Networking Research CenterNetworking Research CenterIndustry DayIndustry Day

Penn State UniversityPenn State UniversityCollege of EngineeringCollege of Engineering

David N. Wormley, DeanDavid N. Wormley, Dean

Tuesday, October 17, 2006Tuesday, October 17, 2006

IndustryDay.ppt

NATIONAL POSITIONNATIONAL POSITION PSU ENGINEERING ranks among the PSU ENGINEERING ranks among the

largest and highest quality colleges in largest and highest quality colleges in the U.S.the U.S.

04/05 U.S. Engineering Degrees 04/05 U.S. Engineering Degrees Awarded Awarded • 2nd in B.S. degrees awarded2nd in B.S. degrees awarded• 7th in Ph.D. degrees awarded7th in Ph.D. degrees awarded

U.S. News U.S. News Engineering RankingsEngineering Rankings• 14th in U.S. undergraduate 14th in U.S. undergraduate • 19th in U.S. graduate19th in U.S. graduate

Undergraduate CurriculumUndergraduate Curriculum

Prepare World-Class Prepare World-Class Engineers:Engineers:Aware of the WorldAware of the WorldSolidly GroundedSolidly GroundedTechnically BroadTechnically BroadVersatileVersatileEffective in Team Effective in Team

OperationsOperationsEffective in LeadershipEffective in Leadership

FIRST YEAR INTERNATIONAL DESIGNFIRST YEAR INTERNATIONAL DESIGN• Collaboration with French students from Collaboration with French students from

Universite D’Artois work on Industry Universite D’Artois work on Industry Sponsored ProjectsSponsored Projects

• Design Reports written in both English and Design Reports written in both English and FrenchFrench

• Collaborations with 4 other EU UniversitiesCollaborations with 4 other EU Universities INTERNATIONAL INTERNSHIPSINTERNATIONAL INTERNSHIPS FIRST YEAR SEMINAR ON ENGINEERING FIRST YEAR SEMINAR ON ENGINEERING

IN CHINAIN CHINA

LEARNING FACTORYLEARNING FACTORY Experiential LearningExperiential Learning Teams from Penn State, Teams from Penn State,

U of Washington, U of U of Washington, U of Puerto Rico, Mayaguez Puerto Rico, Mayaguez developed Learning developed Learning FactoryFactory

In 2006, teams received In 2006, teams received National Academy of National Academy of Engineering $500,000 Engineering $500,000 Bernard Gordon Award Bernard Gordon Award for Educational for Educational InnovationInnovation

Interdisciplinary Minors

Engineering Leadership DevelopmentEngineering Leadership Development• Intended for students to supplement their major Intended for students to supplement their major

field of study with knowledge of leadership field of study with knowledge of leadership concepts, principles, practices, and techniquesconcepts, principles, practices, and techniques

• Current enrollment: 158 (13% non-engr)Current enrollment: 158 (13% non-engr)

Engineering EntrepreneurshipEngineering Entrepreneurship• Intended for students aspiring to be innovation Intended for students aspiring to be innovation

leaders of new technology-based products and leaders of new technology-based products and companiescompanies

Current enrollment: 151 in core courses; Current enrollment: 151 in core courses; 80 in higher level 80 in higher level

electiveselectivesENGINEERING:….A Creative Profession, Serving Society

Research Thrusts in Research Thrusts in Areas of State and National NeedsAreas of State and National Needs

Energy/Environment Energy/Environment Nanotechnology Nanotechnology Biomedical/BiotechBiomedical/Biotech Information Technology Information Technology Homeland SecurityHomeland Security

ENGINEERING:….A Creative Profession, Serving Society

Growth in Research ActivitiesGrowth in Research Activities

Recent increasesrepresent significant growth in interdisciplinary research. Industry funds ~ 20% of COE research.

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Research in Millions

Penn State Engineering: Penn State Engineering: Partnering with Industry on ResearchPartnering with Industry on Research

Central Industrial Research Central Industrial Research OfficeOffice• Serves as liaison between PSU and Serves as liaison between PSU and

industriesindustries

PSU – 2nd in industry sponsored PSU – 2nd in industry sponsored research in nationresearch in nation

Penn State Engineering:Penn State Engineering:Partnering with Industry on ResearchPartnering with Industry on Research

Gifts – support a variety of faculty activitiesGifts – support a variety of faculty activities Unrestricted Grants – support research activitiesUnrestricted Grants – support research activities Cooperative AgreementsCooperative Agreements

• Sponsor involvement on a collaborative basisSponsor involvement on a collaborative basis Master Agreements with IP pre-negotiation to support research Master Agreements with IP pre-negotiation to support research

through Task Orders.through Task Orders.

