Grey Wolf Optimization and Crow Search Algorithm for Resource Allocation Scheme in Cloud Computing

Abstract

The computing resources are supplied by cloud computing on basis of cloud user requirements demand. Using virtualization and distributed computing, the resource allocation model is constructed to highlight the cloud services scalability. Nevertheless, a complex problem is created by the user, to manage the demand in the on-demand resource allocation model. Hence, a novel optimization approach is developed called Grey Wolf Optimization and Crow Search Algorithm (GWO-CSA) to resolve the problem in the resource allocation model. On the basis of the availability of the resources, the tasks are executed with the aid of the virtualization concept, minimize the response time. In a distributed manner, to the virtual machine, the tasks are allocated, to balance workload in the cloud. The proposed optimization method is exploited to attain effectual resource allocation. Finally, the developed method performance showed that it attains the utmost resource consumption, utmost memory consumption, and utmost CPU utilization, least skewness.