A Comparison Between Genetic Algorithm and Cuckoo Search Algorithm to Minimize the Makespan for Grid Job Scheduling
Tarun Kumar Ghosh, Sanjoy Kumar Das, Subhabrata Barman, Rajmohan Goswami · Advances in intelligent systems and computing · 2016
Major subjects like heterogeneity of resources, dynamic and autonomous character of Grid resources are most important challenges for Grid job scheduling. Additionally, there are issues of various strategies being maintained by the resource providers and followed by resource users for execution of their jobs. Thus optimal job scheduling is an NP-complete problem which can easily be solved by using heuristic approaches. This paper compares two heuristic methods: Genetic Algorithm (GA) and Cuckoo Search Algorithm (CSA) for job scheduling problem in order to efficiently allocating jobs to resources in a Grid system so that the makespan is minimized. Our empirical results have proved that the CSA performs better than the GA.