Assessment and Future Directions for Clustering Optimization in Cloud Computing

Abstract

The current cloud technology offers access to a sharable resource such as networks, storage servers, applications, and other services. The way businesses manage their data, save their files, and use their apps has been completely transformed by technology. Nonetheless, the effective and efficient use of hardware and software resources is essential to the success of cloud computing. In a cloud environment where several processes are executing simultaneously, task scheduling and virtual machine clustering become crucial to ensuring maximum performance. Efficient task scheduling methods enable the distribution of resources among various tasks in a way that maximizes overall throughput. To provide a more effective and scalable computing environment, virtual machines are grouped together in a virtual machine cluster. Metaheuristic techniques need to be introduced for effectiveness of TS optimization. By intelligently and effectively navigating the search area, these algorithms are utilized to find the best answers to challenging scheduling issues. A hybrid algorithm is one that combines the advantages of two or more different algorithms. A hybrid algorithm’s success depends on the thoughtful selection and blending of various algorithms and parameters. Several job scheduling strategies, popular cloud simulators will be presented and examine the outcomes in light of the important criteria in this study. In order to assist academics and practitioners in selecting the best algorithm for their unique needs, this study attempts to shed light on the advantages and disadvantages of various algorithms.