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Hybrid Cloud Computing: Economy, Scalability and Responsiveness Optimization
Paper Type  |
Contributed Paper |
Title |
Hybrid Cloud Computing: Economy, Scalability and Responsiveness Optimization |
Author |
Thepparit Banditwattanawong[a], Masawee Masdisornchote*[a], Putchong Uthayopas[b] |
Email |
masawee@gmail.com |
|
Abstract: Hybrid cloud computing gains interest from communities as it supports risk mitigation, business partnership, quality-of-service (QoS) improvement and accesses to uniquely-offered services. Since the providers of a hybrid cloud potentially offer different QoS levels, this sets the new condition of cloud data transfer optimization to reduce public cloud data-out expenses, to improve cloud network scalability and to lower cloud service access latencies. This paper presents an intelligent cloud cache replacement policy, i-Cloud, as the core mechanism of client-side shared cloud cache. Trace-driven simulations have showed that i-Cloud is capable of addressing nonuniform QoS levels by delivering stable performances that outperformed three well-known cache replacement policies in all studied performance metrics against all experimented workloads. The results have also indicated that taking data-out charge rate nonuniformity into cache replacement decisions improved caching performances in all metrics. Furthermore, i-Cloud not only attained optimal efficiencies in all of the performance metrics simultaneously but also performed well for longer runs than its training durations.
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Start & End Page |
884 - 896 |
Received Date |
2014-05-07 |
Revised Date |
|
Accepted Date |
2014-07-30 |
Full Text |
Download |
Keyword |
cloud cache eviction scheme, multi-provider cloud, artificial neural network, cost-saving ratio, window size |
Volume |
Vol.43 No.4 (JULY 2016) |
DOI |
|
Citation |
Banditwattanawong[a] T., Masdisornchote*[a] M. and Uthayopas[b] P., Hybrid Cloud Computing: Economy, Scalability and Responsiveness Optimization, Chiang Mai Journal of Science, 2016; 43(4): 884-896. |
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