Recent Task Scheduling-based Heuristic and Meta-heuristics Methods in Cloud Computing: A Review
Manish Chhabra, Shajahan Basheer · 2022
With the availability of maximum bandwidth INTERNET connectivity, CC (cloud computing) applications have been explored in the current years. The demand for highly effective JS (job scheduling) methods has increased as more and more uses are being run over the cloud and as the total consumer base of several cloud platforms grows. The scheduling methods task is to choose the jobs’ order of execution that consumes the fewest resource, such as memory, time, and, processing. The consumer typically needs more services and extremely high efficacy. An effective scheduling method aids in appropriate resource usage. The cost and make span have been used extensively in the literature as influencing elements for scheduling dependent jobs. The performance issues with dependent TS (task scheduling) have been considered in the previous work, however, failure rate and storage cost issues were not covered. The main motive of this work is to review the custom of heuristic and meta-heuristic methods for task scheduling in cloud computing. This analysis defines an extensive review of TS methods in cloud computing such as; Min-Min, Max-Min, GA (genetic algorithm), PSO (particle swarm optimization), Bee’s life method, etc.