Optimization of Resource Allocation in Cloud Computing by Grasshopper Optimization Algorithm

Abstract

Cloud computing system due to Pay-Per-Use Model has been popular among Cloud resource users. However, large volume of resource and requests from users have made the issue of resource allocation challenging in this kind of system. Therefore, the present paper aims to recognize the role of innovative Grasshopper Optimization Algorithm (GOA) and strongly highlights the significance of such an algorithm for optimized resource allocation in a Cloud computing environment. To do so, the proposed algorithm (i.e., GOA) was simulated with MATLAB and eight datasets were used. Moreover, GOA was compared with GA and SEIRA algorithms in order to have precise evaluation of its performance. Results strongly acknowledged the application of the proposed GOA and highlighted its high ability to solve the resource allocation problem in Cloud computing. Findings also revealed that the functions designed for the basic operators of the GOA could appropriately look into the space of the problem response, resulting in optimization of the discovered responses, and finally providing opportunities to obtain an acceptable response regarding the allocation problem. It was undeniably recommended that other optimization algorithms can be investigated and compared with GOA in order for the users and service providers to be armed with practical solutions concerning the resource allocation problem.