Dynamic Task Scheduler for Real Time Requirement in Cloud Computing System

In such an era of big data, the number of tasks submitted to cloud computing system becomes huge and users' demand for real time has increased. But the existing algorithms rarely take real time into consideration and most of them are static scheduling algorithms. As a result, we ensure real time of cloud computing system under the premise of not influencing the performance on makespan and load balance by proposing a dynamic scheduler called Real Time Dynamic Max-min-min (RTDM) which takes real time, makespan, and load balance into consideration. RTDM is made up of dynamic sequencer and static scheduler. In dynamic sequencer, the tasks are sorted dynamically based on their waiting and execution times to decrease makespan and improve real time. The tasks fetched from the dynamic sequencer to the static scheduler can be seen as static tasks, so we propose an algorithm named Max-min-min in static scheduler which achieves good performance on waiting time, makespan and load balance simultaneously. Experiment results demonstrate that the proposed scheduler greatly improves the performance on real time and makespan compared with the static scheduling algorithms like Max-min, Min-min and PSO, and improves performance on makespan and real time by 1.66% and 17.19% respectively compared to First Come First Serve (FCFS).