HYBRID RESOURCE ALLOCATION TECHNIQUE FOR CLOUD COMPUTING

Authors

  • Rakesh Pandit* & Dr Mona Dwivedi

Keywords:

Cloud Computing; Scheduling; Optimization Algorithm; Particle Swarm Optimization; Bat Optimization Algorithm; Service Level Agreement.

Abstract

The scheduling and distribution of resources are the two main factors in cloud computing that affect the overall quality of services. Since allocating resources inside a single cloud environment is such a complicated procedure, cloud computing necessitates the deployment of a resource allocation module that is both effective and efficient. While the complexity of the techniques used for allocation is further increased by the allocation of resources in a setting with many clouds. In the past, the multi-cloud environment's resources were allocated based on the demands of various workloads. It is vital to do research on the existing availability of resources and their skills before allocating resources to the activities that have been requested. As a result, the goal of this study is to offer an optimised hybrid resource allocation model that takes into account the job requirements, bandwidth needs, resource status, and distance. To distribute the resource, this model employs the particle swarm optimization technique and the bat optimization algorithm. The effectiveness of the suggested model is evaluated by simulation, and the outcomes are contrasted with those of conventional optimization techniques. With a minimal energy consumption of 168 kWh, the approach that has been provided can distribute the available resources across 400 activities in around 48 seconds. The performance of the suggested model is much superior than that of traditional methods in terms of the number of missed deadlines for assignments, the amount of resources required, the amount of energy utilized, and the amount of time provided.

Published

2022-12-31

How to Cite

Rakesh Pandit* & Dr Mona Dwivedi. (2022). HYBRID RESOURCE ALLOCATION TECHNIQUE FOR CLOUD COMPUTING. Harbin Gongye Daxue Xuebao/Journal of Harbin Institute of Technology, 54(12), 86–98. Retrieved from http://hebgydxxb.periodicales.com/index.php/JHIT/article/view/1441

Issue

Section

Articles