On the topology effects in wireless sensor networks based prognostics and health management

TL;DR

This paper investigates how different wireless sensor network topologies affect energy efficiency and diagnostic accuracy in prognostics and health management, using multiple algorithms to evaluate performance.

Contribution

It compares four network topologies and their impact on diagnostics in WSNs, highlighting the importance of topology design for energy conservation and data quality.

Findings

Topology significantly influences energy consumption and data accuracy.

Hierarchical topology offers a good balance between energy efficiency and diagnostic performance.

Decentralized topology shows robustness in data transmission under node failures.

Abstract

In this work, we consider the usage of wireless sensor networks (WSN) to monitor an area of interest, in order to diagnose on real time its state. Each sensor node forwards information about relevant features towards the sink where the data is processed. Nevertheless, energy conservation is a key issue in the design of such networks and once a sensor exhausts its resources, it will be dropped from the network. This will lead to broken links and data loss. It is therefore important to keep the network running for as long as possible by preserving the energy held by the nodes. Indeed, saving the quality of service (QoS) of a wireless sensor network for a long period is very important in order to ensure accurate data. Then, the area diagnosing will be more accurate. From another side, packet transmission is the phase that consumes the highest amount of energy comparing to other activities in the network. Therefore, we can see that the network topology has an important impact on energy efficiency, and thus on data and diagnosis accuracies. In this paper, we study and compare four network topologies: distributed, hierarchical, centralized, and decentralized topology and show their impact on the resulting estimation of diagnostics. We have used six diagnostic algorithms, to evaluate both prognostic and health management with the variation of type of topology in WSN.