Efficient Protocol Selection and Estimation for Diverse Wireless Sensor Network Applications

Abstract

Wireless sensor networks (WSNs) have become an essential technology for a wide range of applications, from environmental monitoring and smart cities to industrial automation and healthcare. A key challenge in designing efficient WSNs is the selection of appropriate communication protocols that can optimize performance metrics such as energy consumption, latency, and reliability, while considering the diverse requirements and constraints of different application scenarios.

In this paper, we present a comprehensive study on the problem of efficient protocol selection and estimation in WSNs, with a focus on addressing the heterogeneity of application requirements. We first conduct an extensive review of the state-of-the-art in WSN communication protocols, categorizing them based on their design principles and target application scenarios.

We then propose a novel multi-stage framework for protocol selection that employs a combination of multi-criteria decision-making (MCDM) and machine learning techniques. The framework first classifies the target WSN application into one of several predefined categories, and then selects the most suitable protocol for that application using a customized MCDM approach.

To further enhance the protocol selection process, we develop a Bayesian network-based estimation model that can predict the performance of the selected protocols under various environmental and network conditions. The model leverages the insights gained from the protocol characterization process and the application-specific MCDM analysis.

We evaluate the proposed framework using real-world WSN deployment data from multiple application domains, including environmental monitoring, industrial automation, and smart city infrastructure. The results demonstrate the effectiveness of the framework in selecting the most suitable protocols for diverse application scenarios and accurately predicting their performance.

The proposed framework can serve as a valuable tool for WSN designers and operators to make informed decisions regarding protocol selection and deployment, ultimately leading to improved overall system performance and efficiency.