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Towards Optimal Collaboration of Policies in the Two-Phase Scheduling of Cloud Tasks

Abstract : The use of virtualization technology makes software applications more scalable and cost effective when they are deployed over cloud computing platforms, but virtualization technology also brings challenges to task scheduling over cloud. The commonly used list scheduling schemes split the scheduling process into two phases: ordering and dispatching. However, majorities of recent researches about scheduling of cloud tasks concentrate on optimizing the schedulers’ performance in one phase, but seldom consider the collaborations of scheduling policies used in different phases. This paper summarizes some representative ordering and dispatching policies used in list schedulers, models the execution processes of these ordering and dispatching policies using Stochastic Petri Nets (SPN), and simulates the list scheduling process of cloud tasks. Based on the modeling and experimental results, we further evaluate which composition of ordering and dispatching policies provides optimal performance in the two-phase scheduling process of cloud tasks.
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Cong Xu, Jiahai Yang, Di Fu, Hui Zhang. Towards Optimal Collaboration of Policies in the Two-Phase Scheduling of Cloud Tasks. 11th IFIP International Conference on Network and Parallel Computing (NPC), Sep 2014, Ilan, Taiwan. pp.306-320, ⟨10.1007/978-3-662-44917-2_26⟩. ⟨hal-01403097⟩



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