Title: A hybrid framework for job scheduling on the cloud through firefly and cuckoo search algorithm

Authors: Swagata Sarkar; S. Vimala; M. Vignesh; C. Sivakumaran

Addresses: Department of Artificial Intelligence and Data Science, Sri-Sairam-Engineering-College, West Tambaram, 600044, Chennai, India ' Department of Computer Science and Engineering, Panimalar Engineering College, Chennai, 602103, Tamil Nadu, India ' Department of Production, Science Academy Press, Chennai, 600017, Tamil Nadu, India ' Machine Learning Engineer, Photon Technologies, Chennai, 600017, Tamil Nadu, India

Abstract: Cloud Scheduler can reliably and effectively automate a lot of the time-consuming processes involved in maintaining cloud infrastructure. To deliver resources successfully, it is necessary to investigate and analyse the scheduling algorithms of recent trends. This problem can be solved by the use of metaheuristic scheduling algorithms. Nesterov's Accelerated Gradient can fix the problem of being stuck at a local minimum in the cuckoo search algorithm (CSA). In the proposed algorithm, Nesterov Accelerated Gradient (NAG) is used for the local search, and Levy Flights are used for the global search. The combination of NAG and CSA helps users save money and time. The simulation was done with the Clouds tool and three different real datasets. Multiple criteria will be used to schedule the different jobs that are on different servers. A hybrid optimisation algorithm is used to plan how the jobs will be done. Different requirements will be taken into account, and the environment will be simulated using the CloudSim tool.

Keywords: cloud; job scheduling; metaheuristic; cuckoo optimisation algorithm; open grid service.

DOI: 10.1504/IJCSM.2024.142729

International Journal of Computing Science and Mathematics, 2024 Vol.20 No.3, pp.197 - 207

Accepted: 25 Jun 2024
Published online: 19 Nov 2024 *

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