Affiliations: [a] School of Computer Engineering and Applied Mathematics, Changsha University, Changsha, China | [b] Information Engineering Department, Zhangjiajie Institute of Aeronautical Engineering, Zhangjiajie, China
Correspondence:
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Corresponding author. Fangmin Li, School of Computer Engineering and Applied Mathematics, Changsha University, Changsha 410081, China. E-mail: [email protected].
Abstract: To deal with the problem of unbalanced load and ignoring task priority in previous task scheduling algorithms, this paper proposes a task scheduling algorithm named P-Min-Min-Max, which combines with priority and greedy strategy. Under the condition of considering the task priority, the algorithm leverages the execution time of tasks for greedy strategy, and binding large task and small task in the task list to form “task pair” to perform scheduling, so as to effectively solve the problem of unbalanced load. To reduce the average response time of tasks, the algorithm priority schedules the small task from the “task pair”. The experimental results show that, compared with the Min-Min and P-Min-Min algorithm, the proposed algorithm improves the system resource utilization and service quality of user, and saves the total execution time for tasks. Compared with Max-Min and P-Max-Min algorithm, the proposed algorithm improves the system resource utilization and service quality of user, and reduces the total completion time and average response time.
Keywords: Cloud computing, greedy strategy, load balancing, priority, service quality
