Abstract
Some load imbalance problems emerge under the distributed cloud computing platform based on container. And it is necessary to transfer the container in the higher load server to another relatively idle servers. The traditional pre-copy algorithm ignores the characteristics of the memory pages, which causes memory pages with high re-modified rate copying many times in the iterative copy phase. Therefore, this paper proposes an optimized pre-copy algorithm (OPCA) which introduces a Gray-Markov prediction model. Memory pages are added with high re-modified rate into the Hot Workspace by the prediction model, and these memory pages are involved in the stop-copy. The experiments show that OPCA reduces the number of iterations and downtime. Moreover, it also improves the utilization of resources and enhances the user’s experience.
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Acknowledgments
The subject is sponsored by the National Natural Science Foundation of P.R. China (Nos. 61373017, 61572260, 61572261, 61672296, 61602261), the Natural Science Foundation of Jiangsu Province (Nos. BK20140886, BK20140888, BK20160089), Scientific & Technological Support Project of Jiangsu Province (Nos. BE2015702, BE2016777, BE2016185), China Postdoctoral Science Foundation (Nos. 2014M551636, 2014M561696), Jiangsu Planned Projects for Postdoctoral Research Funds (Nos. 1302090B, 1401005B), Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks Foundation (No. WSNLBZY201508), Research Innovation Program for College Graduates of Jiangsu Province (SJZZ16_0148).
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Nie, H., Li, P., Xu, H., Dong, L., Song, J., Wang, R. (2017). Research on Optimized Pre-copy Algorithm of Live Container Migration in Cloud Environment. In: Chen, G., Shen, H., Chen, M. (eds) Parallel Architecture, Algorithm and Programming. PAAP 2017. Communications in Computer and Information Science, vol 729. Springer, Singapore. https://doi.org/10.1007/978-981-10-6442-5_53
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DOI: https://doi.org/10.1007/978-981-10-6442-5_53
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