CS 851: Seminar Cyber-Physical Systems Professor John A. Stankovic Department of Computer Science Spring 2009 Course Description As computers and communication bandwidth become ever-faster and ever-cheaper, computing and communication capabilities will be embedded in all types of objects and structures in the physical environment. Applications with enormous societal impact and economic benefit will be created by harnessing these capabilities in time and across space. We refer to systems that bridge the cyber-world of computing and communications with the physical world as cyber-physical systems. Cyber-physical systems (CPSs) are physical and engineered systems whose operations are monitored, coordinated, controlled and integrated by a computing and communication core. This intimate coupling between the cyber and physical will be manifested from the nano-world to large-scale wide-area systems of systems. The internet transformed how humans interact and communicate with one another, revolutionized how and where information is accessed, and even changed how people buy and sell in the marketplace. Similarly, CPSs will transform how humans interact with and control the physical world around us. Examples of CPSs include medical devices and systems, aerospace systems, transportation vehicles and intelligent highways, defense systems, robotic systems, process control, factory automation, building and environmental control and smart spaces. Since CPSs interact with the physical world, they must operate dependably, safely, securely, efficiently and in real-time. Building effective CPSs of the future require multi-disciplinary skills. In particular, the confluence of real-time computing, wireless sensor networks, control theory, signal processing and embedded systems are required to create these new systems. This seminar will cover some basic material from these areas, but focus on advanced research papers related to CPS. Prerequisites Graduate standing. Background in operating systems and computer networking is necessary. It would be helpful to also have a background in wireless sensor systems. Grading Reading Summaries: 10% Paper presentation(s): 30% Discussions: 20% Final Project: 40% Course Topics 1. Introduction – What is CPS? a. Cyber Physical Systems: Design Challenges, Edward Lee. Technical Report No. UCB/EECS-2008-8. b. When Sensor and Actuator Networks Cover the World, John A. Stankovic. ETRI Journal, Volume 30, No. 5, Oct. 2008 c. Extra: Opportunities and Obligations for Physical Computing Systems, J. Stankovic, I. Lee, A. Mok, R. Rajkumar. IEEE Computer, Nov. 2005 2. Applications and Systems a. Nericell: Rich Monitoring of Road and Traffic Conditions using Mobile Smartphones. P. Mohan, V. Padmanabhan, R. Ramjee, Proceedings of SenSys ’08, Nov. 2008. b. Sensing Meets Mobile Social Networks; The Design, Implementation and Evaluation of the CanceMe Application. E. Miluzzo, N. Lane, K. Fodor, R. Peterson, H. Lu, M. Musolesi, S. Eisenman, X. Zheng, A. Cambell, Proceedings of SenSys ’08, Nov. 2008. c. Voxnet: An Interactive, Rapid-Deployable Acoustic Monitoring Platform. M. Allen, L. Girod, R. Newton, S. Madden, D. Blumstein, D. Estrin, IPSN 08. d. Extra: Towards Community Sensing, A. Krause, E. Horvitz, A. Kansal, F. Zhao. IPSN 08. 3. Underlying Standards, Wireless Communications and Related Technologies a. Zigbee: TDBS: a time division beacon scheduling mechanism for Zigbee cluster- tree wireless sensor networks, A. Koubâa, A. Cunha, M. Alves, E. Tover. Real- Time Systems Journal. b. Bluetooth: Chapter 15 from text. c. 6LoWPAN i. IP is Dead, Long Live IP for Wireless Sensor Networks, Jonathan W. Hui and David E. Culler. Proceedings of SenSys ’08, Nov. 2008 ii. Extra: IETF Memo iii. Extra: A Lightweight NEMO Protocol to Support 6LoWPAN, J.H. Kim, C.S. Hong, and T. Shon. ETRI Journal, Vol. 30, No. 5, Oct. 2008 d. Multi-channel: A Practical Multi-Channel Media Access Control Protocol for Wireless Sensor Networks, H.K. Le, D. Henriksson, and T. Abdelzaher. IPSN 2008. e. Extra: Free Space Optical memos (2) f. Extra: Power over Ethernet memos (2) 4. Beyond the Communication Stack a. Energy Harvesting i. Extra: Survey on power, Dand Steingart and Joe Polastre – Sentilla article ii. A Quantitative Investigation of Inertial Power Harvesting for Human- Powered Devices. J. Yun, S. Patel, M. Reynolds and G. Abowd, UbiComp ’08, Sept. 2008 b. Middleware for Wireless Sensor Networks: A Survey, M. Wang, J. Cao, J. Li, and S. Das. Journal of Computer Science and Technology 23(3): 305-326, May 2008. c. Service Oriented Architectures (SOA) i. A Service Oriented Architecture for Wireless Sensor and Actor Network Applications, J. Prinsloo, C. Schulz, D. Kourie, W.H.M. Theunissen, T. Strauss, R. Van Den Heever, S. Grobbelaar. Proceedings of SAICSIT 2006. ii. Service Oriented Software Architecture for Sensor Networks, F. Golatowski, J. Blumenthal, M. Handy, M. Haase, H. Burchardt, and D. Timmermann. d. Livenet: Using Passive Monitoring to Reconstruct Sensor Network Dynamics, B. Chen, G. Peterson, G. Mainland