1 January 31, 2006 Leaders in Instrumentation, Controls & Electronics Partners in Economic Growth.

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August 3, 2005January 31, 2006

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• High-Tech Manufacturing:– Measuring and Control Instruments - Instrumentation - Controls– Computers & Peripheral Equipment– Communications Equipment– Consumer Electronics– Electronic Components and Access– Semiconductors– Defense Electronics– Photonics– Electromedical Equipment

• Communications Services: Wired, Wireless, Satellite

• Software and Tech Services: Software Publishers, Computer System Design, Internet, Engineering

ICEICE

ICE is High-TechICE is High-Tech

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ICE is Membership ICE is Membership

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Target MarketTarget Market

Primary Customers (at the present time):Primary Customers (at the present time):• Industry – existing members:Industry – existing members:

– ABBABB– RockwellRockwell– KeithleyKeithley– OrbitalOrbital

• Industry – new membersIndustry – new members• NASA NASA

– Moon, MarsMoon, Mars• Test bedTest bed• Manufacturing in spaceManufacturing in space

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Academic InvolvementAcademic Involvement

• Primary Partners Primary Partners – Case, Akron, CSUCase, Akron, CSU

• Secondary PartnersSecondary Partners– NASA, OSU, Kent StateNASA, OSU, Kent State

• Developing/Expected PartnersDeveloping/Expected Partners– University of Dayton, University of Cincinnati, University of Dayton, University of Cincinnati,

Youngstown State, Toledo, Zane State, Stark State, Youngstown State, Toledo, Zane State, Stark State, Cleveland Institute of Art Cleveland Institute of Art

Mark Tumeo

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Research, Products, and ServicesResearch, Products, and Services

• Pieces Already In PlacePieces Already In Place

– ““Translational Research” fund in place:Translational Research” fund in place:

• Initially funded by Federal grant and private donorsInitially funded by Federal grant and private donors

• Board of Directors led by businessBoard of Directors led by business

– Venture Capital access:Venture Capital access:

• Through Ohio Innovation Fund provide direction and Through Ohio Innovation Fund provide direction and guidance on accessing venture fundsguidance on accessing venture funds

• Through Through Jumpstart, IncJumpstart, Inc. provide professional review, . provide professional review, support and potential funding for most promising support and potential funding for most promising Start-upsStart-ups

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Research, Products, and ServicesResearch, Products, and Services• Pieces Already In PlacePieces Already In Place

– Pre-arranged Intellectual Property Agreements Pre-arranged Intellectual Property Agreements for Ohio ICE Members: for Ohio ICE Members: • Sets mutually accepted terms on ownership, licensing Sets mutually accepted terms on ownership, licensing

and royalty arrangements for ALL types of research and royalty arrangements for ALL types of research fundingfunding

• Eliminates uncertainty and reduces “administrative” Eliminates uncertainty and reduces “administrative” delays for research contractsdelays for research contracts

– Network of higher education institutions across Network of higher education institutions across Ohio: Ohio: • Provides access right at industry’s “back door” Provides access right at industry’s “back door” • Leverages the 3Leverages the 3rdrd Frontier “Dark Fiber” Network to Frontier “Dark Fiber” Network to

provide access statewideprovide access statewide

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ICE is researchICE is research

• Industry-University ConsortiumIndustry-University Consortium– Integration of computing, communication, measurement, and Integration of computing, communication, measurement, and

controlcontrol– Align the technology needs of industry with the multifunction Align the technology needs of industry with the multifunction

needs of academianeeds of academia– Increase research support for electrical engineering and Increase research support for electrical engineering and

computer sciencescomputer sciences

• ResearchResearch– Perform industrially relevant research that improves Perform industrially relevant research that improves

industrial capacity, production and efficiencyindustrial capacity, production and efficiency– Perform research that develops new concepts, processing Perform research that develops new concepts, processing

methods, and new analytical techniquesmethods, and new analytical techniques

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Research Products & ServicesResearch Products & Services

Research is 100% industry driven!Research is 100% industry driven!• Technical Advisory Committee (TAC):Technical Advisory Committee (TAC):

– Representation from industry and academiaRepresentation from industry and academia– Confirm focus of the research is in alignment with needs of ABB, Confirm focus of the research is in alignment with needs of ABB,

