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Cloud-DLS: Dynamic trusted scheduling for Cloud computing
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DOI：10.1016/j.eswa.2011.08.048.png)
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Abstract
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Clouds are rapidly becoming an important platform for scientific applications. In the Cloud environment with uncountable numeric nodes, resource is inevitably unreliable, which has a great effect on task execution and scheduling. In this paper, inspired by Bayesian cognitive model and referring to the trust relationship models of sociology, we first propose a novel Bayesian method based cognitive trust model, and then we proposed a trust dynamic level scheduling algorithm named Cloud-DLS by integrating the existing DLS algorithm. Moreover, a benchmark is structured to span a range of Cloud computing characteristics for evaluation of the proposed method. Theoretical analysis and simulations prove that the Cloud-DLS algorithm can efficiently meet the requirement of Cloud computing workloads in trust, sacrificing fewer time costs, and assuring the execution of tasks in a security way. (C) 2011 Elsevier Ltd. All rights reserved.
Keywords:
Cloud computing
Bayesian
Cognitive model
Scheduling
Trust
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