Three-Way Task Scheduling Algorithm for Cloud Computing

Cloud task scheduling is a crucial aspect of cloud computing, and it directly influences cloud resource usage. This study presents a cloud task scheduling algorithm based on granularity and three-way decision making (CTSA-3WD). This research aims to address the issues of load imbalance, low resource utilization, and job completion time. In the proposed approach, the execution duration of cloud jobs and the actual computing resource situation restrict the task set’s light-load and heavy-load functions. The algorithm is based on the three-way decision-making and separates the work set into three pieces. The system focusses on three distinct task sets and determines an optimal scheduling strategy by employing the Max-Min algorithm for the significant proportion of light-load jobs task set, the Min-Min algorithm for the substantial percentage of heavy-load studies, and the Min-Min and Max-Min algorithms combination for the task set with both light and heavy load tasks. The experimental results demonstrate that the CTSA-3WD algorithm, when compared to Min-Min, Max-Min, and selective scheduling algorithms, effectively enhances overall resource utilization. Additionally, it enables improved load balancing across the entire system.