Application of intelligent water drops algorithm to workflow scheduling in cloud environment

Cloud Computing has evolved as the one of the most promising approach to execute large scale workflow applications. For successful implementation of any workflow application in cloud computing environment, one of the most significant tasks is to generate an efficient schedule before its execution. The main goal of workflow scheduling is to assign tasks to available resources in a finite time with the satisfaction of users' specified QoS constraints. As workflow scheduling is an NP complete problem, most of the previous work is based on metaheuristic techniques to achieve near optimal solutions within polynomial time. In this paper, we are presenting an application of Intelligent Water drops (IWD) algorithm, a novel metaheuristic technique, to solve workflow scheduling problem focusing on minimization of makespan. The probability function of IWD algorithm is modified to improve quality of solution and enhance convergence speed. Experimental results show that our proposed algorithm achieves better results in comparison to other existing algorithms.