*Research Scholar, Department of Computer of Science & Engineering, Park College of Engineering & Technology, Anna University, India
**Professor & Head, Department of Computer of Science & Engineering, Park College of Engineering & Technology, India
Online published on 9 December, 2016.
Rule Based Scheduling Algorithm have been widely used in the cloud computing as it is simple and easy to implement the Scheduling criteria in terms of energy efficiency and less delay, In this paper, we propose Improved Hyper Heuristic Scheduling which is used to find the candidate solution (low level heuristic) form Scheduling Solutions (heuristics algorithms) from the simulated annealing and genetic algorithm in dynamic large scale Cloud Computing system with diversity operator as sequence dependent and sequence independent scheduling. Specifically, Resources and workloads characterised using the simulated annealing and improved genetic algorithm with n point crossover. Hyper heuristic algorithm is used select best possible solution to the dynamic workload to candidate solutions. The Simulation results on cloudsim proves that proposed system outperforms existing state of approaches in terms of reduced make span and flow time for the task scheduling and resource management
Resource Scheduling, Cloud Computing
