Metaheuristics for scheduling in distributed computing environments
Grid computing has emerged as one of the most promising computing paradigms of the new millennium! Achieving high performance Grid computing requires techniques to efficiently and adaptively allocate jobs and applications to available resources in a large scale, highly heterogenous and dynamic envir...
Gespeichert in:
| Weitere Verfasser: | , , |
|---|---|
| Format: | Livre numérique |
| Sprache: | Anglais |
| Veröffentlicht: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
[20..].
Cham : Springer Nature |
| Ausgabe: | 1st ed. 2008. |
| Schriftenreihe: | Studies in Computational Intelligence
146 |
| Online Zugang: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Anmerkung: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Metaheuristics for scheduling in distributed computing environments, Fatos Xhafa, Ajith Abraham (eds.), Berlin, Springer Verlag, 2008, 1 vol. (xv-364 p.), Studies in computational intelligence, 978-3-540-69260-7 • Metaheuristics for Scheduling in Distributed Computing Environments, Texte imprimé, 9783540865148 • Metaheuristics for Scheduling in Distributed Computing Environments, Texte imprimé, 9783642088759 • Metaheuristics for scheduling in distributed computing environments, Fatos Xhafa, Ajith Abraham (eds.), Berlin, Springer Verlag, 2008, 1 vol. (xv-364 p.), Studies in computational intelligence, 978-3-540-69260-7 |
Inhaltsangabe:
- Meta-heuristics for Grid Scheduling Problems Optimizing Routing and Backlogs for Job Flows in a Distributed Computing Environment Robust Allocation and Scheduling Heuristics for Dynamic, Distributed Real-Time Systems Supercomputer Scheduling with Combined Evolutionary Techniques Adapting Iterative-Improvement Heuristics for Scheduling File-Sharing Tasks on Heterogeneous Platforms Advanced Job Scheduler Based on Markov Availability Model and Resource Selection in Desktop Grid Computing Environment Workflow Scheduling Algorithms for Grid Computing Decentralized Grid Scheduling Using Genetic Algorithms Nature Inspired Meta-heuristics for Grid Scheduling: Single and Multi-objective Optimization Approaches Efficient Batch Job Scheduling in Grids Using Cellular Memetic Algorithms P2P B&B and GA for the Flow-Shop Scheduling Problem Peer-to-Peer Neighbor Selection Using Single and Multi-objective Population-Based Meta-heuristics An Adaptive Co-ordinate Based Scheduling Mechanism for Grid Resource Management with Resource Availabilities