Week 1 Lectures 1
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Transcript of Week 1 Lectures 1
Week 1 Lectures 1Introduction to CPS
Instructor: Prof. Fei Hu, ECE, Univ of Alabama
Computing Evolution
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CPS: Computing Perspective
• Two types of computing systems– Desktops, servers, PCs, and
notebooks– Embedded
• The next frontier– Mainframe computing (60’s-70’s)
• Large computers to execute big data processing applications
– Desktop computing & Internet (80’s-90’s)
• One computer at every desk to do business/personal activities
– Embedded computing (21st Century)
• “Invisible” part of the environment
• Transformation of industry
• Number of microprocessor units per year– Millions in desktops– Billions in embedded processors
• Applications:– Automotive Systems
• Light and heavy automobiles, trucks, buses
– Aerospace Systems• Airplanes, space systems
– Consumer electronics• Mobile phones, office electronics,
digital appliances– Health/Medical Equipment
• Patient monitoring, MRI, infusion pumps, artificial organs
– Industrial Automation• Supervisory Control and Data
Acquisition (SCADA) systems for chemical and power plants
• Manufacturing systems– Defense
• Source of superiority in all weapon systems
Trend 1: Data/Device Proliferation (By Moore’s Law)
Trend 2: Integration at Scale (Isolation has cost!)
Trend 3: Biological Evolution
Confluence of Trends
CPS DefinitionA CPS is a system in which: information processing and physical processes are so tightly
integrated that it is not possible to identify whether behaviors are the result of computations, physical laws, or both working together
where functionality and salient system characteristics are emerging through the interaction of physical and computational objects
What are Cyber-Physical Systems?Based on Dr. Helen Gill from U.S. NSF: Cyber–computation, communication, and control that are discrete, logical,
and switched Physical–natural and human-made systems governed by the laws of physicsand
operating in continuous time Cyber-Physical Systems–systems in which the cyber and physical systems are tightly
integrated at all scales and levels Change from cyber merely appliquéd on physical Change from physical with COTS
“computing as parts” mindset Change from ad hoc to grounded, assured development
“CPS will transform how we interact with the physical world just like the Internet transformed how we interact with one another.”
What are Cyber-Physical Systems?
Characteristics of Cyber-Physical Systems
Some hallmark characteristics: Cyber capability in every physical component Networked at multiple and extreme scales Complex at multiple temporal and spatial scales Constituent elements are coupled logically and physically Dynamically reorganizing/reconfiguring; “open systems” High degrees of automation, control loops closed at many scales Unconventional computational & physical substrates (such as bio,
nano, chem, …) Operation must be dependable, certified in some cases
More features… Some defining characteristics: • Cyber – physical coupling driven by new demands and applications • Cyber capability in every physical component • Large scale wired and wireless networking • Networked at multiple and extreme scales • Systems of systems • New spatial-temporal constraints • Complex at multiple temporal and spatial scales • Dynamically reorganizing/reconfiguring • Unconventional computational and physical substrates (Bio? Nano?) • Novel interactions between communications/computing/control • High degrees of automation, control loops must close at all scales • Large numbers of non-technical savvy users in the control loop • Ubiquity drives unprecedented security and privacy needs • Operation must be dependable, certified in some cases
Why Cyber-Physical Systems?
• CPS allow us to add capabilities to physical systems
• By merging computing and communication with physical processes, CPS brings many benefits:o • Safer and more efficient systemso • Reduce the cost of building and operating systemso • Build complex systems that provide new capabilities • Technological and Economic Driverso • The decreasing cost of computation, networking, and sensingo • Computers and communication are ubiquitous, enables national oro global scale CPSso • Social and economic forces require more efficient use of nationalo infrastructure.
CPS: Systems at Multiple Scales A BMW is “now actually a network of computers” [R. Achatz, Seimens, The Economist,Oct. 11, 2007]
Credits to Dr. Helen Gill at NSF
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Transformation of Industries: Automotive
Current picture Largely single-vehicle focus Integrating safety and fuel economy (full hybrids,
regenerative braking, adaptive transmission control, stability control)
Safety and convenience “add-ons” (collision avoidance radar, complex airbag systems, GPS, …)
Cost of recalls, liability; growing safety culture Better future?
