job grouping based scheduling algorithm di mukherjee arijit (6 risultati)

Taschenbuch. Condizione: Neu. Job-Grouping Based Scheduling Algorithm for Computational Grids | An Efficient Job-Grouping Based Scheduling Algorithm for Fine-Grained Jobs in Computational Grids | Arijit Mukherjee (u. a.) | Taschenbuch | 60 S. | Englisch | 2012 | LAP LAMBERT Academic Publishing | EAN 9783847309574 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.

Paperback. Condizione: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Grid computing is a high performance computing environment to solve large-scale computational demands. Computational grids has emerged as a next generation computing platform which is a collection of heterogeneous computing resources connected by a network across dynamic and geographically dispersed organizations, to form a distributed high performance computing infrastructure. Our work is mainly based on job-grouping approach for fine-grained job scheduling in computational grids. Resources in computational grid are heterogeneous in nature, owned and managed by different organizations with different allocation policies. In our scheduling algorithm jobs are scheduled based on resources computational and communication capabilities. Independent fine-grained jobs are grouped together based on the chosen resources characteristics, to maximize resource utilization and minimize processing time and cost. The performance of the algorithm is evaluated based on above mentioned performance parameters and compared with other existing fine-grained job scheduling strategies using GridSim toolkit. 60 pp. Englisch.

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Mukherjee ArijitArijit Mukherjee has done his M.Tech in CSE from NIT Rourkela,India. His research interest includes Parallel & Distributed Computing, Scheduling Algorithms. Dr. P.M. Khilar has done his PhD from IIT Kharagpur, India. .

Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Grid computing is a high performance computing environment to solve large-scale computational demands. Computational grids has emerged as a next generation computing platform which is a collection of heterogeneous computing resources connected by a network across dynamic and geographically dispersed organizations, to form a distributed high performance computing infrastructure. Our work is mainly based on job-grouping approach for fine-grained job scheduling in computational grids. Resources in computational grid are heterogeneous in nature, owned and managed by different organizations with different allocation policies. In our scheduling algorithm jobs are scheduled based on resources computational and communication capabilities. Independent fine-grained jobs are grouped together based on the chosen resources characteristics, to maximize resource utilization and minimize processing time and cost. The performance of the algorithm is evaluated based on above mentioned performance parameters and compared with other existing fine-grained job scheduling strategies using GridSim toolkit.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 60 pp. Englisch.

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Grid computing is a high performance computing environment to solve large-scale computational demands. Computational grids has emerged as a next generation computing platform which is a collection of heterogeneous computing resources connected by a network across dynamic and geographically dispersed organizations, to form a distributed high performance computing infrastructure. Our work is mainly based on job-grouping approach for fine-grained job scheduling in computational grids. Resources in computational grid are heterogeneous in nature, owned and managed by different organizations with different allocation policies. In our scheduling algorithm jobs are scheduled based on resources computational and communication capabilities. Independent fine-grained jobs are grouped together based on the chosen resources characteristics, to maximize resource utilization and minimize processing time and cost. The performance of the algorithm is evaluated based on above mentioned performance parameters and compared with other existing fine-grained job scheduling strategies using GridSim toolkit.