Open Access

ARTICLE

Battle Royale Optimization-Based Resource Scheduling Scheme for Cloud Computing Environment

Lenin Babu Russeliah^1,*, R. Adaline Suji², D. Bright Anand³

1 Data Scientist, Conversight.ai, Indiana, USA
2 Department of Computer Science and Engineering, KIT-KalaignarKarunanidhi Institute of Technology, Coimbatore, 641 402, India
3 Department of Computer Science and Engineering, Narayana Engineering College, Gudur, 524101, Andhra Pradesh, India

* Corresponding Author: Lenin Babu Russeliah. Email:

Computer Systems Science and Engineering 2023, 46(3), 3925-3938. https://doi.org/10.32604/csse.2023.034727

Received 25 July 2022; Accepted 13 November 2022; Issue published 03 April 2023

Abstract

Cloud computing (CC) is developing as a powerful and flexible computational structure for providing ubiquitous service to users. It receives interrelated software and hardware resources in an integrated manner distinct from the classical computational environment. The variation of software and hardware resources were combined and composed as a resource pool. The software no more resided in the single hardware environment, it can be executed on the schedule of resource pools to optimize resource consumption. Optimizing energy consumption in CC environments is the question that allows utilizing several energy conservation approaches for effective resource allocation. This study introduces a Battle Royale Optimization-based Resource Scheduling Scheme for Cloud Computing Environment (BRORSS-CCE) technique. The presented BRORSS-CCE technique majorly schedules the available resources for maximum utilization and effectual makespan. In the BRORSS-CCE technique, the BRO is a population-based algorithm where all the individuals are denoted by a soldier/player who likes to go towards the optimal place and ultimate survival. The BRORSS-CCE technique can be employed to balance the load, distribute resources based on demand and assure services to all requests. The experimental validation of the BRORSS-CCE technique is tested under distinct aspects. The experimental outcomes indicated the enhancements of the BRORSS-CCE technique over other models.

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Keywords

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