An optimised genetic algorithm for energy aware grid computing with limited iterations. (2016) - Sathish, Kuppani; Reddy, A. Rama Mohan
Grid computing is one of the emerging computing platforms that handles both parallel and distributed computing. This type of the grid environment appends the complicated nature to the scheduler. Genetic algorithm (GA) is a generally used approach by researchers to figure out this type of NP-complete problems. Yet, the conventional GA is also sluggish to figure out the scheduling issues in the realistic environment due to its time consuming iterations. In this composition, we adopt the independent batch scheduling by considering the objective as energy expenditure as the scheduling criteria. Here, we proposed an optimised energy aware genetic algorithm (OGA), which is suitable for grid scheduling, and it can improve the search performance by limited iterations and increase the computing capability of finding the reasonable solution.