Title: Enhancing the job scheduling procedure to develop an efficient cloud environment using near optimal clustering algorithm
Authors: R. Suganya; Niju P. Joseph; R. Rajadevi; S. Ramamoorthy
Addresses: Department of Information Technology, Sri Krishna College of Technology, Tamil Nadu, India ' Department of Computer Science, CHRIST (Deemed to be University), Bengaluru, India ' Department of Information Technology, Kongu Engineering College, Perundurai, India ' Department of Computer Science and Engineering, SRM Institute of Science and Technology, Kattankulathur, Kanchipuram, Tamilnadu, India
Abstract: In this internet era, cloud computing and there are various problems in the cloud computing, where the consumers as well as the service providers facing in their day to day cloud activities. Job scheduling problem plays a vital role in the cloud environment. To provide an efficient job scheduling environment, it is necessary to perform efficient resource clustering. In this regard, the proposed system, concentrated on the resource clustering methodology by proposing an efficient resource clustering algorithm named identicalness split up periodic node size (ISPNS) in the cloud environment. The algorithm proposed helps in forming resource clusters with the help of cloud environment. The proposed system is compared with the existing systems to justify the performance of the proposed resource clustering algorithm and it produces near optimal solution for the resource clustering problem which helps to provide an efficient job scheduling in cloud environment.
Keywords: cloud computing; resource clustering; identicalness; split up; node size.
International Journal of Cloud Computing, 2023 Vol.12 No.2/3/4, pp.134 - 147
Received: 04 Feb 2020
Accepted: 07 Apr 2020
Published online: 14 May 2023 *