Enhancing Sensor Network Data Quality via Collaborated Circuit and Network Operations

Abstract

In many applications, the quality of data gathered by sensor networks is directly related to the signal-to-noise ratio (SNR) of the sensor data being transmitted in the networks. Different from the SNR that is often used in measuring the quality of communication links, the SNR used in this work measures how accurately the data in the network packets represent the physical parameters being sensed. Hence, the signal here refers to the physical parameters that are being monitored by sensor networks; the noise is due to environmental interference and circuit noises at sensor nodes, and packet loss during network transmission. While issues affecting SNR at sensor nodes have been intensively investigated, the impact of network packet loss on data SNR has not attracted significant attention in sensor network design. This paper investigates the impact of packet loss on sensor network data SNR and shows that data SNR is dramatically affected by network packet loss. A data quality metric, based on data SNR, is developed and a cross-layer adaptive scheme is presented to minimize data quality degradation in congested sensor networks. The proposed scheme consists of adaptive downsampling and bit truncation at sensor nodes and intelligent traffic management techniques at the network level. Simulation results are presented to demonstrate the validity and effectiveness of the proposed techniques.

Keywords

• sensor network
• signal-to-noise ratio
• adaptive circuits
• analog-to-digital conversion