cse champs initiative c onstructing h igh- a ssurance m obile and p ervasive s ystems

Computer Science and Engineering, July 21, 2004

CSE CHAMPS Initiative

Constructing High-Assurance Mobile and Pervasive Systems

Department of Computer Science and Engineering

Michigan State University


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, …


CSE Research

• Established strength areas– Networking and pervasive computing– Software engineering and formal methods– Intelligent systems

• Emerging strength areas – Digital Evolution– Computational Linguistics– Cybersecurity– Bioinformatics


Networking and Pervasive Computing


Networking Research• Internet challenges: Real-time interaction,

wireless edge, security and privacy• Internet Tele-operation (Mutka)

– 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)

– Battlefield computing, emergency services

• Funding: NIH, NSF, ONR• Collaborators: Dept. of Surgery, Telecomm, ECE, ME,

Chemistry/BioChemistry, Mathematics, Ohio State, William and Mary, U. Helsinki, Siemens

Japan

E. Lansing

Discovering party

Service provider

Tru

st


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


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


Software Engineering and Formal Methods


SE for High Assurance:Systematic development of software that requires critical properties

–Safety; Security; Real-time; Fault Tolerance

• Related Areas:– Code Generation (Stirewalt, Cheng, Chung)– Automated Verification (Dillon, Stirewalt, Cheng)– Component-Based Development (Stirewalt, Dillon, Cheng)– Embedded Systems (Cheng, Kulkarni)– Fault Tolerance (Kulkarni, Cheng)– Security (Wojcik, Dyksen, Cheng, Chung,

Enbody, Jain, McKinley, Mutka, Shapiro, Stirewalt, Xiao)

• Funding sources:– NSF, DARPA, ONR, Automotive Industries, Siemens, APP&R

• Collaborators:– Telecomm, Business School, Medical School, Criminal Justice,

– Motorola, Detroit Diesel, NASA/JPL, Texas Instruments, Boeing


Software Engineering for High Assurance SW

Patient Monitoring System

Transportation Systems(Signaling/Automation)

Manufacturing Software

Automotive SoftwareAdaptive Cruise Control

Electronically-Controlled Steering


Temptations and Challenges for Software Development

• Ad hoc techniques• Difficult to gain assurance• Acceptable for some application

domains

Ideas for Software

Ideas for Software

``Design at the keyboard’’

``Testing’’``Hacking’’``Debugging’’Code

•High Assurance systems:– Errors are “expensive”– Demand rigorous SE– Must be formally verifiable– Automation


Question:Would you ride the airplane that uses your software?

Reality Check…

Boeing 777Fly-by-wire

Object-Oriented “Blueprints”

Informal specifications,• graphical models,• easy for humans to formulate, •may be inconsistent and incomplete.

Bridge the Gap Between Informal and Formal Methods

Ap

ply F

orm

aliza

tion

Fram

ew

ork

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


“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

Intelligent SystemsIntelligent Systems


• 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)

Research Projects Research Projects


Biometric RecognitionBiometric 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


• 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

Developmental LearningDevelopmental Learning


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.

Face Capture HMD*Face Capture HMD*

* designed by Biocca (MSU) and Rolland (UCF)


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)


Emerging Cyberinfrastructure

Network-Centric

BattlefieldHomeland Security

Ecosystem Monitoring

Disaster Relief

Secure Information SystemsDigital Supply Chain

• Remote• Safety-critical• Real-time• All the above• Privacy• Adaptable


Cyberinfrastructure Research

• First Generation (proof-of-concept)– Driven by applications in science and engineering

– Advanced sensor hardware

– Efficient systems software, network protocols

– Understanding issues, brittle prototypes

• Second Generation (sustainable infrastructure)– 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


CHAMPS

• Constructing High-Assurance Mobile and Pervasive Systems– Research to enable a sustainable, pervasive cyberinfrastructure– Key ingredients: robust, self-managing and self-healing software

• Research theme that draws upon combination of CSE strengths – 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

• An area where CSE (and via interdisciplinary collaborations, MSU) is poised for national leadership.

cse champs initiative c onstructing h igh- a ssurance m obile and p ervasive s ystems

Documents

business school

cse department

iowasoftware engineering

ohio state

high assurance swtemptations

chengembedded systems

mckinleybattlefield

code generation stirewalt