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

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.

@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},
  volume    = {14},
  number    = {9},
  year      = {2023},
  publisher = {The Science and Information Organization},
  author    = {Shuling YIN and Renping YU},
  doi       = {10.14569/IJACSA.2023.0140997},
  url       = {https://doi.org/10.14569/IJACSA.2023.0140997}
}