Effects of communication latency, overhead, and bandwidth in a cluster architecture
Proceedings of the 24th annual international symposium on Computer architecture
The grid: blueprint for a new computing infrastructure
The grid: blueprint for a new computing infrastructure
Distributed Job Scheduling on Computational Grids Using Multiple Simultaneous Requests
HPDC '02 Proceedings of the 11th IEEE International Symposium on High Performance Distributed Computing
A De-Centralized Scheduling and Load Balancing Algorithm for Heterogeneous Grid Environments
ICPPW '02 Proceedings of the 2002 International Conference on Parallel Processing Workshops
Job Superscheduler Architecture and Performance in Computational Grid Environments
Proceedings of the 2003 ACM/IEEE conference on Supercomputing
The Anatomy of the Grid: Enabling Scalable Virtual Organizations
International Journal of High Performance Computing Applications
A distributed and cooperative load balancing mechanism for large-scale P2P systems
SAINT-W '06 Proceedings of the International Symposium on Applications on Internet Workshops
IEEE Transactions on Parallel and Distributed Systems
Proceedings of the 1st Amrita ACM-W Celebration on Women in Computing in India
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Grid computing holds the great promise to effectively share geographically distributed heterogeneous resources to solve large-scale complex scientific problems. One of the distinct characteristics of the Grid system is resource heterogeneity. The effective use of the Grid requires an approach to manage the heterogeneity of the involved resources that can include computers, data, network, etc. In this paper, we proposed a de-centralized and adaptive load balancing algorithm for heterogeneous Grid environment. Our algorithm estimates different system parameters (such as job arrival rate, CPU processing rate, load at processor) and effectively performs load balancing by considering all necessary affecting criteria. Simulation results demonstrate that our algorithm outperforms conventional approaches in the event of heterogeneous environment and when communication overhead is significant.