Title: Efficient VM selection from overutilised PMs: a grasshopper-based approach for cloud resource optimisation

Authors: Jaspreet Singh; Navpreet Kaur Walia

Addresses: Department of Computer Science and Engineering, Chandigarh University, Mohali Punjab, India ' Department of Computer Science and Engineering, Chandigarh University, Mohali Punjab, India

Abstract: Efficient resource allocation is critical for optimising performance and controlling operational costs in cloud computing environments. In this proposed work, a comprehensive two-segment study is presented, in which the first segment relies on grasshopper-based optimisation while the second segment relies on conditional-MBFD. The grasshopper algorithm effectively addresses the intricate challenge of selecting virtual machines (VMs) from overutilised physical machines (PMs) in dynamic cloud environments, thus reshaping resource allocation paradigms. The contributions outlined in this proposed work are rigorously examined through comprehensive comparative evaluations. These evaluations compare grasshopper-based approach against well-established optimisation algorithms such as artificial bee colony (ABC), particle swarm optimisation (PSO), and firefly. Additionally, the proposed work strategies are validated against state-of-the-art algorithms. These meticulous comparisons highlight the resounding superiority of proposed strategies in minimising power consumption, reducing SLA violations, and optimising resource utilisation in cloud computing environments. Meanwhile, the conditional-MBFD algorithm astutely fine tunes resource allocation.

Keywords: allocation and migration; cloud computing; grasshopper optimisation algorithm; GOA; swarm intelligence; SI.

DOI: 10.1504/IJBIC.2025.149534

International Journal of Bio-Inspired Computation, 2025 Vol.26 No.3, pp.169 - 180

Received: 27 Nov 2023
Accepted: 12 Nov 2024
Published online: 05 Nov 2025 *

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