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DOI: 10.14569/IJACSA.2023.0140997
PDF

A QoS-Aware Resource Allocation Method for Internet of Things using Ant Colony Optimization Algorithm and Tabu Search

Author 1: Shuling YIN
Author 2: Renping YU

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 14 Issue 9, 2023.

  • Abstract and Keywords
  • How to Cite this Article
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Abstract: In today's computing era, the Internet of Things (IoT) stands out for its implementation of automation, high-quality ecosystems, creative and efficient services, and higher productivity. IoT has found applications in various fields, such as education, healthcare, agriculture, military, and industry, where diverse resource requirements present a major challenge. To address this issue, we propose a novel QoS-aware resource allocation method for IoT systems. Our approach combines the Ant Colony Optimization (ACO) and Tabu Search (TS) algorithms to manage resources effectively, minimize energy consumption, reduce communication delays, and enhance overall system performance. Experimental results demonstrate the efficiency and effectiveness of our approach, with significant improvements in QoS metrics compared to traditional methods. By merging ACO and TS algorithms, our research contributes to the advancement of IoT capabilities, energy conservation, and business optimization.

Keywords: Internet of things; resource allocation; virtualization; Ant Colony Optimization; Tabu Search

Shuling YIN and Renping YU, “A QoS-Aware Resource Allocation Method for Internet of Things using Ant Colony Optimization Algorithm and Tabu Search” International Journal of Advanced Computer Science and Applications(IJACSA), 14(9), 2023. http://dx.doi.org/10.14569/IJACSA.2023.0140997

@article{YIN2023,
title = {A QoS-Aware Resource Allocation Method for Internet of Things using Ant Colony Optimization Algorithm and Tabu Search},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2023.0140997},
url = {http://dx.doi.org/10.14569/IJACSA.2023.0140997},
year = {2023},
publisher = {The Science and Information Organization},
volume = {14},
number = {9},
author = {Shuling YIN and Renping YU}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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