CSE CHAMPS Initiative
Constructing High-Assurance Mobile and Pervasive Systems
Department of Computer Science and Engineering
Michigan State University
Computer Science and Engineering, July 21, 2004
Goal
• Identify and nurture an “umbrella” research theme for
CSE Department that:
– Leverages and creates synergy among current and emerging
CSE research strengths
– Sets CSE apart from other computer science programs
(e.g., Georgia Tech model)
– Is important to advances in many disciplines across campus
– Helps MSU play a unique role in information technology and
its applications in science, engineering, business, …
Computer Science and Engineering, July 21, 2004
CSE Research
• Established strength areas
– Networking and pervasive computing
– Software engineering and formal methods
– Intelligent systems
• Emerging strength areas
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Digital Evolution
Computational Linguistics
Cybersecurity
Bioinformatics
Computer Science and Engineering, July 21, 2004
Networking and Pervasive
Computing
Computer Science and Engineering, July 21, 2004
Networking Research
• Internet challenges: Real-time interaction,
wireless edge, security and privacy
• Internet Tele-operation (Mutka)
E. Lansing
Japan
– Real-time robot control/feedback
• Anonymous Communication (Shapiro)
– Internet privacy, Internet commerce
• Overlay Networks (Xiao, McKinley)
– Virus early warning systems, P2P apps
• Secure Mobile Computing (Mutka, McKinley)
• Funding: NIH, NSF, ONR
•
Discovering
party
Collaborators: Dept. of Surgery, Telecomm, ECE, ME,
Chemistry/BioChemistry, Mathematics, Ohio State,
William and Mary, U. Helsinki, Siemens
Computer Science and Engineering, July 21, 2004
Service
provider
Trust
– Battlefield computing, emergency services
Pervasive Computing
• Removing traditional boundaries for how,
where and when humans and computers
interact
• Augmented reality (Owen)
• Autonomic computing (McKinley, Kulkarni,
Cheng, Dillon, Stirewalt)
• Example: Critical Infrastructure Protection
– Adaptive auditing to prevent cascading failures
– Detect and respond to security threats
• Funding: ONR, NSF, Microsoft
• Collaborations: Siemens, Cisco, Lucent, MIND
Lab, Dept. Advertising
• Emerging collaborations: Business School,
Entomology, Cyclotron
Computer Science and Engineering, July 21, 2004
Sensor Networks
• A special case of pervasive computing
• Inexpensive MEMS devices deployed in
large quantity to remote, hazardous, or
denied areas
• Self-organizing control and data gathering
• Topics:
– Self-configuring networks (Kulkarni, Mutka)
– Energy management (McKinley)
– Software adaptation (Kulkarni)
• Example: DARPA NEST project
• Applications:
– Battlefield, homeland security
– Ecosystem monitoring
– Smart structures
• Collaborators: Entomology, Ohio State,
U. Iowa
Computer Science and Engineering, July 21, 2004
Software Engineering and
Formal Methods
Computer Science and Engineering, July 21, 2004
SE for High Assurance:
Systematic development of software that
requires critical properties
–Safety; Security; Real-time; Fault Tolerance
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Related Areas:
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Code Generation
Automated Verification
Component-Based Development
Embedded Systems
Fault Tolerance
Security
(Stirewalt, Cheng, Chung)
(Dillon, Stirewalt, Cheng)
(Stirewalt, Dillon, Cheng)
(Cheng, Kulkarni)
(Kulkarni, Cheng)
(Wojcik, Dyksen, Cheng, Chung,
Enbody, Jain, McKinley, Mutka,
Shapiro, Stirewalt, Xiao)
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Funding sources:
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NSF, DARPA, ONR, Automotive Industries, Siemens, APP&R
Collaborators:
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Telecomm, Business School, Medical School, Criminal Justice,
Motorola, Detroit Diesel, NASA/JPL, Texas Instruments, Boeing
Computer Science and Engineering, July 21, 2004
Software Engineering for High Assurance SW
Adaptive Cruise
Control
Automotive Software
ElectronicallyControlled
Steering
Transportation Systems
(Signaling/Automation)
Patient Monitoring
System
Manufacturing Software
Computer Science and Engineering, July 21, 2004
Temptations and Challenges for
Software Development
Ideas for
Software
• Ad hoc techniques
• Difficult to gain assurance
• Acceptable for some application
domains
``Design at the
keyboard’’
Code
``Testing’’
``Hacking’’
``Debugging’’
•High Assurance systems:
– Errors are “expensive”
– Demand rigorous SE
– Must be formally verifiable
– Automation
Computer Science and Engineering, July 21, 2004
Reality Check…
Question:
Would you ride the airplane
that uses your software?
Boeing 777
Fly-by-wire
Computer Science and Engineering, July 21, 2004
Bridge the Gap Between Informal and Formal Methods
Informal specifications,
• graphical models,
• easy for humans to
formulate,
•may be inconsistent and
incomplete.
