Telecom Research at Rutgers
University
Fred S. Roberts
Director, DIMACS
froberts@dimacs.rutgers.edu
July 11, 2003
Commission on Jobs Growth and
Economic Development
1
Outline
• What is Telecom?
• The research players and their background
• A selection of research topics suggested by Rutgers
faculty
– Short synopsis
– Food for thought; aimed at stimulating discussion
July 11, 2003
Commission on Jobs Growth and
Economic Development
2
What is Telecom?
The set of
technologies and
sciences at the
intersection of
communications,
information, and
computing
Communications
Information
Telecom
Computing
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What is Telecom?
• 20th century: transport, switching, and storage of
narrowband voice and data
• 21st century? Reasonable goal: fully integrated
and networked broadband multimedia including:
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data of all types
text, images, audio, video
virtual reality
searchable, browseable multimedia documents
shared reality tele-collaboration
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What is Telecom?
So: telecom is all about networks:
• interconnections of networks (e.g., the Internet)
• operation and maintenance of networks
• things that make up networks (routers, hubs,
switches)
• things that get moved around networks (data,
text, voice, images, video, …)
• things that attach to networks (devices, sensors,
monitors)
• services that run on networks
July 11, 2003
Commission on Jobs Growth and
Economic Development
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Outline
• What is Telecom?
• The research players and their background
• A selection of research topics suggested by Rutgers
faculty
– Short synopsis
– Food for thought; aimed at stimulating discussion
July 11, 2003
Commission on Jobs Growth and
Economic Development
6
Major Hubs of Telecom
Research at Rutgers
CAIP (Center for Advanced Information
Processing)
DIMACS (Center for Discrete Mathematics and
Theoretical Computer Science)
WINLAB (Wireless Information Laboratory)
Computer Science Dept.
Statistics Dept.
July 11, 2003
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CAIP
• Established by NJCST in 1985
• Mission: industrial applications of advanced computing
technologies
• Industry partners:
AT&T, Avaya, Cisco, Datacube, Fujitsu, General Motors, IBM,
InfoValue, Intel, Iscan, Kodak, Lucent, NEC, NIST, Oracle, OSS
Nokalva, Panasonic, Sarnoff, Siemens, SpeechWorks, SUN,
Telcordia, Texas Inst., CECOM, Picatinny Arsenal, Verizon,
Xybernaut
• University partners:
UMDNJ, NJIT, Princeton, Stanford, MIT, Johns Hopkins, CMU,
Colorado, Cal Tech, Columbia, New Mexico State
• 86 faculty, visiting scientists, staff, and students
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Telecom-related Research at CAIP
Multimodal interfaces (NSF)
Image and speech pattern recognition (DOD)
VLSI design (NJCST)
Bio/nano mechatronics (NSF)
Applications to homeland security (DOD, CECOM)
SiC semiconductors (DARPA, Union Carbide)
Collaborative networking (DOD, NSF)
Distributed grid computing (NSF)
Data visualization (NSF)
Telemedicine/rehabilitation (NSF, Novartis)
Virtual environments (NSF)
Speech production (NIH)
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Telecom-related Research at
CAIP: Future Opportunities
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Natural communication with information systems.
Virtual environments for collaboration
Internet delivery of rehabilitative therapies
Autonomic grid computing
Systems and sensors on a chip
Detection of radioactive materials
Human imaging for dosimetry analysis
Low bit-rate communication for security
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CAIP Cumulative Impacts:
• External Contract Funding:
($17M in current contracts)
• Ph.D.’s and MS’s graduated:
• Patents filed:
• Startup companies assisted:
• CAIP spinoff companies created:
• Small business outreach, new jobs:
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$55M
213
80
20+
3
100+
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DIMACS
• The importance of discrete math and theoretical CS
(algorithm development) led Rutgers, Princeton, AT&T
Bell Labs, and Bellcore to develop strong research
groups
• In 1988, they joined to form DIMACS
• Telecommunications: AT&T Labs, Bell Labs, Telcordia,
Avaya
• Computing: NEC Research, IBM Research, Microsoft
Research, HP Labs (Princeton)
• 1989: prestigious NSF “science and technology center”
award. $10M grant largest at Rutgers. NJCST played
important role.
