A Critical Assessment of Task Scheduling Algorithms in Cloud Computing: A Comparative Approach

Every IT-enabled service is intended to be provided as a utility by cloud computing. It is dedicated to providing all needs related to compute, storage, development, etc., in an economical and effective manner, whether it be for hardware or software. The way a cloud distributes user jobs, or tasks, across its resources determines how well services are delivered. A cloud provider has a wide variety of work scheduling methods to select from. The four most adaptable and promising work scheduling algorithms are chosen in this research, i.e., Particle Swarm Optimization (PSO), First Come First Server (FCFS), Shortest Job First (SJF) and Round-Robin (RR) scheduling to figure out how well they perform in comparison. From an experimental perspective, the CloudSim 3.0.3 toolbox is used to simulate these methods under varying workload conditions. Additionally, a collection of metrics is computed, and these measures are used to compare and evaluate the aforementioned algorithms.