The Hough transform on a reconfigurable multi-ring network
Journal of Parallel and Distributed Computing
A taxonomy and survey of grid resource management systems for distributed computing
Software—Practice & Experience
Parallel Edge-Region-Based Segmentation Algorithm Targeted at Reconfigurable MultiRing Network
The Journal of Supercomputing
Grid Computing: Making the Global Infrastructure a Reality
Grid Computing: Making the Global Infrastructure a Reality
The Anatomy of the Grid: Enabling Scalable Virtual Organizations
International Journal of High Performance Computing Applications
A Routing Load Balancing Policy for Grid Computing Environments
AINA '06 Proceedings of the 20th International Conference on Advanced Information Networking and Applications - Volume 01
Adaptive pre-task assignment scheduling strategy for heterogeneous distributed raytracing system
Computers and Electrical Engineering
A survey of load balancing in grid computing
CIS'04 Proceedings of the First international conference on Computational and Information Science
An enhanced load balancing mechanism based on deadline control on GridSim
Future Generation Computer Systems
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Grid is a network of computational resources that may potentially span many continents. Maximization of the resource utilization hinges on the implementation of an efficient load balancing scheme, which provides (i) minimization of idle time, (ii) minimization of overloading, and (iii) minimization of control overhead. In this paper, we propose a dynamic and distributed load balancing scheme for grid networks. The distributed nature of the proposed scheme not only reduces the communication overhead of grid resources but also cuts down the idle time of the resources during the process of load balancing. We apply the proposed load balancing approach on Enhanced GridSim in order to gauge the effectiveness in terms of communication overhead and response time reduction. We show that significant savings are delivered by the proposed technique compared to other approaches such as centralized load balancing and no load balancing.