Abstract:

Task and resource scheduling is one of the key technologies for the cloud system. However, the existing research tends to ignore the dynamic nature of real-time tasks and the randomness of task execution time, which makes the pre-generated schedule may not being effective in real execution. To address this issue, a randomness aware scheduling architecture is designed; a heuristic scheduling algorithm, integrating proactive and reactive strategy （PRS）, is proposed to schedule tasks dynamically, which improves the ability of the cloud system to guarantee the timeliness of real-time tasks; three strategies are proposed to scale up/down computing resources according to the system load to reduce the energy consumption. Finally, the performance of the algorithm PRS is compared with the other four algorithms. The experimental results show that compared with the existing algorithms the performance of the algorithm PRS is improved by 13.85% and 17.23% in terms of guarantee ratio and energy consumption.