• Currently 45 Master Agreements are in place including:Currently 45 Master Agreements are in place including:

Northrup GrummanNorthrup Grumman KennemetalKennemetal

Toyota Manufacturing NAToyota Manufacturing NA Pratt and WhitneyPratt and Whitney

Lockheed MartinLockheed Martin RaytheonRaytheon

GMGM Corning, Inc.Corning, Inc.

Hershey FoodsHershey Foods Pittsburgh Digital Greenhouse Pittsburgh Digital Greenhouse

Network Education andNetwork Education andResearch ProgramsResearch Programs

throughout the College of Engineeringthroughout the College of Engineering

Activities centered in:Activities centered in:

• Aerospace EngineeringAerospace Engineering• Computer Science & EngineeringComputer Science & Engineering• Electrical EngineeringElectrical Engineering• Industrial & Manufacturing EngineeringIndustrial & Manufacturing Engineering• Mechanical & Nuclear EngineeringMechanical & Nuclear Engineering

Department of Department of Aerospace EngineeringAerospace Engineering

Aerospace applicationsAerospace applications

Fleets of small, low-cost Uninhabited Aerial Vehicles (UAVs) for:

•Meteorology•Surveying and remote sensing•Surveillance and target tracking

Satellite Constellations•Terrestrial Planet Finder•Darwin (ESA mission)

CSE Research AreasCSE Research Areas

Research Centers/LabsResearch Centers/Labs

Center for Embedded and Mobile ComputingCenter for Embedded and Mobile Computing (CSE, EE, Mat Sci, ME, (CSE, EE, Mat Sci, ME, Civil)Civil)• Co-Directors: Anand Sivasubramaniam and Janie IrwinCo-Directors: Anand Sivasubramaniam and Janie Irwin

Center for Networking & SecurityCenter for Networking & Security (CSE, EE, Statistics, IST) (CSE, EE, Statistics, IST)• Director: T. La PortaDirector: T. La Porta

Center for Machine Learning ApplicationsCenter for Machine Learning Applications (CSE, IST, Statistics, EE, (CSE, IST, Statistics, EE, Business)Business)• Director: R. AcharyaDirector: R. Acharya

Scalable Computing LabScalable Computing Lab (CSE, Mat Sci, EE, Aero, Math, Physics, Civil) (CSE, Mat Sci, EE, Aero, Math, Physics, Civil)• Director: P. RaghavanDirector: P. Raghavan

Center for Computer VisionCenter for Computer Vision (CSE, EE, Statistics, Civil, ME) (CSE, EE, Statistics, Civil, ME)• Director: B. CollinsDirector: B. Collins

Center for Comparative Genomics (BMB,CSE, Physics, Center for Comparative Genomics (BMB,CSE, Physics, Statistics)Statistics)• Director: W. Miller, R. HardisonDirector: W. Miller, R. Hardison

Department of Department of Electrical EngineeringElectrical Engineering

AYLIN YENERAYLIN YENERAssociate Professor of Electrical Associate Professor of Electrical

EngineeringEngineering

Recent Awards (since 2005): Recent Awards (since 2005): Two NSF grantsTwo NSF grants DARPA- CBMANET programDARPA- CBMANET program

New:New: $6.5M DARPA Grand Challenge that called for a $6.5M DARPA Grand Challenge that called for a

new new IInformation nformation TTheory for heory for MMobile obile AAd Hoc d Hoc NetNetworks (ITMANET): The winning team consists works (ITMANET): The winning team consists of Prof. Yener and 11 professors from 7 other of Prof. Yener and 11 professors from 7 other universities.universities.

Mohsen KavehradMohsen Kavehrad

Electrical Engineering Electrical Engineering DepartmentDepartment

Biologically Inspired Signal Biologically Inspired Signal ProcessingProcessing

Genetic optimization algorithmsGenetic optimization algorithms Particle swarm optimizationParticle swarm optimization Ant colony optimizationAnt colony optimization Neural network pattern Neural network pattern

recognitionrecognition

Work in different areas: Work in different areas: Antenna Design - Doug Werner Antenna Design - Doug Werner

Power Systems - Kwang Lee Power Systems - Kwang Lee

Signal Processing - Ken JenkinsSignal Processing - Ken Jenkins

Payload-Based High-Speed Network Intrusion Detection System Payload-Based High-Speed Network Intrusion Detection System (IDS)(IDS)

J. Wang, G. Kesidis, D.J. Miller, and I. HamadehJ. Wang, G. Kesidis, D.J. Miller, and I. Hamadeh

High-Speed Worm Defense by Using Both Header and PayloadHigh-Speed Worm Defense by Using Both Header and Payload

