Scalable Runtime support for Edge-To-Cloud integration of Distributed Sensing Systems

Name: Brett Chien
Date: November 29, 2016

Time: 10:00AM

Location: EH 2210

Committee: Pai H. Chou (Chair)

Abstract: 

While Internet-Of-Things (IoT) has drawn more attention to researchers and the public, to build a complete system from the edge sensing units to the cloud services requires massive amount of efforts. Researchers with strong interests in collected information are often lost in various technologies, including distributed sensing embedded systems, bridge devices between Internet and local network, and data backend services.

This work takes a cross-system, script-based, and semantic-enhanced approach to address the problem of lacking suitable runtime supports. We proposed a threaded code runtime support for edge sensing systems, a script based wrapper on Physical-to-Cyber bridges, and scalable middleware into the backend services.

With proposed runtime supports, we are able to apply distributed sensing systems into real world applications quickly and explorer insights from collected information. As a result, a building structure monitoring system is installed and allow civil researchers to develop algorithms to prevent disaster events. Body area sensing systems such as ECG monitoring, CO2 detection, and body movement are developed. This enables baby screening and detect potential heart problems. The results have shown that with proposed runtime supports applications can be realized quickly and scalable.