Effective Analysis of Task Scheduling as Well as Load Balancing Schemes and Algorithms in Cloud Computing

Cloud computing (CC) is an emerging technology to provide efficient processing, storage, development platforms, web services, and analytics services for the end-users and organizations to improve their infrastructure and service types fastly. As the need for higher processing power increases, large amounts of data cause a significant burden on the CC environment. Hence, the load-balancing and task-scheduling is considered as an NP-hard problem in CC and diverse solutions exist in the literature to overcome this issue. In this review, several existing load balancing and task scheduling algorithms in CC are investigated to gain a deeper insight into task scheduling and load balancing techniques. Specifically, this review analyzes 25 recent research papers by focusing on advanced heuristic and meta-heuristic algorithms, and their achievements. Additionally, the review focuses on the technologies used, research gaps, pros and cons of different techniques, evaluation metrics, and forthcoming opportunities. Besides, the review provides more significant information about the metaheuristic multi-objective optimization techniques developed to deal with multiple conflicting goals addressing task scheduling and load balancing problems in different CC environments. Moreover, the proposed review facilitates the innovation of the most effective and practical solutions for optimizing the cloud network resources in the future.