Abstract
Xen, a popular virtualization platform which enables multiple operating systems sharing one physical host, has been widely used in various fields nowadays. Currently, the existing schedulers of Xen are initially targeting at serial jobs, which achieves a remarkable utilization of computer hardware and impressive overall performance. However, the virtualized systems are expected to accommodate both parallel jobs and serial jobs in practice, and resource contention between virtual machines results in severe performance degradation of the parallel jobs. Moreover, the physical resource is vastly wasted during the communication process due to the ineffective scheduling of parallel jobs.
This paper aims to optimize the performance of the parallel jobs in Xen using the co-scheduling mechanism. In this paper, we statistically analyze the process of scheduling parallel jobs in Xen, which points out that the credit scheduler is not capable of properly scheduling a parallel job. Moreover, we propose vPlacer, a conservative co-scheduler to improve the performance of the parallel job in Xen. Our co-scheduler is able to identify the parallel jobs and optimize the scheduling process to satisfy the particularity of the parallel job. The prototype of our vPlacer is implemented, and the experimental results show that the performance of the parallel job is significantly improved and the utilization of the hardware resource is optimized.
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Acknowledgement
This work is partially supported by the National Key R&D Program of China 2018YFB1003201 and Guangdong Pre-national Project 2014GKXM054.
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Jiang, P., He, L., Ren, S., Chen, Z., Mao, R. (2018). vPlacer: A Co-scheduler for Optimizing the Performance of Parallel Jobs in Xen. In: Vaidya, J., Li, J. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2018. Lecture Notes in Computer Science(), vol 11334. Springer, Cham. https://doi.org/10.1007/978-3-030-05051-1_2
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