Honolulu, HI, USA USA
June 24, 2012 to June 29, 2012
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.
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, 2012, 2013 IEEE Sixth International Conference on Cloud Computing, 2013 IEEE Sixth International Conference on Cloud Computing 2012, pp. 229-236, doi:10.1109/CLOUD.2012.128