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Metaheuristics for Scheduling in Distributed Computing Environments

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Cover of 'Metaheuristics for Scheduling in Distributed Computing Environments'

Table of Contents

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    Book Overview
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    Chapter 1 Meta-heuristics for Grid Scheduling Problems
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    Chapter 2 Optimizing Routing and Backlogs for Job Flows in a Distributed Computing Environment
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    Chapter 3 Robust Allocation and Scheduling Heuristics for Dynamic, Distributed Real-Time Systems
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    Chapter 4 Supercomputer Scheduling with Combined Evolutionary Techniques
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    Chapter 5 Adapting Iterative-Improvement Heuristics for Scheduling File-Sharing Tasks on Heterogeneous Platforms
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    Chapter 6 Advanced Job Scheduler Based on Markov Availability Model and Resource Selection in Desktop Grid Computing Environment
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    Chapter 7 Workflow Scheduling Algorithms for Grid Computing
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    Chapter 8 Decentralized Grid Scheduling Using Genetic Algorithms
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    Chapter 9 Metaheuristics for Scheduling in Distributed Computing Environments
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    Chapter 10 Efficient Batch Job Scheduling in Grids Using Cellular Memetic Algorithms
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    Chapter 11 P2P B&B and GA for the Flow-Shop Scheduling Problem
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    Chapter 12 Peer-to-Peer Neighbor Selection Using Single and Multi-objective Population-Based Meta-heuristics
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    Chapter 13 An Adaptive Co-ordinate Based Scheduling Mechanism for Grid Resource Management with Resource Availabilities
Attention for Chapter 10: Efficient Batch Job Scheduling in Grids Using Cellular Memetic Algorithms
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