Nonlinear Consensus for Wireless Sensor Networks: Enhancing Convergence in Neighbor-Influenced Models
Rawad Abdulkhaleq Abdulmolla Abdulghafor, Yousuf Nasser Al Husaini, Abdullah Said Al-Aamri, Mohammad Yasir Bin Taleb Abrar, Alaa A. K. Ismaeel, Mohammed Abdulla Salim Al Husaini · International Journal of Advanced Computer Science and Applications · 2025
Wireless sensor networks (WSNs) are a modern technology that has revolutionized many industries thanks to their ability to collect and analyze information from surrounding environments and improve the performance of complex systems through the cooperation of a group of independent sensors to achieve common goals. Sensor clustering and agreement have wide applications in daily life, ranging from environmental monitoring and industrial control to healthcare and smart cities. However, the WSN system faces many challenges, one of the most prominent is achieving agreement between different sensors on a common state. This challenge is essential to enable successful cooperation between sensors in complex systems. Many previous research and models have been developed to address the problem of sensor agreement, such as the Neighbor-Influenced Timestep Consensus Model (NITCM), which was presented as a framework to achieve agreement effectively. In this paper, we propose a new technique to improve this model by using fractional force in the updating process. This leads to developing the Neighbor-Influenced Fractional Timestep Consensus Model (NIFTCM). This technique achieves faster convergence between sensors, which leads to improved efficiency in reaching agreement over previous techniques. This development aims to enhance the speed and stability of consensus processes in wireless sensor networks and make them more suitable for time-sensitive applications.