Use of whale optimization algorithm and its variants for cloud task scheduling: a review

Scheduling is an important issue in distributed computing platforms which decides the allocation of resources to the user-submitted tasks to optimize certain scheduling objectives. Due to the dynamic nature of cloud resources and the growing size of tasks and requests, there are serious problems with resource usage, system performance, task allocation, load balancing, and other factors. To find near-optimal solutions to task scheduling issues, considerable researchers have used various kinds of scheduling strategies. But compared to traditional heuristics and exact scheduling approaches, meta-heuristic scheduling algorithms produce the most successful results. The whale Optimization Algorithm (WOA) is a well-known meta-heuristic method, which has been revealed useful for resolving a wide variety of optimization problems. WOA is suitable for load balancing, workflow scheduling, and dynamic task scheduling. This study presents a detailed analysis of various types of WOA-based scheduling strategies published during the years 2015-2022 using comprehensive evaluation measures in the fog and cloud computing environment.