Hybrid resource allocation and task scheduling scheme in cloud computing using optimal clustering techniques

Abstract

In diverse parallel and distributed computing systems, resource allocation is the progression of distributing consumer tasks for processing elements during execution in which some performance intentions are optimised. This research explains about the innovative resource allocation algorithm for the computing grid environment. In the scheduling problem of independent task in cloud computing, summarise other scheduling algorithms introduce a modified fuzzy C-means (MFCM) clustering algorithm. Our algorithm abstract resource into a model to analyse these characteristics of resources with the MFCM algorithm. From that our proposed technique could decrease a execution time and memory space allocation of the system. For the optimal selection of virtual machines hybrid whale genetic (HWGA) optimisation algorithm is used. Since the virtual machines are optimally selected on the basis of feature values, our proposed method provides reduced load balancing as well as improved parallel execution of tasks.