Observations on Using Genetic Algorithms for Dynamic Load-Balancing
IEEE Transactions on Parallel and Distributed Systems
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Journal of Systems Architecture: the EUROMICRO Journal
Observations on Using Genetic-Algorithms for Channel Allocation in Mobile Computing
IEEE Transactions on Parallel and Distributed Systems
Reliability Analysis of Grid Computing Systems
PRDC '02 Proceedings of the 2002 Pacific Rim International Symposium on Dependable Computing
Genetic Algorithm Based Scheduler for Computational Grids
HPCS '05 Proceedings of the 19th International Symposium on High Performance Computing Systems and Applications
A Unified Scheduling Algorithm for Grid Applications
HPCS '06 Proceedings of the 20th International Symposium on High-Performance Computing in an Advanced Collaborative Environment
Evaluating the reliability of computational grids from the end user's point of view
Journal of Systems Architecture: the EUROMICRO Journal
Fair Game-Theoretic Resource Management in Dedicated Grids
CCGRID '07 Proceedings of the Seventh IEEE International Symposium on Cluster Computing and the Grid
Reliability-Aware Resource Management for Computational Grid/Cluster Environments
GRID '05 Proceedings of the 6th IEEE/ACM International Workshop on Grid Computing
From P2P and Grids to Services on the Web: Evolving Distributed Communities
From P2P and Grids to Services on the Web: Evolving Distributed Communities
Grid Workflow Scheduling Based on the Resource Combination Reliability
ICNC '08 Proceedings of the 2008 Fourth International Conference on Natural Computation - Volume 01
Adaptive grid job scheduling with genetic algorithms
Future Generation Computer Systems
A task duplication based scheduling algorithm on GA in grid computing systems
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part III
A Scheduling Model with Multi-Objective Optimization for Computational Grids using NSGA-II
International Journal of Applied Evolutionary Computation
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This paper presents a grid scheduling model to schedule a job on the grid with the objective of ensuring maximum reliability to the job under the current grid state. The model schedules a modular job to those resources that suit the job requirements in terms of resources while offering the most reliable environment. The reliability estimates depict true grid picture and considers the contribution of the computational resources, network links and the application awaiting allocation. The scheduling executes the interactive jobs while considering the looping structure. As scheduling on the grid is an NP hard problem, soft computing tools are often applied. This paper applies Modified Genetic Algorithm MGA, which is an elitist selection method based on the two threshold values, to improve the solution. The MGA works on the basis of partitioning the current population in three categories: the fittest chromosomes, average fit chromosomes and the ones with worst fitness. The worst are dropped, while the fittest chromosomes of the current generation are mated with the average fit chromosomes of the previous generation to produce off-spring. The simulation results are compared with other similar grid scheduling models to study the performance of the proposed model under various grid conditions.