PhD Oral Defense: Song Han, Oct. 26th, 2 p.m. CST, ACES 5.336

Contact Name: 
Lydia Griffith
Date: 
Oct 26, 2012 2:00pm - 4:00pm

PhD Oral Defense: Song Han

Date: Oct.26th
Time: 2:00pm
Place:  ACES 5.336
Research Supervisor: Al Mok

Title of Dissertation: Networking Infrastructure and Data Management
for Cyber-Physical Systems

Abstract:

A cyber-physical system (CPS) is a system featuring a tight
combination of, and coordination between, the system’s computational
and physical elements. A large-scale CPS usually
consists of several subsystems which are formed by networked sensors
and actuators, and deployed in different locations. These subsystems
interact with the physical world and execute specific monitoring and
control functions. How to organize the sensors and actuators inside
each subsystem and interconnect these physically separated subsystems
together to achieve secure, reliable and real-time communication is a
big challenge. In this thesis, we first present a TDMA-based low-power
and secure real-time wireless protocol. This protocol can serve as an
ideal communication infrastructure for CPS subsystems which require
flexible topology control, secure and reliable communication and
adjustable real-time service support. We then describe the network
management techniques designed for ensuring the reliable routing and
real-time services inside the subsystems and data management
techniques for maintaining the quality of the sampled data from the
physical world. To evaluate these proposed techniques, we built a
prototype system and deployed it in different environments for
performance measurement. We also present a light-weighted and scalable
solution for interconnecting heterogeneous CPS subsystems together
through a slim IP adaptation layer and a constrained application
protocol layer. This approach makes the underlying connectivity
technologies transparent to the application developers thus enables
rapid application development and efficient migration among different
CPS platforms. At the end of this thesis, we present a semi-autonomous
robotic system called cyberphysical avatar. The cyberphysical avatar
is built based on our proposed network infrastructure and data
management techniques. By integrating recent advance in body-compliant
control in robotics, and neuroevolution in machine learning, the
cyberphysical avatar can adjust to an unstructured environment and
performs physical tasks subject to critical timing constraints while
under human supervision.