The week's pick
Reseach Article
Improving Performance in Load Balancing Problem on the Grid Computing System
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 16 - Number 1 |
| Year of Publication: 2011 |
| Authors: Prabhat Kr.Srivastava, Sonu Gupta, Dheerendra Singh Yadav |
10.5120/1979-2658
|
Prabhat Kr.Srivastava, Sonu Gupta, Dheerendra Singh Yadav . Improving Performance in Load Balancing Problem on the Grid Computing System. International Journal of Computer Applications. 16, 1 ( February 2011), 6-10. DOI=10.5120/1979-2658
Abstract
Load Balancing is a technique to improve resources, utilizing parallelism, exploiting throughput managing and to reduce response time through proper distribution of the application. Load balancing strategies is always used for the emergence of Distributed systems. Generally there are three type of phases related to Load balancing i.e. Information Collection, Decision Making, Data Migration.
References
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- Rajkumar Buyya , Grid Computing and Distributed Systems (GRIDS) Lab., Department of Computer Science and Software Engineering, University of Melbourne, Australia and Manzur Murshed, Gippsland School of comp and IT, Monash University, Gippsland Campus , GridSim: a toolkit for the modeling and simulation of distributed resource mgmt and scheduling for Grid computing.
- Dazhang Gu, Lin Yang, Lonnie R. Welch ,Center for Intelligent, Distributed and Dependable Systems ,School of Electrical Engineering & Computer Science ,Ohio University, A Predictive, Decentralized Load Balancing Approach.
- Akshay Luther, Rajkumar Buyya, Rajiv Ranjan, and Srikumar Venugopal, “Peer-to-Peer Grid Computing and a .NET-based Alchemi Framework”, GRIDS Laboratory, The University of Melbourne, Australia.
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- Jennifer M. Schopf, Mathematics and ComputerScience Division, Argonn National Lab, Department of Computer Science, Northwestern University, Grids: The Top Ten Questions.
- Karl Czajkowski, Ian Foster and Carl Kesselman, Resource Co-Allocation in Computational Grids.
- Ann Chervenak, Ian Foster, Carl Kesselman, Charles Salisbury and Steven Tuecke, The Data Grid: Towards an Architecture for the Distributed Management and Analysis of Large Scientific Data sets.
- Klaus Krauter, Rajkumar Buyya, and Muthucumaru Maheswaran, a Taxonomy and Survey of Grid Resource Management Systems.
- Arie Shoshani, Alex Sim and Junmin Gu, Lawrence Berkeley National laboratory, Storage Resource Managers: Middleware Components for Grid Storage.
- Hai Zhuge, Xiaoping Sun, Jie Liu, Erlin Yao, and Xue Chen, A Scalable P2P Platform for the Knowledge Grid.
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