Enhanced Jaya Algorithm for Quality-of-Service-Aware Service Composition in the Internet of Things

The Internet of Things (IoT) has shifted how devices and services interact, resulting in diverse innovations ranging from health and smart cities to industrial automation. Nevertheless, at its core, IoT continues to face one of the major tough tasks of Quality of Service-aware Service Composition (QoS-SC), as these IoT settings are normally transient and unpredictable. This paper proposes an improved Jaya algorithm for QoS-SC and focuses on optimizing service selection with a balance between the main QoS attributes: execution time, cost, reliability, and scalability. The proposed approach was designed with adaptive mechanisms to avoid local optima stagnation and slow convergence and thus assure robust exploration and exploitation of the solution area. Incorporating these enhancements, the proposed algorithm outperforms prior metaheuristic approaches regarding QoS satisfaction and computational efficiency. Extensive experiments conducted over diverse IoT scenarios show the algorithm's scalability, demonstrating that it can achieve faster convergence with superior QoS optimization.

@article{SHI2025,
  title     = {Enhanced Jaya Algorithm for Quality-of-Service-Aware Service Composition in the Internet of Things},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {16},
  number    = {1},
  year      = {2025},
  publisher = {The Science and Information Organization},
  author    = {Yan SHI},
  doi       = {10.14569/IJACSA.2025.0160172},
  url       = {https://doi.org/10.14569/IJACSA.2025.0160172}
}