Keithley, Rockwell, and other Industrial Partners Keithley, Rockwell, and other Industrial Partners – Review, refine, approve proposals submitted by associated Review, refine, approve proposals submitted by associated

UniversitiesUniversities– Process tested over the last six months: Case/Akron proposalProcess tested over the last six months: Case/Akron proposal

• Industry Benefits:Industry Benefits:– New talent trained in fields of instrumentation, controls, and New talent trained in fields of instrumentation, controls, and

electronicselectronics– Help advance state-of-the-art and provide new employees with Help advance state-of-the-art and provide new employees with

these state-of-the-art skills. these state-of-the-art skills. – Neutral workshop with competitors where can work on compatibility Neutral workshop with competitors where can work on compatibility

between products and develop industry standardsbetween products and develop industry standards

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Research NeedsResearch Needs

• Sensor issuesSensor issues

• Advanced Motion Control issuesAdvanced Motion Control issues

• Networked, Distributed Control issuesNetworked, Distributed Control issues

• Hard to separate these three areas as each Hard to separate these three areas as each impacts the bigger issues that companies impacts the bigger issues that companies such as ABB, Rockwell, etc. are trying to solvesuch as ABB, Rockwell, etc. are trying to solve

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Networked ControlNetworked Control

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Networked ControlNetworked Control

• Computing in the Computing in the physical worldphysical world

• ComponentsComponents– Sensors, actuatorsSensors, actuators– ControllersControllers– NetworksNetworks

• EnablesEnables– Operations in hazardous Operations in hazardous

environmentsenvironments– Timely remote supportTimely remote support– Continuous operationsContinuous operations

• Remote monitoringRemote monitoring• TroubleshootingTroubleshooting

– Reduce time, effort, cost to Reduce time, effort, cost to develop and upgrade develop and upgrade applicationsapplications

• Merge cyber- and physical- Merge cyber- and physical- worldsworlds

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ExampleExample

• Physical environmentPhysical environment– Pipes, leversPipes, levers– SwitchesSwitches

• Sample task Sample task – Close leverClose lever

• RobotRobot– ActuatorsActuators

• Arm, gripperArm, gripper– SensingSensing

• Force feedbackForce feedback• Visual feedbackVisual feedback

– ControlControl• Local compliant controlLocal compliant control

• Remote supervisionRemote supervision

(Joint work with W. Newman, A. Al-Hammouri)(Joint work with W. Newman, A. Al-Hammouri)

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Networked ControlHardware

Diagnostics

Software Engineering

Security

Leaders in Instrumentation, Controls & ElectronicsPartners in Economic Growth

Wireless Sensor Platform for Wireless Sensor Platform for Harsh EnvironmentsHarsh Environments

Prof. Steven L. GarverickProf. Steven L. GarverickX. Yu, L. Toygur, Y. He, M. CraneX. Yu, L. Toygur, Y. He, M. Crane

Hardware

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• ObjectivesObjectives– Low-power and robust, wireless microsensorsLow-power and robust, wireless microsensors

• Unobtrusive sensing Unobtrusive sensing • Harsh operating conditionsHarsh operating conditions

– High temperatureHigh temperature– Mechanically/chemically active environmentsMechanically/chemically active environments

• ApplicationsApplications– Automotive, aerospace, and geothermal industriesAutomotive, aerospace, and geothermal industries– In-vivo tissue and blood sensing for health monitoring and In-vivo tissue and blood sensing for health monitoring and

treatmenttreatment– In-situ monitoring of liquids and gasses for contamination In-situ monitoring of liquids and gasses for contamination

control and securitycontrol and security

Wireless Sensor PlatformWireless Sensor PlatformObjectives and ApplicationsObjectives and Applications