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Telecom-related Research at
DIMACS
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next generation networks technologies
computational information theory and coding
communication security
simulations of communication architectures
computer-aided verification of software
massively parallel computing
massive data sets
applications of large scale discrete optimization to
communication networks
• cryptography
• complexity of interactive computing
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Telecom-related Research at
DIMACS - II
telecom researchers find new applications of their
methods:
• homeland security research
• epidemiology/public health
• computational biology
• DNA computing
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Telecom Research at DIMACS
• More than $50M in external funding for research and
education program at DIMACS since its inception
• NSF, ONR, NSA, NIH, DARPA, ICMIC (intelligence
community), Sloan Foundation, Burroughs Wellcome
Fund, NJCST, numerous companies.
• Solution of Gilbert-Pollak conjecture led to highly
efficient heuristics for design of communication
networks.
• Pioneer in field of computer-aided verification; methods
now used widely by Intel, Sun, Motorola, AT&T,
Lucent.
• Simulation software for the global internet adopted by
more than 40 companies/universities.
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Telecom Research at DIMACS
• Work on error-correcting codes led to new techniques
for the design of efficicient encoders and decoders.
• A remarkably simple on-line algorithm for bin packing
small information packets of varying sizes into bins of
fixed capacity.
• Powerful cryptographic methods for secure authorized
access.
• The “players” at DIMACS
– 230 scientists from partner universities and
companies
– partner company scientists directly involved in
DIMACS projects
– more than 1000 visitors a year
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WINLAB
• Founded in 1989
• Broad experimental and theoretical expertise in wireless
technologies
• Broad collaborative experience with industry:
– about 20 industry sponsors
– major partners brought into NJ include Intel, Nortel,
Thomson, Samsung, NTT, Sprint, Motorola,
Mitsubishi, …
• Implementing technology transfer through both sponsor
companies and startups
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Telecom Research at WINLAB
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Freebits -- short range ultra high speed communications
NJ Center for Wireless Communication
4th Generation Radio Resource Management
Adaptive Networking for 3rd Generation Cellular
Security in Next Generation Wireless
Dynamic Spectrum Management
First Generation of MUSE sensor program
Research Wireless Testbed
Cognitive Network Management
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Telecom Research at WINLAB
• Pioneer in “hot spot” wireless networking technology
now appearing at Starbucks, McDonalds, etc. through
its “infostations” program. Going out to startups and
Army STTR tech transfer.
• ~20 faculty/staff + ~40-50 students
• Currently over $2M a year in funding.
• This year won IEEE Marconi and William R. Bennett
Awards
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WINLAB: Implications for the Future
• Wireless is fastest growing segment of telecom.
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Almost 500M cell phones sold/year.
1/3 of calls in US are already wireless, not wired (FCC).
148M US subscribers,~ half the population. (FCC).
$76B Wireless revenues in 2002; 30% of telecom (FCC).
Wireless Data devices market expected to be $10B+ by end of
2003.
– 21M American users of Wireless Hot Spots by 2007 (IBM).
• 6,300 global hotspots in 2001; expect 114,000 by 2006.
(IBM).
• NJ needs a world-class center of expertise in all major
areas of wireless communications.
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Economic Impact of Wireless Research in NJ
• 100’s of new high tech jobs/year via startups and
partnerships.
• Retain high tech talent in NJ.
• Train and retain the best students.
• Diversify the telecom industrial base in NJ
through diverse wireless end-user applications, not
just the traditional (and now stagnant) core
infrastructure.
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Outline
• What is Telecom?
• The research players and their background
• A selection of research topics suggested by Rutgers
faculty
– Short synopsis
– Food for thought; aimed at stimulating discussion
July 11, 2003
Commission on Jobs Growth and
Economic Development
22
Sensor
RF
Modem/CPU
Multimodal Integrated
Wireless Sensor on-Silicon
(MUSE)
(WinLAB, ECE, BME, CS, UMDNJ, GaTech)
• Today, sensors are individual units as transistors once
were.
– Temperature, pressure, light, chemicals, etc.
– Expensive controllers, readouts, and
communications
– Usually physically large and often hand-made.
• With new technology, we should be able to link
sensors in complex networks to gather information in
new ways.
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Multimodal Integrated
Wireless Sensor on-Silicon
(MUSE)
• Networks of Sensors:
– Applications to medicine, consumer, environment,
security, military, etc.
– Need new wireless networking technology
– Need ultra-low cost sensors and controllers
• New sensor technology that can measure many
properties
• Ultra low power electronics, algorithms, and
protocols
• All on one chip, reusing as much of integrated
circuit technology as possible
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Multimodal Integrated
Wireless Sensor on-Silicon
(MUSE)
• Low Cost, Wireless Networked Sensors
– Strongly multidisciplinary program
– Draws in all levels of technology from devices to
networks to applications and security.
– Build on strengths of the partners and ongoing
programs.
