Real-Time Decision Making Seminar

Quantitative Policies over Streaming Data

Decision making in emerging IoT systems often requires dynamic monitoring of a data stream to compute performance-related quantitative properties. We propose StreamQRE as a high-level declarative language for modular specifications of such policies. This language is rooted in the emerging theory of regular functions, and every policy described in this language can be compiled into a space-efficient streaming implementation. We describe a prototype system that is integrated within an SDN controller and show how it can be used to specify and enforce dynamic updates for traffic engineering as well as in response to security threats.  As another case study, we will discuss the application of StreamQRE to the design space exploration of alternative algorithms for cardiac arrhythmia detection. We conclude by outlining the rich opportunities for both theoretical investigations and practical systems for real-time decision making in IoT applications.

Rajeev Alur is Zisman Family Professor of Computer and Information Science at University of Pennsylvania. He obtained his bachelor's degree from IIT Kanpur and PhD from Stanford University. His research is focused on formal methods for system design, and spans theoretical computer science, software verification and synthesis, and cyber-physical systems. He is a Fellow of the AAAS, ACM, and IEEE, an Alfred P. Sloan Faculty Fellow, and a Simons Investigator. He was awarded the inaugural CAV (Computer-Aided Verification) award, Logic in Computer Science (LICS) Test-of-Time award and the inaugural Alonzo Church award  for his work on timed automata.

Anyone who would like to give one of the weekly seminars on the RTDM program can fill in the survey at https://goo.gl/forms/Li5jQ0jm01DeYZVC3.