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Sensorfmax:7.5KHz

8bit,1st-orderƒ°-ƒ¢

15 kHz 125 kbps

8bits

Vin+

Vin-1bit

Vdd Vss

2nd-orderDecimation

FilterP/S VCO

fs/2500KHz

fd/27.5KHz

Sig

nal M

agni

tude Deci

mation fil

ter

Noise a

fter d

ecim

ation

Quantization Noise

start stopdata

Sensorfmax:7.5KHz

SOI IC

8-bit 1st-order ADC

1 MHz

8bits

+

-1bit

Vdd Vss

2nd-orderDecimation

FilterP/S VCO

fs/2500KHz

fd/27.5KHz

Sig

nal M

agni

tude Deci

mation fil

ter

Noise a

fter d

ecim

ation

Quantization Noise

start stopdatastart stopdata

R+RR+R

R RPreamplifier

Rm AmpVS+

VS-

FSK

Wireless Sensor PlatformWireless Sensor PlatformApproachApproach

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VCO

Decimator

Sigma-Delta Modulator

Bias

Rm Amp

Test Structure

SOI Test ICSOI Test ICDie MicrophotographDie Microphotograph

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SOI SOI ADC ADCDC Tests at Room TemperatureDC Tests at Room Temperature

Power Power Consumption Consumption

200 200 ww

Max. Input LevelMax. Input Level 3 V3 Vp-pp-p

Dynamic RangeDynamic Range 40 dB40 dB

SNRSNRMAXMAX 55 dB55 dB

Sampling Sampling FrequencyFrequency

1 MHz1 MHz

BandwidthBandwidth 8 kHz8 kHz

Input AmplitudeInput Amplitude 3 V3 Vp-pp-p

Input FrequencyInput Frequency 3 kHz3 kHz

OSROSR 6464

-1.8 -1.4 -1 -0.6 -0.2 0.2 0.6 1 1.4 1.8-200

0

200

400

600

800

1000

1200DC Transfer Characteristic

Differential Input Amplitude (V)

DataLinear fit

Num

ber

of 1

s in

100

0 sa

mpl

es

Nominal operating conditions

Performance summary

DC transfer characteristics at room temperature

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SOI SOI ADC ADCAC Tests at Room TemperatureAC Tests at Room Temperature

-40 -35 -30 -25 -20 -15 -10 -5 0 515

20

25

30

35

40

45

50

55

60

Input Voltage (dBFS)

SN

R (

dB

) A

ve

rag

e V

alu

e:(

*)

SNR vs. input amplitude

2 4 6 8 10 12 14

x 104

-20

-10

0

10

20

30

40

50

60

70

80

Frequency (Hz)

Am

plit

ud

e (

dB

)

@ nominal conditionsNumber of points = 16384The 16, 48, 80 .. kHz dither

FFT magnitude of the output

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SNR versus temperature

Hot Plate

. .. .

Thermal grease

Instruments

ConnectorTube

ThermocoupleDIP

High-temperature test setup

SOI SOI ADC ADCHigh Temperature TestHigh Temperature Test

27 50 100 150 200 250 300-10

0

10

20

30

40

50

60

Temperature (°C)

SN

R (

dB)

@ nominal conditions

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SOI RSOI Rmm Amplifier Amplifier

Test SetupTest Setup

• DIP packageDIP package– Pin coupling > 15 fF caused Pin coupling > 15 fF caused

oscillation at ~1 MHzoscillation at ~1 MHz• Gold-on-ceramic module using Gold-on-ceramic module using

bare diebare die– Oscillations continueOscillations continue– With CWith CL L = 100 pF, oscillations stop = 100 pF, oscillations stop

and BW and BW 700 kHz 700 kHz

Ceramic-on-gold ModuleMeasurement setup for Rm amplifier

Rm Amplifier

CinRin

Vin CL

Vout

SOI IC

Tunnel diodeResistor

SOI IC

Capacitor

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SOI RSOI Rmm Amplifier Amplifier High Temperature Test ResultsHigh Temperature Test Results

AC response for different temp

1.00E+04

1.00E+05

1.00E+06

1.00E+07

1.00E+08

1.00E+02 1.00E+03 1.00E+04 1.00E+05 1.00E+06 1.00E+07

Frequency(Hz)

Gai

n(o

hm

s)

Gain(25 °C)

Gain(50 °C)

Gain(100 °C)

Gain(150 °C)

Gain(200 °C)

Gain(250 °C)

Gain(270 °C)

Gain(300 °C)

Rm = ~ 8 M~500 kHz

Magnitude response vs. frequency

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Passband Gain v.s. Temperature

0.00E+00

1.00E+06

2.00E+06

3.00E+06

4.00E+06

5.00E+06

6.00E+06

7.00E+06

8.00E+06

9.00E+06

0 50 100 150 200 250 300

Temperature(°C)

Passb

an

d G

ain

(O

hm

s)

