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Elastic compute clouds are best represented by the virtual clusters in Amazon EC2 or in IBM RC2. This paper proposes a simulation based approach to scheduling scientific workflows onto elastic clouds. Scheduling multitask workflows in virtual clusters is a NP-hard problem. Excessive simulations in months of time may be needed to produce the optimal schedule using Monte Carlo simulations. To reduce...
Virtual machines are allocated on demand in virtualized cloud platforms to provide flexible and reliable services. The major difficulty lies in satisfying the conflicting objectives of reducing response time while lowering resource costs. In this paper, a mathematical multi-tier framework for virtual machine allocation is proposed, which can be used to capture the performance of the cloud platform...
This paper presents AMREF, an Adaptive Map Reduce Framework designed for an effective use of computational resources in data center networks to deal with real time data intensive applications. AMREF entails its adaptivity from adaptive splitter, adaptive mappers and adaptive reducers in a stochastic control manner. We use three methods, feedback control, stochastic learning with smooth filter and...
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