Bio-inspired optimization techniques for job scheduling in grid computing
Reetika Grover, Amit Chabbra · 2016
Grid computing provides an environment with large number of disseminated and decentralized computational resources which coordinate and provide resource sharing on networks situated at different locations to fulfill large-scale computational demands. Scheduling of jobs in such environment is a crucial task, so various evolutionary algorithms have gained immense popularity among researchers for finding feasible solutions to optimization problems. Due to heterogeneity and complexity of resources, bio-inspired algorithms are capable of finding a good solution in ample amount of time. Bio-inspired heuristics show effectiveness and generality for handling computational optimization problems. Various bio-inspired techniques have been explored in this paper.