A System-Level Methodology for the Design of Reliable Low-Power Wireless Sensor Networks.

Oussama Brini,Dominic Deslandes,Frederic Nabki

doi:10.3390/s19081800

Oussama Brini, Dominic Deslandes + Show 1 more

Open Access

https://doi.org/10.3390/s19081800

Copy DOI

Abstract

Innovative Internet of Things (IoT) applications with strict performance and energy consumption requirements and where the agile collection of data is paramount are arising. Wireless sensor networks (WSNs) represent a promising solution as they can be easily deployed to sense, process, and forward data. The large number of Sensor Nodes (SNs) composing a WSN are expected to be autonomous, with a node’s lifetime dictated by the battery’s size. As the form factor of the SN is critical in various use cases, minimizing energy consumption while ensuring availability becomes a priority. Moreover, energy harvesting techniques are increasingly considered as a viable solution for building an entirely green SN and prolonging its lifetime. In the process of building a SN and in the absence of a clear and well-rounded methodology, the designer can easily make unfounded and suboptimal decisions about the right hardware components, their configuration, and reliable data communication techniques, such as automatic repeat request (ARQ) and forward error correction (FEC). In this paper, a methodology to design, configure, and deploy a reliable ultra-low power WSNs is proposed. A comprehensive energy model and a realistic path-loss (PL) model of the sensor node are also established. Through estimations and field measurements it is proven that, following the proposed methodology, the designer can thoroughly explore the design space and the make most favorable decisions when choosing commercial off-the-shelf (COTS) components, configuring the node, and deploying a reliable and energy-efficient WSN.

Highlights

Wireless sensor networks (WSNs) are increasingly being deployed in a broad range of applications, such as home automation [1,2], smart cities [3,4], industrial automation [5,6,7,8,9,10], and precision agriculture [11,12,13]
It can be seen that increasing the bandwidth, B, in the urban area to achieve a these measurement results, it can be seen that increasing the bandwidth, B, in the urban area to higher data rate has a more pronounced impact on range (i.e., bit error rate (BER) ≤ 0.1) when compared 12 with the of 28 suburban area, which can be explained by the previously measured higher noise density
The noise power in a given bandwidth is expressed by achieve a higher data rate has a more pronounced impact on range (i.e., BER ≤ 0.1) when compared with the suburban area, which can be explained by the previously measured higher noise density

Summary

Introduction

Wireless sensor networks (WSNs) are increasingly being deployed in a broad range of applications, such as home automation [1,2], smart cities [3,4], industrial automation [5,6,7,8,9,10], and precision agriculture [11,12,13]. This is because WSNs are low cost and composed of easy to deploy battery-operated devices. Renewable energy sources, such as vibration, light, or heat can be considered for powering a SN when several harvesters are used and a proper dimensioning of the energy buffer is carried-out

Methods

Results

Conclusion