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2015 10th International Conference on P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC) (2015)
Krakow, Poland
Nov. 4, 2015 to Nov. 6, 2015
ISBN: 978-1-4673-8317-2
pp: 116-120
ABSTRACT
Cloud computing is a pattern of processing the big data and provides the convenient, on-demand network access to a shared pool of configurable computing resources. Cloud data center's cost is becoming the hot topic in recent years. This paper studies how to minimize the bandwidth cost for uploading deferral big data to a cloud computing platform, based on the MapReduce Framework. We study the deficiency of randomized online algorithm and Dynamic Self-adaption Algorithm, and we propose the improved algorithm to minimize the bandwidth cost based on DSA, and the results demonstrate that the IDSA' performance is better than the ROA and DSA.
INDEX TERMS
Heuristic algorithms, Cloud computing, Bandwidth, Industries, Distributed databases, Resource management, Schedules
CITATION

B. Cui, P. Shi, J. Yang and Y. Hao, "Uploading Deferrable Big Data to the Cloud by Improved Dynamic Self-Adaption Algorithm," 2015 10th International Conference on P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC), Krakow, Poland, 2015, pp. 116-120.
doi:10.1109/3PGCIC.2015.39
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