Secure and confidential workflow scheduling in hybrid cloud using improved particle swarm optimization algorithm
While private clouds provide high security and low cost for scheduling workflow, public clouds are potentially exposed to the risk of data and computation breach as well as their higher costs. In real world, however, we may need high performance resources and high capacity storage devices encouraging organizations to use public clouds. Task scheduling, therefore, is one of the most important challenges in cloud computing. In this paper a new scheduling method is proposed for workflow applications in hybrid cloud, while considering the security issue as well. Specifically, in adition to sensitivity of tasks, that considered in recent works, security requirement for data and security strength for both resources and channels are taken into account. Proposed scheduling method is implemented by improved particle swarm optimization algorithm and is named PSO-WSCS. The goal function is to minimize the security distance of data and workflow from security strengths of resources and channels so that time and budget constraints are met. The proposed PSO-WSCS algorithm is compared with three state of the art scheduling algorithms, namely VNPSO, MPSO and MPSO-SA, in hybrid cloud. Evaluations show the effectiveness of our algorithm by finding resources having security aspects resemblance to the security requirements. In average, improvement of 40% is resulted for the given samples.
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