Date of Award
Dissertation - SCU Access Only
Santa Clara : Santa Clara University, 2021.
Doctor of Philosophy (PhD)
Computer Science and Engineering
Wireless Sensor Networks (WSNs) are being used in various applications, such as structural health monitoring and industrial control. Since energy efficiency is a major design factor, existing WSNs primarily rely on low-power, low-rate wireless technologies such as IEEE 802.15.4 and IEEE 802.15.1. In this thesis, we strive to tackle the challenges of developing accurate, ultra-high-rate WSNs based on the IEEE 802.11 (WiFi) standard. This thesis addresses the design challenges in two ways. First, we highlight the importance of the accurate conversion of analog signals to digital data and argue the importance of calibration to mitigate the conversion error of Analog to Digital Converters (ADCs). We design and develop calibration tools that are programmable, provide a wide range of current and voltage outputs, and can adapt to environmental variations. System prototyping and extensive experimental studies show that the proposed calibration tools can significantly improve measurement accuracy. In the second part of this thesis, we address the challenges of developing ultra-high-rate WSNs. We emphasize the requirements and challenges of Structural Health Monitoring (SHM) as an illustrative application domain. We show that assigning accurate timestamps (sub-μs accuracy) to samples (collected by ADC) introduces significant overhead, wastes precious payload bytes, and utilizes higher wireless communication bandwidth. We propose three encoding methods based on the distribution of inter-sampling intervals to reduce payload overhead. Also, we propose methods to reduce the energy consumption of nodes during their inactivity periods. In particular, since the 802.11 transceiver is the primary energy consumption source, we study two energy-efficiency methods: periodic association with the Access Point (AP), and extended-period beacon reception. In terms of processing outgoing packets, our work reveals that bypassing transport layer processing is essential to minimize the effect of packet processing on the sampling rate, and this enhancement also translates to a higher performance of timestamp encoding. By addressing the challenges of high-accuracy and high-rate sampling, the contributions of this work provide generic solutions towards developing WSNs for a wide range of applications such as Process Automation (PA), Factory Automation (FA), Building Automation System (BAS), intra-vehicle communication, and Wireless Avionics Intra-Communications (WAIC).
Li, Chia-Chi (Chelsey), "Taming the Challenges of Accurate and Ultra-High-Rate Data Collection in Wireless Sensing Systems" (2021). Engineering Ph.D. Theses. 36.