Multidimensional Traffic MiningMultidimensional Traffic Mining Frequent item set mining applied to network traffic flows, based on the

packet header 5-tuple (source IP, destination IP, source port, destination port, protocol)

Using top-down method to build up a multidimensional tree and only mining significant (with traffic volume larger than a threshold) and suspicious clusters

Worm Signature ExtractionWorm Signature Extraction Building a generalized suffix tree for each suspicious cluster, and extracting

signatures only from a small part of packets

With time and space linear in the length of each suspicious cluster

Jointly considering length, frequency and false positive to improve the accuracy of signatures

Easily modifying rules to search for multiple signature descriptions of varying length range, with little increase in complexity

Packet Header Hashing

Multidimensional Clustering

Suspicious Cluster Identification

Suspicious Cluster Pool

Multidimensional Traffic Clustering and Classification

Innocuous Packet Pool

Worm Signature Extration

Worm Signature Evaluation

Worm Signature Extraction and Evaluation

Worm Signatures

Payload-Based Worm Containment

Incoming Packets

Pipelined ImplementationPipelined Implementation

3T delay (T could be as small as 1 second): hash packets arriving in [0, T]; perform mining in [T, 2T]; collect suspicious packets and extract signatures in [2T, 3T]

Requiring 50 to 60 MB memory without packet sampling

Can handle the link with load up to 800Mbps in real-time by software

Suspicious Cluster IdentificationSuspicious Cluster Identification

Two Criteria for Defining a Suspicious Cluster:

Its traffic volume is larger than a threshold (e.g., 1%)

Its source or destination IP dispersion/cardinality is larger than a threshold. In other words, the number of different source or destination IP addresses involved in a cluster is larger than a threshold (e.g., 30)

This work is supported by NSF and DHS.

Organic Thin Film Electronics Organic Thin Film Electronics – Electronics Anywhere– Electronics Anywhere

T. N. JacksonT. N. Jackson

Center for Thin Film Devices and Materials Research Institute, Electrical Center for Thin Film Devices and Materials Research Institute, Electrical Engineering, Penn State UniversityEngineering, Penn State University

Low-cost devices and circuits on arbitrary substratesLow-cost devices and circuits on arbitrary substrates

Organic thin film transistor

polymeric substrate AMLCD

a-Si:H active matrix Gamma ray detector on

polyimide substrate

a-Si:H strain bridge array

Electronics anywhere

Transistors on cloth

a-Si:H active matrix OLED

display

Transistors on cloth

OTFTs on non-

planar surfaces

Organic display

Marcus Department of Marcus Department of Industrial and Industrial and

Manufacturing EngineeringManufacturing Engineering

Perform maintenance(Self-Healing)

Sensor Network: Clustering and routing algorithm

Health Monitoring

Maintenancegroup

Identify and respond to defects

Defect

Broadcasting information

Report data

NSF-SST: PIPELINE INFRASTRUCTURE MONITORINGNSF-SST: PIPELINE INFRASTRUCTURE MONITORING

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2000

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6000

Frequency [Hz]

Magnitude

WT

FT

0 100 200 300 400 500 600 700 8000

1000

2000

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4000

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6000

Frequency [Hz]

Magnitude

WT

FT

Sensor data fusion and data mining

T-mote sensor board

Sensor for collecting dataMiniature Wireless Sensors (Self-sustainable)

S. Kumara (PSUIE)Xiang Zhang (UCB)Sangkook Kim (MIT)

S. Bukkapatnam (OSU)

LocalInterfaceEnterprise 1

Business ObjectDocument Ontology

(2) Annotate

LocalInterface

A*

LocalInterface

ARES

ATHOS

(4)

Rec

onci

le

(1) Create

(3) Def. Rulesfor mapping

R ARGOS R

Enterprise 1

Internet

AAdvanced dvanced TTechnology for echnology for interoperability of interoperability of HHeterogeneous eterogeneous EEnterprise nterprise NNetwork & their etwork & their AApplicationspplications

LocalInterfaceEnterprise 2

(3) Def. Rulesfor mapping

Internet

Enterprise 2

(1) Partners in USA : AIAG, NIST, GM, Ford, Microsoft, IBM, SAP, and other business partners (1) Partners in USA : AIAG, NIST, GM, Ford, Microsoft, IBM, SAP, and other business partners and software vendors (and software vendors (PSUIE – Kumara & Oh support GMPSUIE – Kumara & Oh support GM) ) (2) Partners in EU : CNR in Italy, SAP in Austria, Breza in Serbia and other laboratories in (2) Partners in EU : CNR in Italy, SAP in Austria, Breza in Serbia and other laboratories in European countriesEuropean countries

Information Technology Related ResearchInformation Technology Related ResearchMechanical and Nuclear Engineering DepartmentMechanical and Nuclear Engineering Department

