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.
1
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-orderġ-Ģ
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
Leaders in Instrumentation, Controls & ElectronicsPartners in Economic Growth
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
29
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
Leaders in Instrumentation, Controls & ElectronicsPartners in Economic Growth
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)
46
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]
47
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.
49
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)
Leaders in Instrumentation, Controls & ElectronicsPartners in Economic Growth
Software Engineering: Software Engineering: Middleware and AgentsMiddleware and Agents
Vincenzo LiberatoreVincenzo Liberatore
Software Engineering
53
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)
54
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
55
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
58
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
59
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
60
Agent typesAgent types
On-board controllers
Thin-legacy layer
GUI, interface
Virtual Robots: The Core
61
Hierarchical organizationHierarchical organization
Chain of command
62
ExampleExample
RPCS
Agent-basedsoftware
MoveTo
Open/Close
Virtual Supervisor
Leaders in Instrumentation, Controls & ElectronicsPartners in Economic Growth
Security: Security: Post-deployment Validation Post-deployment Validation
Andy PodgurskiAndy Podgurski
Security
64
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”
65
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
66
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
67
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August 3, 2005January 31, 2006