– Too large to tackle without cohesive program with a
shared vision and strong core funding.
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Multimodal Integrated
Wireless Sensor on-Silicon
(MUSE)
• Economic impact for NJ
– Market for integrated sensors estimated at $3B in
2005 and $10B in 2010
• This is before security adders or changes in
military needs.
– Can build on existing industrial partnerships and
experience to make the technology transfer happen.
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Locating Mobile Users
• Estimating the location of wireless communications
users attracts huge attention
• Applications include
– location-aware services
• finding the nearest vending machine or printer
• finding the nearest buyer or seller in a market of
buyers and sellers
• in a museum setting, presenting artifact-specific
descriptions on a handheld device
• locating a misplaced handheld device
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Locating Mobile Users
• Other applications:
– emergency location
• identifying the room location
of a crime victim
• in a prison setting, locating a
distressed guard
– access control
• blocking access to a Wi-Fi
network from outside a
building
• blocking access for specific
users from specific locations
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Locating Mobile Users
• Team from Rutgers (Statistics Dept.) and Avaya
Inc. (wireless expertise) have developed novel and
highly sophisticated statistical algorithms unlike
any of the existing approaches
• Substantially more accurate location estimation
with dramatically less training data
• Immediate application in enterprise settings
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Locating Mobile Users
• Every major telecommunications company
working on this problem
• Tremendous commercial potential
• Avaya team has significant experience with
wireless technology and markets
• Rutgers has a long track record of funding and
innovation in statistical methods
• Urgent need for seed funding for experimentation
and software development
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Massive Data Analysis Lab
(MassDAL)
• Agenda: Gather,
manage and process
massive data logs---Web, IP/wireless
traffic data, location
trajectories of objects,
sensor readings of
physical world.
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Massive Data Analysis Lab
(MassDAL)
• Key Challenges:
– Scale: Beyond the traditional “human” scale. Eg., IP data
at a single router interface for an hour exceeds total
yearly worldwide credit card transactions!
– Data Collection: probes/sensors with associated data
quality and communication problems.
• Need breakthroughs in Mathematics, Algorithms, Systems
and Engineering, to meet these challenges.
• Potential: Major impact in Telecom, Transportation and
Society-at-large.
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State of MassDAL
• Engineering:
– Consulting in analysis of wireless network logs. Client: AT&T
Wireless, 3rd largest in US, 20 Million customers.
Terabytes/month. Current value: $3M per year. 5 pers. Fully
operational, telco-grade! Interest from Cingular wireless.
– Incorporated novel algorithms in operational IP network data
analysis tools. Current partner: AT&T. Potential partner: Lucent.
• Mathematics and Computer Science.
– Algorithms, Databases, Statistics, and Data Mining on novel
models and algorithms.
– Supported by NSF grants. Partners: Rutgers CS, DIMACS, MIT.
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State of MassDAL (Contd)
• Science
– Developing wearable sensors for
tracking location of objects as well as
“interactions” between objects.
– Current partner: Telcordia. Their initial
investment: $300K/3 months (est).
Potential partner in works: Los Alamos
National Lab.
– Potential: Analysis of social networks
for Epidemiology and Homeland
Security.
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Future of MassDAL
• Research: Need breakthrough research in mathematics,
systems, databases, algorithms, sensor networking.
• Expand data domains.
– Potential partners: Google, NJ auto insurance fraud data, USPTO
patent data, AWS location trajectories, etc.
• Build state-of-art facility at Rutgers.
– Secure, 24x7, data hosting and analysis infrastructure capable of
gathering and processing petabytes of data/month across
domains, data sources, etc. Unique in the world!
• Potential.
– Every wireless, telecom, internet service provider is looking to
farm out this crucial piece of their operations. Estimated market
for these services: 100’s of millions in US $ per year. Crucial for
NJ State. Interest from multiple VCs now.
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Visualizing, Monitoring, and
Analyzing Network Data
(Statistics Dept. and Avaya Labs)
• Communication networks are widespread.
• Typical data provides a partial view of flow-data (e.g.,
on links)
• Analyzing network data is important in:
– network planning and design
– monitoring flaws
– measuring reliability parameters
– determining suitability of the network for different
transmission functions (voice, data, voice over IP…)
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Visualizing, Monitoring, and
Analyzing Network Data
Challenges
• Network data is complex and of high dimensionality.
• Statistical methods for analyzing network data are few
and far between.
• Visualizing data helps us to spot trends quickly.
• Need is to develop high quality, practical, statistical and
data analytic tools for understanding data from partial
views and limited measurements.
