Abstract
With the increasing integration of sensor networks in various domains, optimizing their performance has become a crucial challenge. This paper presents an intelligent Smart Multi-Attribute Decision-Making (SMADM) approach designed to enhance sensor network performance. By leveraging advanced algorithms and real-time data processing, the proposed approach aims to improve decision-making processes, ensuring efficient sensor network management. The study highlights the effectiveness of the SMADM approach through simulation results, showcasing significant improvements in network reliability, data accuracy, and overall system efficiency. The consistent poor performance in our communication network occurs when the wireless sensor does not effectively reduce packet loss and interference, leading to high costs. This issue is addressed by improving sensor network performance using the SMADM approach. This involves characterizing increased energy consumption, interference, and packet loss, which contribute to reduced performance, and designing a rule base for the SMADM approach to mitigate these issues. A SIMULINK model for wireless sensor networks (WSN) is developed, along with an algorithm to implement the process. Validation results indicate that conventional packet loss peaks at 30Kb/s on day 4, while sensor 1 experiences a reduced loss of 27.98Kb/s. Incorporating sensor 2 decreases packet loss to 28.6Kb/s, and sensor 3 further reduces it to 27.39Kb/s, demonstrating that sensor 3 is the most effective for improved network performance. Additionally, conventional power consumption is highest at 0.5W on day 1. With sensor 1, it drops to 0.4663W, with sensor 2 to 0.4767W, and with sensor 3, it reduces to 0.456W, making sensor 3 very efficient. JCSRE 8.1 (1-19) Download Citations APA