Three-Way Task Scheduling Algorithm for Cloud Computing

Cloud task scheduling is a crucial aspect of a cloud computing system, and its scheduling technique directly influences cloud platform resource usage and user service quality. This study presents a cloud task scheduling optimization algorithm, known as CTSA-3WD, which aims to address the issues of load imbalance, low resource utilization, and lengthy job completion time. In the suggested approach, the execution duration of cloud jobs and the actual computing resources situation restrict the task set’s light-load and heavy-load functions. The algorithm is based on the fundamental idea of three-way decision-making, and separates the work set into three pieces according to the percentage of the two jobs inside it. The system focuses on three distinct task sets and determines an optimal scheduling strategy by employing the Max-Min algorithm for the task set containing a significant proportion of light-load jobs, the Min-Min algorithm for the task set with a substantial percentage of heavy-load studies, and a combination of the Min-Min and Max-Min algorithms for the task set that includes both light and heavy load tasks. Essential resources within the designated nodes are rearranged, and the task that is most suitable for the underutilized resources is assigned to them in order to achieve the objective of reducing the overall time required for completion. The experimental results conducted on the CloudSim simulation platform demonstrate that the CTSA-3WD algorithm, when compared to Min-Min, Max-Min, and selective scheduling algorithms, effectively enhances overall resource utilization, user service quality, and resource efficiency. Additionally, it enables improved load balancing across the entire system.