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Journal of Information and Optimization Sciences cover
Hybrid ·Peer-reviewed·ISSN (Online): 2169-0103·ISSN (Print): 0252-2667

WoS  JIF 2026 : 0.4 (Q4)

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Monthly Journal: Publishes theoretical and applied research on topics in information and optimization sciences.

Issues up to 2022 co-published with and available at:Taylor & Francis
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Open Access Research Article

Energy-efficient resource allocation in fog computing using hybrid genetic algorithm-based VM consolidation

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pp. 1871–1879Vol. 46Issue 6September 2025DOI: 10.47974/JIOS-2016XML
Received:
10 Dec 2024
Published Online:
30 Sep 2025
Article type:
Research Article
Language:
EN
Article no.:
JIOS-2016
Pages:
1871–1879

Abstract

Fog computing brings cloud-like services closer to data sources, improving responsiveness but also introducing challenges like high energy consumption and inefficient resource use. To tackle this, VM consolidation using live migration is employed to enhance energy efficiency and resource management. This paper introduces a hybrid Genetic Algorithm model that combines various selection strategies—Tournament, Rank, SUS, Truncation, and Roulette-Wheel—to optimize CPU and memory usage during VM consolidation. By using heuristics for population generation, fitness evaluation, and load balancing, the model minimizes active physical machines and adapts to workload changes, improving efficiency in fog data centers.

Keywords

Subject Classifications

68M2068U2068T20

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