An Energy Preserving and Fault Tolerant Task Scheduler in Cloud Computing

In Cloud, virtualization technology is employed to integrate physical machines into a virtual resource pool to control resources in centralized manner. Recent work considers various strategies with only taking into account only one specific problem of task scheduling without considering the other related problems. Provisioning customer applications in the Cloud while maintaining the application's required quality of service and achieving resource efficiency with power consumption issues are still open research challenges in Cloud computing. Hence, by considering other related problems of the task scheduling while schedule tasks can improve the resource utilization, fault tolerance, energy saving and throughput of the Cloud system. In this paper, we proposed an integrated task scheduling algorithm that takes into account the issues such as VM management and Datacenter management. This algorithm is implemented on CloudSim platform and the obtained experimental results show that the proposed algorithm runs efficiently, reducing the average execution time, average waiting time of tasks and improving the throughput of the Cloud system. The proposed algorithm can be easily integrated with Virtual Machine management strategies and is fault tolerant and can efficiently deal with energy consumption problem.