A Task Scheduling Approach for Cloud Resource Management
Yong Shi, Kun Suo, Steven M. Kemp, Jameson Hodge
Abstract
As an emerging subfield of computer science, cloud computing is increasingly relevant to both academia and numerous industries as a solution to high barriers of entry in configuring and maintaining computing hardware and inflexible platform constraints. One vital aspect of cloud computing is task scheduling, which deals with the strategies in assigning tasks to computing resources. There are numerous commonly used task scheduling algorithms defined by their performance trade-off among various factors such as cutting down the completion time and increasing throughput. In this paper, an algorithm called BMin is designed to augment the performance for algorithm Min-min. Using the CloudSim package as a framework for simulating cloud processes, we conduct our experiments, yielding experimental results that demonstrate decreased completion time, increased throughput, and improved load balancing of resources—outperforming the classical algorithm.