Passband bandwidth v.s. Temperature

0.00E+00

2.00E+05

4.00E+05

6.00E+05

8.00E+05

1.00E+06

1.20E+06

1.40E+06

0 50 100 150 200 250 300

Temperature(°C)P

assb

and

band

wid

th (H

z)

• The frequency response for temperatures up to 250 The frequency response for temperatures up to 250 C is nearly ideal:C is nearly ideal: RRmm = 8.3 Meg = 8.3 Meg, f, fLL = 1 kHz, f = 1 kHz, fHH = 500 kHz = 500 kHz

• The transimpedance gain decreases at temperatures above 250 The transimpedance gain decreases at temperatures above 250 CC• The amplifier continues to function well at temperatures up to 300 The amplifier continues to function well at temperatures up to 300 CC

Passband gain vs. Temperature Passband bandwidth vs. Temperature

SOI RSOI Rmm Amplifier Amplifier High Temperature Test SummaryHigh Temperature Test Summary


Diagnostics and Prognostics: Diagnostics and Prognostics: Sensor and Algorithm for Health Sensor and Algorithm for Health Monitoring in Industrial SystemsMonitoring in Industrial Systems

Kenneth A. LoparoKenneth A. Loparo

Diagnostics

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Motor and Gearbox Motor and Gearbox Diagnostics and PrognosticsDiagnostics and Prognostics

Gear Diagnostics

Bearing Diagnostics

Motor Diagnostics:-rotor unbalance-rotor bar faults-stator winding faults

Motor and GearboxHealth Monitoring

System

Lube Diagnostics

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Lubricant Health Monitoring: Signal Lubricant Health Monitoring: Signal Processing, Diagnostics and Processing, Diagnostics and

PrognosticsPrognostics

preprocessingSensor

1

preprocessingSensor

n

Estimationof

LubricantHealth

Indicators

Indicator1(1)

DataAssociation

Lubricant information

RemainingUseful lifeEstimation

Decisionfusion

Indicator m(1)

Indicator1(n)

Indicatorm(n)

Water contamination

overheating

HistoryHistory

MEMS Sensor Feature Extraction Data LevelFusion

Lubricant Failure Space

DecisionLevel fusion

TemperatureTANElectroChemicalConductivity

MachineHealthAssessment

MachineHealthPrediction

Lubricant HealthEstimation

Feature vectors

History

History

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Experimental Results (Prognosis)Experimental Results (Prognosis)

SKF6204 Bearings• Failed in 50 days• Speed = 10012 rpm• Load = 340 lbs (axial)• T = 260oF• Fs = 24 kHz

HMM Probabilities given HMM for Normal Condition

0 5 10 15 20 25 30 35 40 45 50-8000

-7000

-6000

-5000

-4000

-3000

-2000

-1000

0

Day

Log

Pro

babi

litie

s

Log

Pro

babi

lity


Networked Control SystemsNetworked Control Systems

Michael S. BranickyMichael S. Branicky

Networked Control

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Networked Control SystemsNetworked Control Systems• Numerous distributed agents• Physical and informational dependencies •Control loops closed over heterogeneous networks

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Fundamental IssuesFundamental Issues• Time-Varying Transmission Period• Network Schedulability• Network-Induced Delays• Packet Loss

[Branicky, Phillips, Zhang: ACC’00, CSM’01, CDC’02]

Plant

Controller

h(t)

Plant

Controller

h

DelayDelay

Plant

Controller

r

Plant

Plant

Controller

Controller

.

.

.N

etw

ork

h1(t)

hN(t)

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Control and Scheduling Co-Control and Scheduling Co-DesignDesign

• Control-theoretic characterization of stability and performance (bounds on transmission rate)

• Transmission scheduling satisfying network bandwidth constraints

Simultaneous optimization ofboth of these = Co-Design

Plant

Plant

Controller

Controller

.

.

.