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Visualizing, Monitoring, and
Analyzing Network Data
• Results potentially useful for other kinds of networks:
transportation, social, …
• Such tools of great importance in telecom.
• Research in this area already funded through NSF and
NSA
• New methods/products should be very useful to NJ
companies.
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Self-Healing Dependable Computing
• Computer, Heal Thyself
– Scientific American, July 2003
• We need systems that
– monitor themselves
– adjust hardware and software
configurations to match demand
– predict and diagnose problems and
effect repairs
– defend against hacker attacks
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Self-Healing Dependable Computing
Key Concerns
• Susceptibility to attack
– Do denial-of-service attacks and viruses cause problem?
• Performability
– Is system available with adequate performance when
needed?
• Dependability
– Can you rely on correct and predictable behavior?
• Self-awareness and autonomy
– Does your system monitor and repair itself?
• Fail-safe uses
– Would you trust your computer with a mission-critical
task?
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Self-Healing Dependable Computing
State of the Art needs to be refocused!
• Information Technology is predicated on
well-behaved, interacting machines
• but spam, viruses, and attacks are epidemic
• To combat these problems we are
pouring valuable resources into firewalls
• however firewalls restrict interaction!
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Self-Healing Dependable Computing
Solutions
• Be realistic about computing environments
– Errors, both human and computer, will always be
present
– Machines are only as well-behaved as their owners
– Viruses, spam, and attacks ARE part of the
environment
• Design systems that are self-aware and self-healing
– Hardware is fast enough and affordable
– Establish self-administered distributed policies
– Continuously monitor, diagnose, and adapt
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Self-Healing Dependable Computing:
Economic Impact
• On the global IT sector
– System downtime will become increasingly costly
– Without self-healing systems salaries will dominate IT
costs
• On New Jersey – build on strengths
– Two of the six NJ growth clusters are related to IT
– NJ is center of telecom industry
– NJ has the largest number of scientists/engineers per
capita
• Experienced workforce is available for new initiatives
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Self-Healing Dependable Computing:
Rutgers Expertise
• Active research in several related areas
– autonomous agents, change analysis for OO languages,
component-based scalable networks, database mining,
distributed systems, fault tolerance, peer-to-peer computing,
secure services, modeling and simulation
• 7 CS faculty are currently working on relevant research
• $3.5M in external grants awarded over last few years
• Active industrial collaboration
– Panasonic (Peer-to-peer computing)
– IBM (change analysis for OO languages)
– Telcordia and Rutgers CS are developing a joint initiative in
this area
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Multimodal Human-Machine Interface
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Multimodal Human-Machine Interface
Real-world trial with NJ National Guard
Microphone
Array
Gaze Tracker
Force Feedback Glove
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User interface for interaction and
collaboration with robots and humans
NSF Equipment Grant EIA#98-18313 Center for Advanced Information Processing,
Rutgers University, Piscataway, NJ 08854.
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PI: J.L. Flanagan, co-PIs: J. Wilder, I. Marsic, M. Krane
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Portable Interactive Command Console (PICC)
Internet
HQ/VEHICLE
Loudspeakers
Flatpanel
display
Source locator microphone
Gaze tracker
Stereo face tracking cameras
Steerable microphone array
element
Light pen
Sensors
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Robotic Vehicles
Emergency Responder in the 48
Field
Pervasive and Autonomous
Computing
WinLAB, ECE, CS
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Pervasive and Autonomous
Computing
WinLAB, ECE, CS
• Communication and computing cost and
performance have been improving by 2x every 18
months or less for decades.
• Wireless now makes it possible to complete the
last link to people, machines, sensors, etc.,
everywhere.
• Great opportunity (and challenge) to move from
point-to-point communication to pervasive
communication, computing and knowledge access.
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Pervasive and Autonomous Computing
• Computing and communication can be
integrated in the environment
– Knowledge, information, communication always
available, but less obtrusive
• Your personal “Radar O’Riley” is there to help,
wherever you are (and gone when you want privacy)
• Sensors bring realtime data that matters
– From your heartbeat to traffic jams and afternoon
weather
• The world’s knowledge is always available when
needed.
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Pervasive and Autonomous Computing
• Massive (and interesting) Research Challenges
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Flexible system integration
New approaches to networking at all levels
Information-centric parallel and grid computing
Energy efficiency at all levels
Context awareness for communication and applications
Location awareness in routing and computing
Effective and user friendly security at all levels
• Integrating of Computing and Communication
(especially wireless) is already a major corporate
thrust at Intel, Microsoft, IBM, and many others.
