Flexible resource allocation for reliable virtual cluster computing systems
Proceedings of 2011 International Conference for High Performance Computing, Networking, Storage and Analysis
Provisioning Virtual Resources Adaptively in Elastic Compute Cloud Platforms
International Journal of Web Services Research
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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 kalman filter to implement the framwork. Comparison among the three methods suggests they can be effectively and efficiently used to reduce the makspan in three different real-world workload scenarios.