Abstract: As an essential component of the cloud computing system,task scheduling directly impacts resource utilization and service quality.To solve the problems existing in Min-Min and Max-Min algorithms in the current cloud platform,such as load imbalance,low comprehensive resource utilization,and sizeable overall task completion time due to task distribution,a task sche-duling optimization algorithm based on the three-way decision (CTSA-3WD) is proposed.First,the algorithm divides tasks into light-load and heavy-load tasks according to their execution time and computational resource requirements.Secondly,the algorithm divides the tasks into three categories according to the proportion of the task set's two types of tasks.It develops scheduling strategies for these three task sets.Specifically,the strategy uses the Max-Min algorithm for tasks with a high percentage of light load tasks and uses the Min-Min algorithm for a high proportion of heavily loaded tasks.An improved task scheduling algorithm based on Min-Min and Max-Min is used for the set,which has close numbers between light and heavy-duty tasks.Third,the critical resources in the allocated nodes are rescheduled.The algorithm selects the best matching tasks to be allocated to the light-load resources,subject to the overall completion time reduction.The experimental based on the CloudSim reveals that the CTSA-3WD algorithm can effectively improve the overall resource utilization and quality of service to users compared to Min-Min,Max-Min,selective scheduling algorithms.Moreover,it also makes the resources in the whole system reach a better load-balancing level.

Key words: Cloud computing, Load balancing, Multi-granularity, Task scheduling, Three-way decisions