Open Access

ARTICLE

Resource Allocation Using Phase Change Hyper Switching Algorithm in the Cloud Environment

J. Praveenchandar^1,*, A. Tamilarasi²

1 Anna University, Chennai, 600025, Tamilnadu, India
2 Department of Computer Applications, Kongu Engineering College, Perundurai, 638052, Tamilnadu, India

* Corresponding Author: J. Praveenchandar. Email:

Intelligent Automation & Soft Computing 2022, 34(3), 1839-1850. https://doi.org/10.32604/iasc.2022.026354

Received 23 December 2021; Accepted 15 February 2022; Issue published 25 May 2022

Abstract

Cloud computing is one of the emerging technology; it provides various services like Software as a Service, Platform as a Service, and Infrastructure as a Service on demand. It reduces the cost of traditional computing by renting the resources instead of buying them for a huge cost. The usage of cloud resources is increasing day by day. Due to the heavy workload, all users cannot get uninterrupted service at some time. And the response time of some users also gets increased. Resource allocation is one of the primary issues of a cloud environment, one of the challenging problems is improving scheduling performance and reducing waiting time performance. In this research work, a new approach is proposed to distribute the heavy workload to overcome this problem. In addition to that, the resource allocation of dynamic user requests is also taken into study. The Max-Min scheduling algorithm is modified concerning Dynamic Phase Change Memory (DPCM), and the Hyper switching algorithm is implemented to speed up the resource allocation process. The proposed DPCM algorithm provides efficient performance, improves scheduling results, and minimizes the waiting time. In the experimentation analysis, it is observed that this proposed approach optimizes the response time and waiting time of the dynamic user requests and distributes the workloads effectively, compared with other existing approaches. So the performance of the resource allocation process is improved, which enhances the efficiency of the cloud system.

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Keywords

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