NSF Information Technology Research Grants:NSF Information Technology Research Grants: Data-Driven Autonomic Performance Modulation for Servers, Q. Wang

Infrastructure of the Networked Robotics & Signal Intelligence Laboratory, A. Ray

An Agent-Based Negotiation Framework for the Robust Design of Active-Passive Hybrid Piezoelectric Vibration Control Networks, K-W. Wang

Cyber-infrastructure Grant:Cyber-infrastructure Grant: Network of Design Repositories, T. SimpsonNetwork of Design Repositories, T. Simpson

NSF-ITR: Data-Driven Autonomic NSF-ITR: Data-Driven Autonomic Performance Modulation for ServersPerformance Modulation for Servers

Qian Wang, MNE DepartmentQian Wang, MNE Departmentwith A. Sivasubramaniam and N. Gautamwith A. Sivasubramaniam and N. Gautam

Objective: Objective: Self-managing large Self-managing large clusters of server systems such as clusters of server systems such as hosting centers & data centers hosting centers & data centers • Performance modulationPerformance modulation• Resource allocationResource allocation• Power managementPower management

Approach:Approach: Control-theoretic based Control-theoretic based modeling and control designmodeling and control design• Workload parameterized dynamic Workload parameterized dynamic

models and controller structuremodels and controller structure• On-line optimization & On-line optimization &

implementationimplementation

Floor with embedded piezo-electric pressure sensorsOverhead Vision based localization

Scanning Laser Rangefinder Dedicated Wireless Network

Infrastructure of theInfrastructure of the Networked Robotics Networked Robotics & Signal Intelligence Laboratory& Signal Intelligence Laboratory

Asok Ray, MNE DepartmentAsok Ray, MNE Department

NSF-ITR: An Agent-Based Negotiation Framework for the NSF-ITR: An Agent-Based Negotiation Framework for the Robust Design of Active-Passive Hybrid Piezoelectric Robust Design of Active-Passive Hybrid Piezoelectric

Vibration Control Networks –Vibration Control Networks – KW Wang, MNE DepartmentKW Wang, MNE Department

Controller

V VV

To Distributed Actuators

Distributed Circuitry

Controller

V VV

To Distributed Actuators

Distributed Circuitry

Distributed piezo-transducers and multiple-branch circuitry networks with

active source and passive circuits

Significantly increase smart structure DOF and design space System much more adaptable to advanced monitoring and control

Solve Ricatti / Lyapunov Equations

and Active Gains

Calculate Cost Function J

Models of Different Topology

TopologySelection

Agent FL-basedNegotiation

Agent

Energy Power-

concernedAgent

Vibration-concerned

Agent

RobustnessAgent

Selected Topology

Design variables Fitness

Robustness requirement

Weights

FIRST LEVEL

SECOND LEVEL

THIRD LEVEL

GA-basedSensitivity

Agent

GA-basedOptimization Agent

Solve Ricatti / Lyapunov Equations

and Active Gains

Calculate Cost Function J

Models of Different Topology

TopologySelection

Agent FL-basedNegotiation

Agent

Energy Power-

concernedAgent

Vibration-concerned

Agent

RobustnessAgent

Selected Topology

Design variables Fitness

Robustness requirement

Weights

FIRST LEVEL

SECOND LEVEL

THIRD LEVEL

GA-basedSensitivity

Agent

GA-basedOptimization Agent

Advanced design framework - Agent-based information

technology for robust design, tradeoff negotiation and circuit

topology synthesis Aims to incorporate/learn

knowledge and heuristics to assist designers to address high-level smart structure design issues in a systematic way

Two NSF CI-TEAM AwardsTwo NSF CI-TEAM Awards Prof. Tim Simpson is leading two multi-university NSF CI-TEAM1 projects to

develop a cyber-infrastructure-based network of design repositories to support innovative education and instruction in product design and development

MNE, IME, SEDTAPP, IST, and Psychology faculty involved at Penn State

Partner institutions include:

1. Northwestern University

2. Bucknell University

3. Drexel University

4. Virginia Tech

5. SUNY-Buffalo

6. Sweet Briar College

7. Norfolk State University

8. University of Missouri-Rolla

Cyber-infrastructure GrantsCyber-infrastructure GrantsT. Simpson, MNE Department

1CI-TEAM = Cyber-infrastructure Training, Education, Advancement, and Mentoring Program

Repository(VaTech)

Repository(Drexel)

Repository(Penn State)

PartneredRepositories

Penn State is continuing to build leading Penn State is continuing to build leading educational and research programs.educational and research programs.

A significant initiative in the College -- A significant initiative in the College -- network focused programs.network focused programs.

SUMMARYSUMMARY