform Base on Session Time Prediction. In: Abdennadher, N., Petcu, D. (eds) Advances in Grid and Pervasive Computing. GPC 2009. Lecture Notes in Computer Science, vol 5529. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01671-4_33
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DOI: https://doi.org/10.1007/978-3-642-01671-4_33
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-01670-7
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