Bio-Inspired Optimization Techniques for Job Scheduling In Grid Computing

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.