 A hybrid PSO optimised virtual machine scheduling algorithm in cloud computingP. Karthikeyan and Rinta Soni International Journal of Business Information Systems, 2020, vol. 34, issue 4, 536-559 Abstract: The service to the end user in cloud computing is offered as virtual machine instances as demanded for a specified duration of time and billed on pay per use basis. A major problem faced in cloud computing is the virtual machine scheduling problem. The existing algorithms efficiently cannot satisfy the requirements with respect to resource utilisation, bandwidth utilisation, and cost. Also, most of them are of the fixed type which leads to wastage of resources. To overcome these problems, the hybrid particle swarm optimisation (HPSO) algorithm is proposed by efficiently allocating the resources to the users. This algorithm combines the genetic algorithm (GA) and the variable neighbourhood search (VNS) algorithm with the particle swarm optimisation (PSO) technique to increase the utilisation rate of the virtual machine as well as to minimise the total completion time. The proposed system is evaluated by performing simulations. The experimental results show that the proposed algorithm minimises the total completion time and increase the resource utilisation than PSO, GA and VNS algorithm. Keywords: cloud computing; particle swarm optimisation; PSO; variable neighbourhood search; VNS; genetic algorithm; GA. (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:ids:ijbisy:v:34:y:2020:i:4:p:536-559 Access Statistics for this article More articles in International Journal of Business Information Systems from Inderscience Enterprises Ltd |
Is your work missing from RePEc? Here is how to contribute.
Questions or problems? Check the EconPapers FAQ or send mail to .
EconPapers is hosted by the
School of Business at Örebro University.