Efficient Protocol Selection and Estimation in Wireless Sensor Networks

Abstract

Wireless sensor networks, or WSNs, are rapidly being adopted by a number of industries, including industrial automation and environmental monitoring. Building effective WSNs involves a lot of work, including selecting the appropriate communication techniques to maximise performance metrics like power consumption, latency, and dependability. In-depth analysis of wireless sensor networks is the focus of our study's protocol evaluation and selection process.

We start with a detailed examination of current best practices for WSN communication protocols, classifying them according to their use cases and tenets. Next, we present a novel protocol selection algorithm that takes into account the characteristics of the current protocols as well as the particular needs and constraints of the WSN implementation.

The framework uses a multi-criteria decision-making, or MCDM, method to rank the protocols based on several performance parameters, including cost, validity, latency, and energy economy. We then design a Bayesian network-based estimation model to predict the performance of the chosen protocols under different network and environmental conditions.

We assess the proposed framework and show that it can choose the best protocols for various use scenarios using actual WSN deployment data. The results demonstrate that our concept performs better than conventional protocol selection techniques in terms of overall performance and system adaptability. The framework can be useful to WSN designers and operators when choosing and implementing protocols.