Abstract
The goal of this project is to develop a semantic foundation, cross-layer system architecture and adaptation services to improve dependability in instrumented cyberphysical spaces (ICPS) based on the principles of "computation reflection". ICPSs integrate a variety of sensing devices to create a digital representation of the evolving physical world and its processes for use by applications such as critical infrastructure monitoring, surveillance and incident-site emergency response. This requires the underlying systems to be dependable despite disruptions caused by failures in sensing, communications, and computation. The digital state representation guides a range of adaptations at different layers of the ICPS (i.e. networking, sensing, applications, cross-layer) to achieve end-to-end dependability at both the infrastructure and information levels. Examples of techniques explored include mechanisms for reliable information delivery over multi-networks, quality aware data collection, semantic sensing and reconfiguration using overlapping capabilities of heterogeneous sensors. Such adaptations are driven by a formal-methods based runtime analysis of system components, resource availability and application dependability needs. Responsphere, a real-world ICPS infrastructure on the University of California at Irvine campus, will serve as a testbed for development and validation of the overall ?reflective? approach and the cross-layer adaptation techniques to achieve dependability. Students at different levels (graduate, undergraduate, K-12) will be given opportunities to gain experience with using and designing real-world applications in the Responsphere ICPS via courses, independent study projects and demonstration sessions. Students will benefit tremendously from exposure to new software development paradigms for the ICPSs that will be a part of the future living environments.
Performance Period: 10/01/2010 - 09/30/2015
Institution: University of California-Irvine
Sponsor: National Science Foundation
Award Number: 1063596