Net

wor

k

h1(t)

hN(t)

[Branicky, Phillips, Zhang: CDC’02]

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Co-Simulation MethodologyCo-Simulation Methodology

Simulation languages

Bandwidthmonitoring

VisualizationNetwork dynamics

Plant output dynamics

Packet queueing and forwarding

Co-simulation of systems and networks

Plant agent(actuator, sensor, …)

Router

Controlleragent(SBC, PLC, …)

[Branicky, Liberatore, Phillips: ACC’03]

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Co-Simulation Components (1):Co-Simulation Components (1):Network Topology, ParametersNetwork Topology, Parameters

ns-2 package used to simulate network at packet level: • state-of-art, open-source software• follows packets over links• queuing and de-queuing at router buffers• GUI depicts packet flows• can capture delays, drop rates, inter-arrival times

Our simulations (heterogeneous links, diff. queue sizes): • Fast Ethernet links, switches, 48B packets• T1 line with 1.544 MB/s (from router to controller)• FTP cross-traffic: TCP SACK/DelAck, Internet params.

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Extension of ns-2 release (written by Liberatore):• plant “agents”: sample/send output at specific intervals• control “agents”: generate/send control back to plant• dynamics solved numerically using Ode utility, “in-line” (e.g., Euler), or through calls to Matlab

Co-Simulation Components (2):Co-Simulation Components (2):Plant and Controller DynamicsPlant and Controller Dynamics

Our simulations (scalar, NL inv. pendulum, aircraft):• identical unstable plants, sensors sampling periodically• controller stabilizes plant, which is event-based• actuators receive/exert control and are event-based• one (distinguished) plant

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Analysis and Design ToolsAnalysis and Design Tools• Stability Regions [Zhang, EECS, Ph.D., May 2001]• Traffic Locus [Hartman, EECS, M.S., Jun. 2004]

Both for an inverted pendulum on a cart (4-d), with feedback matrix designed for nominal delay of 50ms. Queue size = 25 (left), 120 (right)

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SummarySummary

• Reviewed Networked Control Systems (NCS)Reviewed Networked Control Systems (NCS)

• Summarized Fundamental Issues, Co-DesignSummarized Fundamental Issues, Co-Design

• Introduced a Co-Simulation Methodology, CodeIntroduced a Co-Simulation Methodology, Code

• Presented Analytical/Design Tools:Presented Analytical/Design Tools:

Scaling, Heterogeneity (links, traffic)Scaling, Heterogeneity (links, traffic)


Software Engineering: Software Engineering: Middleware and AgentsMiddleware and Agents

Vincenzo LiberatoreVincenzo Liberatore

Software Engineering

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MiddlewareMiddleware

• Dealing with complex systemsDealing with complex systems• Explicit structure allows Explicit structure allows

identification, relationship of identification, relationship of complex system’s piecescomplex system’s pieces– Layered reference model for Layered reference model for

discussiondiscussion• Modularization eases Modularization eases

maintenance, updating of maintenance, updating of systemsystem– Change of implementation of Change of implementation of

layer’s service transparent to layer’s service transparent to rest of systemrest of system

– E.g., change in data link doesn’t E.g., change in data link doesn’t affect rest of systemaffect rest of system

Application(the control application, e.g., close-lever)

Middleware(common to multiple applications,

e.g., resource discovery)

Transport(e.g., TCP, RTP/UDP)

Data Link(low level communication, e.g. Ethernet, Infinet, etc.)

Network(convergence layer: IP)

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Resource DiscoveryResource Discovery

• Plug-and-playPlug-and-play– Add new resources on Add new resources on

the flythe fly– Example: USBExample: USB

• Plug in a USB camera Plug in a USB camera on a USB porton a USB port

• But now we want: on a But now we want: on a network, with arbitrary network, with arbitrary unitsunits

• ExampleExample– Locate a robot on the Locate a robot on the

networknetwork

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JiniJini

• OperationsOperations– Discover, Join, Look-up, UseDiscover, Join, Look-up, Use

• ProgrammingProgramming– Include a libraryInclude a library– Use functionsUse functions

• Fault-toleranceFault-tolerance– LeasesLeases

• Join only last for a certain Join only last for a certain time periodtime period

• Renew the leaseRenew the lease– Multiple look-up serversMultiple look-up servers– JavaSpacesJavaSpaces

• Distributed shared memoryDistributed shared memory

• URL: www.jini.orgURL: www.jini.orgCourtesy of Sun Microsystems

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MiddlewareMiddleware

• Between application and transportBetween application and transport– Libraries to provide advanced functionalityLibraries to provide advanced functionality– Hide communicationHide communication

