Titlebook: Automated Workflow Scheduling in Self-Adaptive Clouds; Concepts, Algorithms G. Kousalya,P. Balakrishnan,C. Pethuru Raj Book 2017 Springer I

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Stepping into the Digital Intelligence Era,practices are hitting the market. There is a kind of convergence blurring the boundaries of physical and virtual worlds. Further on, all kinds of physical, mechanical, electrical, and electronics systems are adequately empowered to be instrumented and interconnected to exhibit intelligent behavior.

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Demystifying the Traits of Software-Defined Cloud Environments (SDCEs),machines are being virtualized in order to have multiple virtual machines, which are provisioned dynamically and kept in ready and steady state to deliver sufficient resources (compute, storage, and network) for optimally running any software application. That is, a physical machine can be empowered

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Workflow Modeling and Simulation Techniques, to solve the complex scientific workflows in distributed environment. There are many scientific workflow simulation software frameworks that are available for grid and cloud environment. WorkflowSim is an open-source simulator. WorkflowSim Simulator extends the existing CloudSim Simulator. The arch

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Execution of Workflow Scheduling in Cloud Middleware, Cloud provides a better solution to this problem by offering the promising environment for the execution of these workflow. As it involves tremendous data computations and resources, there is a need to automate the entire process. Workflow management system serves this purpose by orchestrating work

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Workload Consolidation Through Automated Workload Scheduling,sed on their server utilization. The primary objective is to optimally allocate the number of servers for executing the workflows which in turn minimize the cost and energy of data centers. This chapter consolidates the cost- and energy-aware workload consolidation approaches along with the tools an

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