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An Optimal Hybrid Firefly Optimization and Min-Min Algorithm for Dynamic Resource Management in Fog Nodes for IoT Networks
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V. Mokhtari   , N. Mikaeilvand , A. Mirzaei , B. Nouri-Moghaddam , S. Jahanbakhsh Gudakahriz |
| Department of Computer Science and Mathematics, CT.C., Islamic Azad University, Tehran, Iran. |
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Abstract: (13 Views) |
| With the proliferation of Internet of Things (IoT) devices, predicted to reach 75 billion by 2025, dynamic resource management in Fog Nodes faces challenges in delay-sensitive applications such as smart cities and autonomous vehicles. This paper presents a hybrid framework that integrates the Firefly Optimization Algorithm (FFO) for Virtual Machine (VM) migration and the Min-Min algorithm for rapid convergence probability with fog computations. Instead of generating a completely random population, a chromosome is generated using the greedy Min-Min algorithm, providing a high-quality initial solution, while FFO optimizes resource allocation and VM migration. Simulations on the dataset showed that the proposed method -- based on the Min-Min algorithm and the FFO algorithm for VM migration -- decisively confirms its effectiveness in IoT Fog Nodes. This method reduces energy consumption by up to 44.39%, VM migration by up to 72.34%, the number of active hosts by up to 34.36%, and improves delay by 25% compared to FFD baselines. Such performance not only establishes a multi-objective balance between energy, stability, and Quality of Service (QoS) in delay-sensitive applications like smart cities and autonomous vehicles but also fills the gap of integrating dynamic topology and resource management in the literature and provides a scalable solution for green 5G computing. Despite limitations such as dependency on simulation, it is suggested. |
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| Keywords: Firefly Optimization, Min-Min Algorithm, Fog Computing, Dynamic Resource, Management, Internet of Things, VM Migration. |
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Type of Study: Research |
Subject:
General
Received: 2025/01/20 | Accepted: 2025/03/26 | Published: 2025/10/9
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