Optimized scheduling of scientific workflows based on iterated local search

<span>Recent years have witnessed a great interest in scientific applications with large data and processing-intensive, so cloud computing is used which provides the resources needed to implement run these applications. One of challenges management workflow scheduling them solve many combinatorial optimization problems, including reducing execution time, cost, resource utilization, energy <span>consumption. Due fact that iterated local search algorithm (ILS) has been successfully applied this paper investigates performance ILS solving problem highly constrained problem. The main components are different from one others parameters, search, perturbation, must be</span> <span>carefully designed. standard examined compared latest technology. experimental results show proposed obtained good best-known literature. This due being an adaptable metaheuristic, can be simply adapted different situations instances.</span></span>