• ApplicationsApplications– Resource DiscoveryResource Discovery– Remote Procedure CallsRemote Procedure Calls– SecuritySecurity– Interoperability (e.g., since Real-Time Corba)Interoperability (e.g., since Real-Time Corba)– Scheduling, resource management, performance analysisScheduling, resource management, performance analysis– MulticastMulticast

• Software developmentSoftware development– Simpler, fasterSimpler, faster– State-of-the-art functionalityState-of-the-art functionality

• Middleware over IPMiddleware over IP– Wealth of libraries for IPWealth of libraries for IP– Critical advantage of the Internet ProtocolCritical advantage of the Internet Protocol

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Agents: ObjectivesAgents: Objectives

• Survivability and fault-toleranceSurvivability and fault-tolerance• Safety and securitySafety and security• Cope with unstructured physical Cope with unstructured physical

environmentsenvironments• Unified protocols across human-robotic Unified protocols across human-robotic

networksnetworks• Software re-useSoftware re-use

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Agent: Objectives (contd)Agent: Objectives (contd)

• Tolerate low network Quality-of-ServiceTolerate low network Quality-of-Service– Long-haul delays, packet lossesLong-haul delays, packet losses

• Unit aggregation and cooperationUnit aggregation and cooperation• EvolvabilityEvolvability

– Re-programmabilityRe-programmability– Dynamic reconfigurationDynamic reconfiguration– ExtensibilityExtensibility

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Vision: Agent-basedVision: Agent-based

• Basic propertiesBasic properties– Autonomous, mobile Autonomous, mobile – Adaptable, flexible, reactiveAdaptable, flexible, reactive– Knowledgeable, goal-oriented, learningKnowledgeable, goal-oriented, learning– Collaborative Collaborative – PersistentPersistent

• Agents for robotsAgents for robots– Aggregation into task-oriented teamsAggregation into task-oriented teams– Evolvable Evolvable

• Re-programmability, reconfiguration, extensibilityRe-programmability, reconfiguration, extensibility

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Agent typesAgent types

On-board controllers

Thin-legacy layer

GUI, interface

Virtual Robots: The Core

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Hierarchical organizationHierarchical organization

Chain of command

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ExampleExample

RPCS

Agent-basedsoftware

MoveTo

Open/Close

Virtual Supervisor


Security: Security: Post-deployment Validation Post-deployment Validation

Andy PodgurskiAndy Podgurski

Security

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VulnerabilitiesVulnerabilities

• VulnerabilitiesVulnerabilities– Possible origin: software defectPossible origin: software defect– Present after deploymentPresent after deployment

• Must identify latent defects earlyMust identify latent defects early

• AAAAAA– Authentication, Authorization, AccountingAuthentication, Authorization, Accounting– Defect and vulnerabilitiesDefect and vulnerabilities

• E.g., OpenLDAP ITS 1530 “Anonymous user can use E.g., OpenLDAP ITS 1530 “Anonymous user can use ldapmodify to delete user attributes”ldapmodify to delete user attributes”

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Mining ProfilesMining Profiles

• ProfilesProfiles– E.g., count of function callsE.g., count of function calls– Previous objectivesPrevious objectives

• Compiler optimizationCompiler optimization• Detect defectDetect defect

– Detect related vulnerabilitiesDetect related vulnerabilities• Mining and AuditMining and Audit

– Mine and visualize profiles Mine and visualize profiles – Drives manual auditDrives manual audit

• Avoid false positivesAvoid false positives– ObjectivesObjectives

• Detect unusual executionsDetect unusual executions– Unusual executions known to be positively correlated with defectsUnusual executions known to be positively correlated with defects

• Cluster similar executionsCluster similar executions

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ExampleExample

• MethodologyMethodology– Synthetically generate Synthetically generate

executionsexecutions– Profile OpenLDAP Profile OpenLDAP

function callsfunction calls– Multidimensional scaling Multidimensional scaling

to produce 2D displayto produce 2D display

• ObservationsObservations– Troublesome executions Troublesome executions

in an identifiable clusterin an identifiable cluster

Anonymous user deletes attributes

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August 3, 2005January 31, 2006

1 January 31, 2006 Leaders in Instrumentation, Controls & Electronics Partners in Economic Growth.

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Transcript of 1 January 31, 2006 Leaders in Instrumentation, Controls & Electronics Partners in Economic Growth.