CSE Doctoral Dissertation Defense: Dolvara Gunatilaka

Feb 7
2:00 p.m.
4:00 p.m.
Jolley Hall, Room 309

“High Performance Wireless Sensor-Actuator Networks for the Industrial Internet of Things”

Dolvara Gunatilaka
Adviser: Chenyang Lu

Wireless Sensor-Actuator Networks (WSANs) enable cost-effective communication for Industrial Internet of Things (IIoT). To achieve predictability and reliability demanded by industrial applications, industrial wireless standards (e.g., WirelessHART) incorporate a set of unique features such as a centralized management architecture, Time Slotted Channel Hopping (TSCH), and conservative channel selection. However, those features also incurs significant degradation in performance, efficiency, and agility. To overcome these key limitations of existing industrial wireless technologies, this thesis work develops and empirically evaluates a suite of novel network protocols and algorithms.

The primary contributions of this thesis are four-fold. (1) We first build an experimental testbed realizing key features of the WirelessHART protocol stack, and perform a series of empirical studies to uncover the limitations and potential improvements of existing network features. (2) We then investigate the impacts of the industrial WSAN protocol's channel selection mechanism on routing and real-time performance, and present new channel and link selection strategies that improve route diversity and real-time performance. (3) To further enhance performance, we propose and design conservative channel reuse, a novel approach to support concurrent transmissions in a same wireless channel while maintaining a high degree of reliability. (4) Lastly, to address the limitation of the centralized architecture in handling network dynamics, we develop REACT, a Reliable, Efficient, and Adaptive Control Plane for centralized network management. REACT is designed to reduce the latency and energy cost of network reconfiguration by incorporating a reconfiguration planner to reduce a rescheduling cost, and an update engine providing efficient and reliable mechanisms to support schedule reconfiguration. All the network protocols and algorithms developed in this thesis have been empirically evaluated on the wireless testbed. This thesis represents a step toward next-generation IIoT for industrial automation that demands high-performance and agile wireless communication.