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Journal of Information and Optimization Sciences

(Since 1980)
Hybrid ·Peer-reviewed·ISSN (Online): 2169-0103·ISSN (Print): 0252-2667

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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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Journal of Information and Optimization Sciences
Open Access Research Article

Enhancing Quality of Service (QoS) and minimizing application placement delay in cloud-fog nodes through meta-heuristic algorithms

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pp. 1167–1177Vol. 44Issue 6September 2023DOI: 10.47974/JIOS-1455XML
Published Online:
11 Nov 2023
Article type:
Research Article
Language:
EN
Article no.:
JIOS-1455
Pages:
1167–1177

Abstract

Efficient module placement in Cloud-Fog computing enhances QoS and minimizes delay. Binary Particle Swarm Optimization (BPSO) and Binary Bat Algorithm (BBA), effective meta-heuristic algorithms, address dynamic fog complexities. This study models placement as binary optimization, incorporating resource availability and latency. BPSO and BBA optimize module placement, demonstrated through simulations improving response time, throughput, and resource utilization. These meta-heuristic methods surpass traditional techniques, optimizing cloud-fog systems, achieving superior QoS, and reduced delay.

Keywords

QoS improvementDelay minimizationapplication module placementCloud-Fog nodesMeta-heuristic algorithmsBPSOBBA

Subject Classifications

Primary 68T20Secondary 68M20

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