Optimized Probabilistic Sink Node Deployment for Enhanced Performance in Wireless Sensor Networks

Abstract

This paper presents an innovative mechanism to deploy sink nodes in Wireless Sensor Networks (WSN), which play an essential role in the gathering sensed data from sensor nodes across diverse applications. Our mechanism is different from existing mechanisms, which deploy sink nodes based on the residual status of buffer and energy of the sensor nodes. Instead, proposed mechanism’s sink node deployment is decided based on the optimal probabilistic metrics related to buffer and energy status during data processing; aim to extend the network performance with respect to risk of buffer overflow and energy consumption. We analyse and validate the performance of the proposed work through simulation and compared the results with existing residual-based sink node deployment mechanisms. The results indicate the signification extension in the performance in terms of energy, packet loss and lifetime by mitigating bottlenecks at nodes. The work contributes to the improvement of WSN design and deployment mechanisms by significantly enhancing the performance and reliability of the network.