Reliability-based Diagnosis of Wireless Sensor Network Communication Quality Using Readily Available Data

A densely distributed wireless sensor network has the potential to provide rich information, with its lowcost and on-board computational capabilities providing significant advantage over wired sensor networks. However, communication between sensors in such networks can be challenging. Especially for wireless sensors located within civil infrastructures, which are usually made of steel and concrete, providing reliable radio communication is a key issue. Assessing network communication quality before and after finalizing a deployment is needed to achieve a robust sensor network for structural health monitoring. A framework of reliability-based diagnosis of wireless sensor network communication quality is proposed. Using radio signal strength and link quality indicators, an empirical expression for packet reception rate is derived. First-order reliability methods and Monte Carlo Simulation are further used to perform component-based reliability analyses. Predetermined information on radio signal properties enhances the applicability of the approach by requiring smaller data sets for parameter fitting. By performing the proposed analysis in complex sensor networks, an optimized sensor topology can be achieved. Moreover, periodic analyses will help with understanding the impact of temporal environmental effects on packet reception. This paper utilizes an application tool developed for the Imote2 smart sensor platform based on the Illinois Structural Health Monitoring Project Services Toolsuite.