Titlebook: Metaheuristics for Scheduling in Distributed Computing Environments; Fatos Xhafa,Ajith Abraham Book 2008 Springer-Verlag Berlin Heidelberg

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Workflow Scheduling Algorithms for Grid Computing,-dependent tasks on distributed resources. It introduces allocating suitable resources to workflow tasks so that the execution can be completed to satisfy objective functions specified by users. Proper scheduling can have significant impact on the performance of the system. In this chapter, we inves

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Efficient Batch Job Scheduling in Grids Using Cellular Memetic Algorithms,ny conflicting criteria in very short periods of time. This problem has been tackled in the literature by several different meta-heuristics, and our main focus in this work is to develop a new highly competitive technique with respect to the existing ones. For that, we exploit the capabilities of Ce

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P2P B&B and GA for the Flow-Shop Scheduling Problem, The efficiency of such algorithm can be improved by its hybridization with meta-heuristics such as Genetic Algorithms (GA) which proved their effectiveness, since they generate acceptable solutions in a reasonable time. Moreover, distributing at large scale the computation, using for instance Peer-

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Peer-to-Peer Neighbor Selection Using Single and Multi-objective Population-Based Meta-heuristics,this Chapter, we introduce the problem of neighbor selection in peer-to-peer networks using two population based meta-heuristics: Particle Swarm Optimization (PSO) algorithms and Genetic Algorithms (GAs). Both a single objective and a multi-objective problem are formulated, and then the P2P neighbor

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1860-949X eduling approaches, excellent coverage of timely, advanced scheduling topics, state-of-the-art theoretical research and application developments and chapters authored by pioneers in the field. Academics, scientists as 978-3-642-08875-9978-3-540-69277-5Series ISSN 1860-949X Series E-ISSN 1860-9503

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