1. Other CITRIS Research Programs Jim Demmel, Chief Scientist EECS and Math Depts. www.citris.berkeley.edu UC Santa Cruz

2. Outline  Security (Wagner, Tygar)  Software Reliability (Aiken, Necula, Henzinger)  Sensors Webs (Sastry,…)  Transportation Networks (Hedrick, Varaiya, …)  Visualization (Hamann, Joy, Max, Staadt)  CAD for MEMS (Demmel, Govindjee, Agogino, Pister, Bai)

3. Security

4. Software Security – D. Wagner  Security programming is pitfall-laden  It’s too easy to unintentionally violate implicit usage rules of OS API’s  Our approach: enforce defensive coding  Enumerate rules of prudent security coding  Use tools to automatically verify that SW follows rules

5. Prudent Coding Rules system() or exec() seteuid(0) seteuid(0) Example of a rule:  Avoid calling system() or exec() with root privilege In our tool, MOPS:  Rules are finite-state machines  Good for ordering properties  Intuitive for programmers  Programs are PDAs  Use model checking to verify absence of security holes  Numerous bugs uncovered   www.cs.berkeley.edu/~daw/ mops

6. On going work – Security in Sensor Nets  with D. Culler, D. Tygar  Motivation: resist attack on sensor nets  Secure routing  Secure location finding  Challenge: low resource environment

7. Security with Privacy – D. Tygar  DARPA ISAT study, co-lead by E. Felton  Security: protection of people and property by intelligence and law enforcement  Privacy: while respecting legal, political, ethical rules on use of personal data  Data Sources: US Govt, other govts, commercial, private

8. Approach  Focus on two application areas  Profiling: On whom should security personnel focus?  Data mining: What can we learn by automated analysis of available data?  Understand how to do these things better  Constrained by privacy concerns (legal and policy)  Constrained by real-world organizational issues  Look for technological leverage points

9. Conclusions [to date]  Biggest technical challenge is data fragmentation  Selective revelation (shorter term),  General function shipping (longer term)  Privacy metrics valuable, if feasible  Entropy based?  Law has been slow to track changes in technology; would help to redraw some legal lines to maintain original spirit of laws.  Final Report due: August 2002  Impact on design of Societal Scale Information Systems

10. Software Reliability

11. OSQ: Open Source Quality  Goals: Automatic analysis of software for  Finding bugs  Checking specifications Of a at least simple properties  Help with writing specifications  Focus  Large, ubiquitous systems programs  Linux kernel, sendmail, apache, etc.

12. Tools  CCured  Automatically enforce memory safety for C Array index out of bounds, wild pointer dereferences  CQual  Specification and checking of system-specific properties Locking, file handling, ordering of method calls, …  BLAST  Software model checker E.g., for checking complex control-flow in device drivers http://www.cs.berkeley.edu/~weimer/osq

13. Sensor Webs

14. Activities of the SensorWebs Group (Sastry)  Studied theory and algorithms for networks of wireless sensors (SensorWebs)  Basic idea: A large number of SmartDust motes distributed in an environment; they sense it, compute, and communicate  Main problems:  Localization  Environmental monitoring  Tracking  Map building  Localization: some nodes have known, some unknown locations – compute the unknown ones  Environmental monitoring: given a scalar environmental variable (temperature, air pressure, intensity of light, etc.), monitor it using a (possibly random) sensor network and visualize its gradient  Tracking of moving objects: track one or more moving objects through a sensor network  Map building: use a mobile sensor network (e.g., robots carrying sensors) to create a map of an unknown environment)

15. Main Results and Applications  Designed distributed, computationally efficient algorithms for localization, environmental monitoring (static and dynamic), tracking, and map building  Obtained analytical estimates on the required density of sensor nodes to achieve desired average accuracy  Preparing to implement and test the algorithms on a test-bed with several hundred nodes in collaboration with the NEST Project (D. Culler) Applications  Environmental monitoring: of the gradient of environmental variables, to close control loop for cutting power use, energy conservation, increasing comfort in smart buildings; also, tracking hazardous plumes.  Map building: investigation of dangerous areas (e.g., following a major natural disaster) using mobile robots  Tracking: possible applications in preventing terrorist activity.