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Pervasive and Autonomous Computing
• Rutgers has expertise and ongoing programs in
these areas.
• Communications and computing affect every
aspect of the economy and every individual
• Recent events show the limitations of the existing
models for Telecom. NJ could take the lead in
changing the landscape.
New Jersey has the right combination of people,
expertise, facilities to make it happen.
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Trusted Computing/Authentication
Rutgers – Camden (CS)
• Security is the fastest growing sector of the
telecommunications market today
• Security involves: encryption, authentication, access
control, identity management, user provisioning, …
• Telecom often involves access to remote resources,
requiring authentication of users and monitoring of
users’ access privileges
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Trusted Computing/Authentication
Some Research Themes
•Authentication of remote users is
usually done by passwords.
•Traditional (alphanumeric)
passwords are not user-friendly
and lead to security problems and
increased IT costs.
•Graphical passwords: userfriendly; provide an extremely
large password space (similar to a
cryptographic key space) and thus
are inherently more secure.
•Human-factors analysis of new
password schemes
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Trusted Computing/Authentication
Impact of Research:
•Passwords are the most common method for
authentication, but also one of the most vulnerable to
cyber as well as physical attack.
•Improved authentication will impact human-computer
interface, security.
•Will allow users to directly use passwords as
cryptographic keys
•Collaborations: Drexel, Brooklyn Poly., Minnesota
•Collaborations: Unisys
•Password research is of great interest to software and
telecommunications industries.
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Trusted Computing/Authentication
Other Research Challenges:
• Location-aware authentication/provisioning
• Dynamically changing access control and
inference management
• Biometrics
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Telecom and Homeland Security
• Communication security
– wireless security
– sharing data
– information privacy
– identity theft
– secure e-commerce
• Emergency Communication
• Sensor Networks for
Bio/Chemical Hazard
Monitoring
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Telecom and Homeland Security
• Rutgers projects in communication security include:
– tunable, programmable, adaptive filters for secure
communication (Engineering School)
– low bit-rate coding of speech signals for secure
communications (CAIP) (with Sarnoff)
– information privacy (DIMACS) (with HP Labs NJ,
Telcordia, AT&T Labs, NEC Labs)
– secure e-commerce (CS with Fogbreak Software)
• These projects are funded by NSF, DARPA, NJCST
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Telecom and Homeland Security
• Rutgers projects in emergency
communication include:
– infostations for rapid
wireless communication for
first responders (WINLAB)
(with Mayflower Radio)
– rapid networking at
emergency locations
(DIMACS with Telcordia)
– rapid telecollaboration
(CAIP)
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These projects are
funded by DARPA
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Telecom and Homeland Security
• Rutgers project in
sensor networks with
application to
bio/chemical hazard
monitoring:
– WINLAB
– partnered with
Agere, Sarnoff,
Semandex,
Thomson, J&J,
Lucent
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Telecom and Homeland Security
• Methods used in telecom are coming to be useful in
homeland security research.
• Provides a great business opportunity for NJ’s telecom
industry.
• Already, NJ telecom companies are subcontractors to
Rutgers federal grants in this area.
• Examples are:
– surveillance/detection methods
– bioterrorism sensor location
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Telecom and Homeland Security
• Surveillance/detection:
– Massive data set methods used in
fraud detection, network intrusion
detection, etc. are being used in
bioterrorist attack detection,
emerging disease identification.
• DIMACS, $3M from NSF, ONR,
Sloan Foundation, Burroughs
Wellcome Fund
• cooperating with AT&T, Lucent,
Telcordia, Merck, state and local
health departments, CDC
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anthrax
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Telecom and Homeland Security
• Surveillance/detection:
– MDS methods also
used in monitoring
streams of text
messages for “new
events”
• DIMACS, $1M from
ICMIC (intelligence
community)
• cooperating with
AT&T, Telcordia
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Telecom and Homeland Security
• Bioterrorism
sensor location
BASIS bioterroism
sensor system
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Telecom and Homeland Security
• Bioterrorism sensor location
– Network design methods useful.
– “Equipment placing” algorithms developed for
broadband access at Telcordia are candidates for
modification for sensor placement problems.
– Algorithms developed at Telcordia for placing
regenerating equipment in transparent optical
networks are also relevant.
– Work at DIMACS with partners from AT&T Labs,
Telcordia, Industrial Engineering, Environmental and
Occupational Health and Safety Institute (joint with
UMDNJ), Statistics, CS, and RUTCOR
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Telecom and Homeland Security
• Thus, homeland
security research
can put NJ telecom
back to work.
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