and M. Welsh. DCOSS 2008, LNCS 5067, pp. 79-98, 2008. e. Extra: Java for embedded systems: Java Platform, Micro Edition (J2ME), http://java.sun.com/javame/technology/index.jsp 5. Real-Time and Control Theory a. Achieving Real-Time Target Tracking Using Wireless Sensor Networks, T. He, P. Vicaire, T. Yan, L. Luo, L. Gu, G. Zhou, R. Stoleru, Q. Cao, J. Stankovic and T. Abdelzaher. RTAS 2006. b. Real-Time Tools and Analysis i. Synthesis of Task and Message Activation Models in Real-Time Distributed Automotive Systems, W. Zheng, M. Di Natale, C. Pinello, P. Giusto, A. Sangiovanni-Vincentelli. Design, Automation and Test in Europe, April, 2007. ii. Definition of Task Allocation and Priority Assignment in Hard Real- Time Distributed Systems, W. Zheng, Q. Zhu, M. Di Natale, A. Sangiovanni-Vincentelli. RTSS Proceedings, 2007. iii. Period Optimization for Hard Real-Time Distributed Automotive Systems, A. Davare, Q. Zhu, M. Di Natale, C. Pinello, S. Kanajan, A. Sangiovanni-Vincentelli. DAC 2007. c. Control Theory Basic concepts i. Feedback Performance Control in Software Services, T. Abdelzaher, J. Stankovic, C. Lu, R. Zhang, and Y. Lu. Control Systems Magazine, Vol. 23, Issue 3, pp. 74-90, 2003. ii. Feedback Control Real-Time Scheduling: Framework, Modeling and Algorithms, C. Lu, J. Stankovic, g. Tao, S. Son. Journal of Real-Time Systems, Special Issue on Control-Theoretical Approaches to Real-Time Computing, 2001. d. DEUCON: Decentralized End-to-End Utilization Control for Distributed Real- Time Systems, X. Wang, D. Jia, C. Lu and X. Koutsoukos. IEEE Transactions on Parallel and Distributed Systems, Vol. 18, No. 7, July 2007. e. Extra: Control over Unreliable Networks Affected by packet Erasures and Variable Transmission Delays, D. Quevedo, E. Silva, and G. Goodwin. IEEE Journal on selected Areas in Communications, Vol. 26, No. 4, May 2008. 6. Sensor Fusion and Signal Processing a. Information Fusion for Wireless Sensor Networks: Methods, Models and Classifications, E. Nakamura, A. Loureiro, and A. Frery. ACM Computing Surveys, Vol. 39, No. 3, Article 9, August 2007. b. Detection, Classification and Tracking of Targets in Distributed Sensor Networks, D. Li, K. Wong, Y. Hu, and A. Sayeed. IEEE Signal Processing Magazine, 2002 c. Distributed Activity Recognition with Fuzzy-Enabled Wireless Sensor Networks, M. Marin-Perianu, C. Lombriser, O. Amft, P. Havinga, and G. Tröster. DCOSS 2008, LNCS 5067, pp. 296-313, 2008. d. Extra: On Accurate and Efficient Statistical Counting in Sensor Based Surveillance Systems, S. Guo, T. He, M. Mokbel, J. Stankovic, and T. Abdelzaher. IEEE MASS 2008, April 2008. Best Paper Award (selected from 250 papers) 7. Knowledge Creation a. Learning Techniques applied to activity inference 1. Naive Bayesian inference: Applied in Tapia 2004 - Activity Recognition in the Home Using Simple and Ubiquitous Sensors, E. M. Tapia, S. S. Intille, and K. Larson. Lecture Notes in Computer Science, Vol. 3001, pp. 158-175, 2004. http://courses.media.mit.edu/2004fall/mas622j/04.projects/home/TapiaIntilleLars on04.pdf 2. Harmonic Markov Models and Conditional Random Fields - Accurate Activity Recognition in a Home Setting, T. van Kasteren, A. Noulas, G. Englebienne and B. Kröse. Ubicomp 08. http://doi.acm.org/10.1145/1409635.1409637 b. Inference Techniques 1. Particle filters for location tracking: Simultaneous Tracking & Activity Recognition (STAR) Using Many Anonymous, Binary Sensors, Daniel Wilson and Chris Atkeson. The Third International Conference on Pervasive Computing, 2005. http://www.cs.cmu.edu/~dwilson/papers/wilsonPERVASIVE2005.pdf 2. Pedestrian localization in indoor environments, Oliver Woodman and Robert Harle. Ubicomp 08. http://doi.acm.org/10.1145/1409635.1409651 c. New techniques applied to pattern inference Topic models - Discovery of activity patterns using topic models, Tâm Huỳnh, Mario Fritz and Bernt Schiele. Ubicomp 08. http://doi.acm.org/10.1145/1409635.1409638 d. Probabilistic Context Free Grammars D. Lymberopoulos, A. Barton-Sweeney, T. Teixeira and A. Savvides, An Easy- to-Program Sensor System for Parsing Human Activities, ENALAB Technical Report 090601, May 2006. D. Lymberopoulos, T. Teixeira and A. Savvides, BScope: A Scalable, Run-Time Architecture for Activity Recognition Using Wireless Sensor Networks, ENALAB Technical Report 040701 e. Extra: At the Flick of a Switch: Detecting and Classifying Unique Electrical Events on the Residential Power Line, S. N. Patel, T. Robertson, J. A. Kientz, M. S. Reynolds, and G. D. Abowd. UbiComp 2007, LNCS 4717, pp. 271-288, 2007. 8. Security a. A Survey of Sensor Network Security, A. Vaseashta and S. Vaseashta. Sensors and Transducers, Vol. 94, Issue 7, July 2008. b. State of the Art: Denial of Service in WSN - Chapter 2 of Anthony Wood thesis c. Seluge: Secure and DoS-Resistant Code Dissemination in Wireless Sensor Networks, S. Hyun, P. Ning, A. Liu, and W. Du. IPSN 2008. d. Extra: Denial of Service in Sensor Networks, Anthony D. Wood and John A. Stankovic. Computer, Vol. 35, Issue 10, pp. 54-62, 2002.