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2012 IEEE Fifth International Conference on Cloud Computing
Risk-Aware Workload Distribution in Hybrid Clouds
Honolulu, HI, USA USA
June 24-June 29
ISBN: 978-1-4673-2892-0
This paper explores an efficient and secure mechanism to partition computations across public and private machines in a hybrid cloud setting. We propose a principled framework for distributing data and processing in a hybrid cloud that meets the conflicting goals of performance, sensitive data disclosure risk and resource allocation costs. The proposed solution is implemented as an add-on tool for a Hadoop and Hive based cloud computing infrastructure. Our experiments demonstrate that the developed mechanism can lead to a major performance gain by exploiting both the hybrid cloud components without violating any pre-determined public cloud usage constraints.
Index Terms:
Cloud computing,Computational modeling,Resource management,Dynamic programming,Heuristic algorithms,Data models,Organizations,hybrid cloud,Data Privacy,Cloud Computing,Risk aware data processing
Kerim Yasin Oktay, Vaibhav Khadilkar, Bijit Hore, Murat Kantarcioglu, Sharad Mehrotra, Bhavani Thuraisingham, "Risk-Aware Workload Distribution in Hybrid Clouds," cloud, pp.229-236, 2012 IEEE Fifth International Conference on Cloud Computing, 2012
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