CITRIS Scientific Agenda

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

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Security
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Software Security D. Wagner

• Security programming is pitfall-laden
• Its too easy to unintentionally violate implicit
  usage rules of OS APIs
• Our approach enforce defensive coding
• Enumerate rules of prudent security coding
• Use tools to automatically verify that SW follows
  rules

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Prudent Coding Rules

• 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

• Example of a rule
• Avoid calling system() or exec() with root
  privilege

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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

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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

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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

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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

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Software Reliability
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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.

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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

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Sensor Webs
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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)

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Main Results and Applications

• 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.

• 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)

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Experimental Results Pursuit-Evasion Games with
4UGVs and 1 UAV
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Where does the Sensor Network fit in?
UAVs

Lucent Orinoco (WaveLAN) (Ad Hoc Mode)
Ground Monitoring System
Ground Mobile Robots
Gateways
Sensor Webs
Courtesy of Jin Kim
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Transportation
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Karl Hedrick Director, California PATH Research
Center on Intelligent Transportation Systems
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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

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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

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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

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Center for Commercialization of ITS Technologies
(CCIT) Focus

• Bring the best minds together to conduct RD,
  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

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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

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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

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Visualization
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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
• http//graphics.cs.ucdavis.edu

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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!

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Collaborative Visualization

• Connection of multiple data exploration and
  visualization centers
• Collaborative data exploration by
  interdisciplinary expert teams

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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,

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Computer Aided Design ofMEMS
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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,

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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

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