Titlebook: Handbook on Data Centers; Samee U. Khan,Albert Y. Zomaya Book 2015 Springer Science+Business Media New York 2015 Commodity Networks.Data C

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Energy-Aware Algorithms for Task Graph Scheduling, Replica Placement and Checkpoint Strategiesocessors can run at different speeds. Faster speeds allow for a faster execution, but they also lead to a much higher (superlinear) power consumption. Energy-aware scheduling aims at minimizing the energy consumed during the execution of the target application, both for computations and for communic

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A Power-Aware Autonomic Approach for Performance Management of Scientific Applications in a Data Ceny increased in numbers and have become great consumers of electrical power. Supercomputers often run at their peak performance for an efficient execution of scientific applications, and therefore consume an enormous amount of power that results in increased operational cost. Furthermore, an increase

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CoolEmAll: Models and Tools for Planning and Operating Energy Efficient Data Centresr factors such as the increased competition for energy resources. The financial crisis may have dampened data centre demand temporarily, but current projections indicate strong growth ahead. By 2020, it is estimated that annual investment in the construction of new data centres will rise to $ 50bn i

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Smart Data Center centers tremendously. In this chapter, we have addressed the problem of minimizing the operational cost of the power consumption in the data center. We have presented a new idea to power up the data center from more than one Smart grid. The algorithm titled “Smart Data center” is also presented in

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Network Virtualization in Data Centers: A Data Plane Perspectivezation. By virtualizing physical network links, each virtual network may obtain a slice of network links and build its own logical topology out of the shared physical topology. In network node virtualization, a physical networking device is logically partitioned so that each virtual network has its

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