Visible to the public CPS: Medium: Timing-Centric Software

Submitted by Edward Lee on Thu, 04/07/2011 - 5:24pm
Project Details
Lead PI:Edward Lee
Co-PI(s):Sanjit Seshia
Performance Period:09/15/10 - 08/31/14
Institution(s):University of California-Berkeley
Sponsor(s):National Science Foundation
Project URL:http://chess.eecs.berkeley.edu/ptides/
Award Number:1035672
2737 Reads. Placed 69 out of 804 NSF CPS Projects based on total reads on all related artifacts.
Abstract: The objective of this research is to define programming abstractions with temporal semantics for distributed cyber-physical systems. The approach is to create a coordination language for distributed embedded software that blends naturally with models of physical dynamics. The coordination language is based on a rigorous discrete-event concurrent model of computation. It will be used by system designers to construct models from which software implementations are derived. The objective is distributed software that, if it compiles for a platform, delivers precisely the temporal semantics specified in the model. Intellectual merit: This project addresses the core abstractions of computing, which throughout the 20th century, have abstracted away time, and of physical dynamics, which have omitted software and network behaviors. For cyber-physical systems, both are inappropriate. This project is developing new time-centric abstractions for software, programming models, analysis techniques, and integration of software and network models with physical dynamics. Broader impacts: Besides the considerable economic and societal impact of CPS in general, the project is expected to have considerable impact on engineering and computer science education. Its focus on engineering applications and on sound computer science methods will erode the boundaries between these disciplines that hamper competitiveness of our students. A new generation of students is needed to dramatically improve our energy efficiency, manufacturing capabilities, transportation efficiency, instrumentation prowess (and hence, scientific knowledge), and infrastructure robustness. Because of the broad societal implications of the work, it will help attract to engineering and computer science a more diverse talent pool.