Cyber-Physical Systems (CPS) enable various new applications, including self-driving cars, drones, implantable medical devices, smart cars, distributed transportation systems, smart grids, and planetary robots. CPS sense the physical environment, process data in real-time, control the actuators, and guarantee the timing of the whole execution chain for ensuring safety. Since CPS are tightly coupled with the physical world, anomalies such as hardware failures and timing errors may cause significant damage to life and/or property. Common practices addressing those failures tend to use redundant hardware to overprovision resources. However, many CPS are targeted towards large-scale cost-sensitive markets that have stringent space and bill-of-material constraints that cannot afford overprovisioning. In this talk, I will discuss my research on a software-level redundancy approach providing many of the same benefits of using redundant hardware while maintaining lower costs and a higher level of flexibility. I will first present a framework called SAFER (System-level Architecture for Failure Evasion in Real-time applications) that incorporates configurable software mechanisms and policies to tolerate failures of critical CPS resources while meeting their timing constraints. I will then present how to guarantee timeliness by devising new computational models reflecting the timing nature of CPS. I will describe the schedulability analysis and runtime support for such models with and without resource failures. Finally, I will show how the proposed approaches make an autonomous vehicle dependable and conclude my talk with future directions towards large-scale CPS.
Junsung Kim is Research Engineering Manager – Software and Functional Safety at Delphi and contributes to realizing automated driving. Formerly, he co-founded Ottomatika, a CMU spin-out company commercializing automated driving technologies. He served as the director of Software and Safety until Ottomatika was acquired by Delphi. He holds a Ph.D. degree from the department of Electrical and Computer Engineering at Carnegie Mellon University (CMU) since 2014. During his Ph.D., he was also affiliated with the General Motors-Carnegie Mellon Autonomous Driving Collaborative Research Laboratory, where he led efforts to design and build safer automated vehicles. Before joining CMU, he was a research engineer developing 4G LTE protocol software at LG Electronics for four years. He graduated KAIST with M.S. and B.S. degrees in Electrical Engineering in 2004 and 2002, respectively.