Stochastic Scheduling Algorithm for Distributed Cloud Networks using Heuristic Approach

Rule based heuristic scheduling algorithms in real time and cloud computing Systems employ for resource or task scheduling since they are suitable to implement for NP-complete problems. However, they are simple but there is much room to improve these algorithms. This study presents a heuristic scheduling algorithm, called High performance hyper-heuristic scheduling algorithm (HHSA) using detection operator, to find better scheduling solutions for real and cloud computing systems. The two operators - diversity detection and improvement detection operators - are employed in this algorithm to determine the timing to determine the heuristic algorithm.. These two are employed to dynamically determine a low level heuristic that can be used to find better solution. To evaluate the performance of this method, authors examined the above method with several scheduling algorithms and results prove that Hyper Heuristic Scheduling Algorithm can significantly decrease the make span of task scheduling when compared with all other scheduling algorithms. A novel high-performance hyper-heuristic algorithm is proposed for scheduling on cloud computing systems to reduce the makespan. This algorithm can be applied to both sequence dependent and sequence independent scheduling problems.