Apply Formalization Framework
Object-Oriented “Blueprints”
Formal Representations
Objective:
• formal (mathematical-based)
specifications
• executable code
• that can be verified
for correctness
and completeness
Benefits:
•Automated Analysis
•Consistency, completeness
•Rapid Prototyping
•Behavior Simulation
• Design Transformations
•Test Case generation
Intelligent Systems
Computer Science and Engineering, July 21, 2004
Intelligent Systems
“Design and engineer systems that exhibit intelligence”
Autonomous agents, human computer interaction, knowledge
discovery
• Natural Language Understanding (Joyce Chai*, John Hale* +)
• Robotics (John Weng)
• Machine Learning (Rong Jin*, John Weng)
• Computer Vision (George Stockman, Anil Jain, Aude Oliva*# , John Weng)
• Pattern Recognition (Anil Jain)
• Data Mining (Pang-Ning Tan* and Anil Jain)
• Information Retrieval (Joyce Chai* and Rong Jin*)
*
Hired in the last two years # Dept. of Psychology + Dept. of Linguistics
Computer Science and Engineering, July 21, 2004
Research Projects
• Biometric Recognition (NSF, DHS)
• Question answering system for multimedia information
(ARDA)
• Handwritten document understanding (Microsoft)
• Data clustering (ONR)
• Smart airbags (Eaton)
• Developmental learning and humanoid robots
(DARPA, SAIC, Zyvex)
• Office presence (status of human presence in office)
(Microsoft)
• Multimodal conversational system (NSF)
• 3D sensing, modeling and movement (Army)
• Facial expression analysis and HCI (NSF)
Computer Science and Engineering, July 21, 2004
Biometric Recognition
• Biometrics: A measurable, physical characteristic
or personal behavioral trait used to recognize the
identity, or verify the claimed identity, of an enrollee
• Biometric recognition: Personal recognition
based on “who you are or what you do” as opposed
to “what you know” (password) or “what you have”
(ID card)
• Advantages: Eliminates fraud; enhances
security; cannot be easily transferred, forgotten,
lost or copied; eliminates repudiation claims; user
convenience
• Applications: Cybersecurity, border control,
driver license, cellular phones, ATM
Computer Science and Engineering, July 21, 2004
Developmental Learning
• Autonomous Mental development;
NSF/DARPA Workshop on Development
and Learning, MSU 2000 (Science, Jan. 2001)
• Designed and constructed Dav: the
only mobile and untethered humanoid
robot in US
• Press reports by UPI, BBC, KRN, 30 US
newspapers, Technology Review.
• Created ICDL conference series:
2nd ICDL (MIT’02), 3rd ICDL (San
Diego’04), 4th ICDL (Japan’05)
• Created a new journal:
Int’l J. of Humanoid Robotics
• Created IEEE NNS AMD Technical
Committee
Computer Science and Engineering, July 21, 2004
Face Capture HMD*
HMD wearer will see
faces of others on
the glass OR
projected on the
wall, etc. Small
mirrors and cameras
allow user’s facial
expressions to be
communicated to
remote colleagues.
* designed by Biocca (MSU) and Rolland (UCF)
Computer Science and Engineering, July 21, 2004
Emerging Interdisciplinary Research
Bioinformatics (Pramanik and Torng, in conjunction with
Chemistry, Biochemistry, and Microbial Ecology)
Computational Linguistics (Chai, Jin, and Hale, in conjunction
with Linguistics and Psychology)
Cyber-Security (Dyksen, Enbody, Tan, and Wojcik, in
conjunction with Criminal Justice, Telecommunications, Business,
the Law School, and the Medical School)
Digital Evolution (Ofria, Punch, and Torng, in conjunction with
Biochemistry, Electrical and Computer Engineering, Fisheries and
Wildlife, Microbiology and Molecular Genetics, Microbial Ecology,
Zoology, Plant Biology, Philosophy)
And others: Network Economics (Shapiro), Augmented Reality
(Owen), Human-Computer Interaction (Chai)
Computer Science and Engineering, July 21, 2004
Emerging Cyberinfrastructure
Secure Information Systems
Digital Supply Chain
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Remote
Safety-critical
Real-time
All the above
Privacy
Adaptable
NetworkCentric
Battlefield
Ecosystem Monitoring
Disaster
Relief
Homeland Security
Computer Science and Engineering, July 21, 2004
Cyberinfrastructure Research
• First Generation (proof-of-concept)
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Driven by applications in science and engineering
Advanced sensor hardware
Efficient systems software, network protocols
Understanding issues, brittle prototypes
• Second Generation (sustainable infrastructure)
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Driven by applications in science and engineering
Advanced sensor hardware
Efficient systems software, network protocols
High-assurance (generated) adaptable software and protocols
Intelligent systems that can learn how to respond and adapt
Designing and building robust, self-healing (autonomic)
systems for deployment
Computer Science and Engineering, July 21, 2004
CHAMPS
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Constructing High-Assurance Mobile and Pervasive Systems
– Research to enable a sustainable, pervasive cyberinfrastructure
– Key ingredients: robust, self-managing and self-healing software
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Research theme that draws upon combination of CSE strengths
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Adaptive networking, augmented reality, secure mobile computing, sensor networks
Rigorous software engineering, autonomic systems, fault tolerance
Biometrics, embodied intelligence, autonomous robots, data mining
Bioinformatics, human computer interaction, computational linguistics
Wide range of applications and collaborations
– Agriculture and ecosystem monitoring, remote scientific experimentation
– Tele-medicine, digital supply chain, secure/robust information systems
– Battlefield and surveillance, infrastructure protection, homeland security
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An area where CSE (and via interdisciplinary collaborations, MSU) is poised
for national leadership.
Computer Science and Engineering, July 21, 2004