16. Experimental Results: Pursuit-Evasion Games with 4UGVs and 1 UAV

17. Where does the Sensor Network fit in? Ground Monitoring System Ground Mobile Robots UAVs Sensor Webs Gateways Courtesy of Jin Kim Lucent Orinoco (WaveLAN) (Ad Hoc Mode)

18. Transportation

19. Karl Hedrick Director, California PATH Research Center on Intelligent Transportation Systems

20. PATH Activities   Advanced Vehicle Control and Safety Systems (AVCSS) Steven Shladover, Senior Deputy Director   Advanced Transportation Management and Information Systems (ATMIS) Hamed Benouar, Acting Deputy Director   Center for Commercialization of ITS Technologies (CCIT) Hamed Benouar, Executive Director

21. Partners for Advanced Transit and Highways (PATH Program)  Applying information technology to improve surface transportation operations  Partnership between California Department of Transportation and UCB Institute of Transportation Studies since 1986  Started national interest in Intelligent Transportation Systems (ITS)  Annual statewide RFP for new research projects  Combination of faculty/graduate student and full-time research staff projects - 100 person level of effort

22. PATH-Identified Research Needs  Enabling technologies for intelligent transportation systems:  Remote sensing of macroscopic traffic conditions  Remote sensing of microscopic vehicle positions and surroundings  Wireless communications (vehicle-vehicle and vehicle- roadside)  Safety-critical software systems  More information at poster session

23. Center for Commercialization of ITS Technologies (CCIT): Focus  Bring the best minds together to conduct R&D, testing, and evaluation of ITS  Collaboration among researchers, industry professional, and practitioners  Accelerate commercial deployment of transportation products and services  Solve transportation problems using new products and services  Facilitate traffic data dissemination  Focus researcher and industry efforts on Information Technology (IT) solutions for transportation

24. CCIT Programs  Traveler Information Traffic Data Collection and dissemination  Vehicle Information and Control In-vehicle information systems  Transportation Management Systems Performance management  Innovative Mobility System Concepts Electronic and wireless technologies to support transit and carsharing, smart parking management, and smart growth

25. Advanced Traffic Management and Information Systems(ATMIS)/CCIT Projects  IT to Improve Transportation, Safety, Efficiency, Security, and the Environment  Caltrans Performance Measurement System (PeMS)  Integrated Transportation Performance Management  Traffic Data collection/dissemination  Partnership with Information Service Providers  Smart Detector Technology (Vehicle Signature)  Border Crossing ITS Technologies (US-Mexico)  Technologies for Carsharing and Smart Parking Management  Cellular Technology for traffic data collection/traveler information

26. Visualization

27. Interactive and Collaborative Visualization and Exploration of Massive Data Sets ---- UC Davis Visualization Investigators: Bernd Hamann, Ken Joy, Kwan-Liu Ma, Nelson Max and Oliver Staadt Nelson Max and Oliver Staadthttp://graphics.cs.ucdavis.edu

28. Massive Data Visualization - The Challenge  Massive amounts of data acquired by millions of multi-modal sensors – embedded in civil infrastructure  Exploration for multiple purposes  Traffic flow monitoring  Behavior of structures during earthquakes  Environmental monitoring (water, air, land)  Crisis management  …  Automatic “filtering” and compression of data  Real-time visualization for different groups  Decision and policy makers  Emergency response teams  Civil engineers  …  Major technological challenges!

29. Collaborative Visualization  Connection of multiple data exploration and visualization centers  Collaborative data exploration by interdisciplinary expert teams

30. Contribution to CITRIS  Compression of massive data streams supporting analysis at multiple levels of abstraction – quantitative / qualitative  Efficient and automatic feature extraction  Visualization in immersive three-dimensional environments  Interactive visualization – real-time  Techniques for large, room-size “display walls”  Parallel and distributed computing in support of scalable, multiresolution-based data exploration techniques  Hybrid display environments - virtual environments, augmented virtuality, augmented reality, voice, gesture, force, …

31. Computer Aided Design of MEMS

32. SUGAR  Pister, Demmel, Govindjee, Agogino, Bai  Tool for system-level MEMS simulation  Goal: Be SPICE to the MEMS world  Analyzes static, dynamic, and linearized steady-state behavior  Challenges:  Be fast enough for design and optimization (not just verification)  Handle coupled physical effects electrical, mechanical, thermal, optical, …

33. SUGAR: Current work  Broad set of component models  Validation against optical measurements  Deployment of Millennium-based web service (used in EE245 in Fall 2001)  Analyze dependence on parameters (sensitivity analysis, bifurcation analysis)  Design synthesis and optimization  Integration of state-of-the-art solvers

35. Torsional micromirror. MEMS Design by: M. Last, K.S.J. Pister Complex system with ~1000 comb fingers and torsional springs Finite Element Analysis might use O(10 6 ) continuum elements Sugar: system reduces to 2,621 elements and 11,706 unknowns Device described using parameterized substructures Cosine- shaped beams Perforate d beams Mirror Torsional hinge Perforated comb drive array Actuation direction Moment arm Recessed inner plate

36. M&MEMS: SUGAR on the Web Hosted on Berkeley Millennium cluster Requires only a web browser (with Java for graphics) Used in Berkeley’s Fall 2001 introductory MEMS course