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At prior era, the task scheduling explorations utilized as a chief concern. The swarm-based optimization methods are introduced to advance the task scheduling in huge network. The optimization strategy for task scheduling examination is developed to obtain optimized solutions for achieving optimal task scheduling. Consequently, the optimal strategy has an auxiliary mechanism in examination by means of general task scheduling technique. In a while, obtaining the optimized schedulers by exploiting swarm-based techniques, the best task schedulers are unbiased during their substance loads by exchanging the supplementary loads among machines. In the course of the numerous databases, modeling, clustering, and task scheduling concerns may occur, and task scheduling has become one of the significant scrutinize concerns. This paper illustrated numerous existing task scheduling strategies such as fuzzy theory; optimization-related schemes, and machine learning and relationship amid strategies. Extensive assessment of vast variety of task scheduling and optimization schemes related on some effective features such as execution time, cost, energy, and overhead is notified in tabular arrangement. Task scheduling and numerous optimization methods have been described. This paper dissertates the assessment of numerous task scheduling mechanisms. Later than the examination of optimal task scheduling mechanisms, the assessment of methods motivates us to be familiar with the issues and concerns in task scheduling, and optimization methods.
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