The grid: blueprint for a new computing infrastructure
The grid: blueprint for a new computing infrastructure
The Anatomy of the Grid: Enabling Scalable Virtual Organizations
Euro-Par '01 Proceedings of the 7th International Euro-Par Conference Manchester on Parallel Processing
Theory of cellular automata: a survey
Theoretical Computer Science
IEEE Transactions on Parallel and Distributed Systems
A Hybrid Policy for Job Scheduling and Load Balancing in Heterogeneous Computational Grids
ISPDC '07 Proceedings of the Sixth International Symposium on Parallel and Distributed Computing
IEEE Transactions on Parallel and Distributed Systems
Game-Theoretic Approach for Load Balancing in Computational Grids
IEEE Transactions on Parallel and Distributed Systems
Towards a hybrid load balancing policy in grid computing system
Expert Systems with Applications: An International Journal
Load Balancing Using Enhanced Ant Algorithm in Grid Computing
CIMSIM '10 Proceedings of the 2010 Second International Conference on Computational Intelligence, Modelling and Simulation
Game-theoretic static load balancing for distributed systems
Journal of Parallel and Distributed Computing
Towards decentralized load balancing in a computational grid environment
GPC'06 Proceedings of the First international conference on Advances in Grid and Pervasive Computing
Hi-index | 0.00 |
Load balancing algorithms play a challenging, complicated, and important role in the performance of computational Grid systems. In this paper, we present a decentralized adaptive load balancing algorithm with use of cellular automata, named LBA_CA. Each computing node in the Grid system is modeled as a cell of proposed cellular automata and can be in four states. Cellular automata (abbreviated to CA) are used for designing a load balancing algorithm for computational Grids because of its distributed and dynamic manner. In addition, such natural properties of CA make LBA_CA an appropriate local load balancing algorithm for each cluster of computational Grids. Due to resource heterogeneity and communication overheads exist in computational Grid systems; we take account of several issues in LBA_CA such as processing power of computing nodes and communication latency. The main goal of our algorithm is to reduce the average response time of arrival jobs. The performance of our algorithm is evaluated in terms of several metrics including the average response time of jobs, processor utilization, percent of executed jobs, and average Off time in relation to considerable variations in transition time, service time, and number of jobs.