Multi-vehicle high-capacity cooperative control roadway technologies
Vehicular networks Energy-absorbing “smart materials” for collision
protection (cooperative crush zones?) Alternative fuel technologies, “smart skin” integrated
photovoltaics and energy scavaging, …. Integrated operation of drivetrain, smart tires, active
aerodynamic surfaces, … Safety, security, privacy certification; regulatory
enforcement Time-to-market raceImage thanks to Sushil Birla, GMC
CPS in Multiple Domains
Energy: smart appliances, buildings, power grid Net-zero energy buildings Minimize peak system usage No cascading failures
Healthcare: embedded medical devices and smart prosthetics; operating room of the future; integrated health care delivery Patient records available at every point of care 24/7 monitoring and treatment
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National Health Information Network, Electronic Patient Record initiative Medical records at any point of service Hospital, OR, ICU, …, EMT?
Home care: monitoring and control Pulse oximeters (oxygen saturation), blood glucose
monitors, infusion pumps (insulin), accelerometers (falling, immobility), wearable networks (gait analysis), …
Operating Room of the Future (Goldman) Closed loop monitoring and control; multiple treatment
stations, plug and play devices; robotic microsurgery (remotely guided?)
System coordination challenge Progress in bioinformatics: gene, protein
expression; systems biology; disease dynamics, control mechanisms
Images thanks to Dr. Julian Goldman, Dr. Fred Pearce
Transformation of Industries: Health Care and Medicine
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Current picture: Equipment protection devices trip
locally, reactively Cascading failure: August (US/Canada)
and October (Europe), 2003 Better future?
Real-time cooperative control of protection devices
Or -- self-healing -- (re-)aggregate islands of stable bulk power (protection, market motives)
Ubiquitous green technologies Issue: standard operational control
concerns exhibit wide-area characteristics (bulk power stability and quality, flow control, fault isolation)
Context: market (timing?) behavior, power routing transactions, regulation
IT Layer
Images thanks to William H. Sanders, Bruce Krogh, and Marija Ilic
Transformation of Industries: Electric Power Grid
Smart Buildings
Main Application Domains A new underlying
discipline Abstracting from
sectors to more general principles
Apply these to problems in new sectors
Build a new CPS community
CPS Research Gaps
Interaction and Coordination
Rich time models instead of sequencing
Behavioral invariants instead of end results
Functionality through interactions of ongoing behaviors instead of sequence of actions
Component architectures instead of procedural abstraction
Concurrency models with partially ordered instead of linearly ordered event sets
Precise interaction and coordination protocols
Hugely increased system size with controllable, stable behavior
Dynamic system architectures (nature and extent of interaction can be modified)
Adaptive, autonomic behavior
Self-descriptive, self monitoring system architecture for safety guarantees.
Changes in Cyber Changes in Physical
CPS Challenges
Societal challenge –CPS people can bet their lives on Technical challenge –Systems that interface the cyber and physical,
with predictable behavior
o Where are the boundaries?o What are the limits to abstracting the physical world?o Are complex CPS too unpredictable?o Can we transcend overly conservative design?
It is a new discipline!
Not simply robotics/motion control/vision –rather, design for certifiably dependable control of (complex) systems
Principles for bridging control, real-time systems, safety, security (not just a platform question –rather an interdisciplinary systems science issue)
Next generation system architectures, a recurring question: “What’s in a mode?” (cooperation/coordination? is the safety controller reachable?)
Next generation system ID (bridging machine learning with traditional system ID state estimation, stochasticsand uncertainty, purpose: reactive and predictive control)
Next generation fault tolerance (not just TMR: multicore/many-core, new forms of analytic and synthetic redundancy for FT, addressing interference and interaction, including separation/correlation reasoning)
Next generation real-time systems (coordinated, dynamic multisystem scheduling; property-preserving scheduling; timed networks, precision timing)
FPGAs and other reconfigurables; not just “software” –rather, next generation DA and PLs, system abstractions, software/system co-synthesis
Safe AND Secure, Resilient AND Capable
NSF-Funded Topics
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package org.apache.tomcat.session;
import org.apache.tomcat.core.*;import org.apache.tomcat.util.StringManager;
import java.io.*;import java.net.*;import java.util.*;
import javax.servlet.*;import javax.servlet.http.*;
/** * Core implementation of a server session
* * @author James Duncan Davidson [[email protected]]
* @author James Todd [[email protected]] */
public class ServerSession {
private StringManager sm = StringManager.getManager("org.apache.tomcat.session");
private Hashtable values = new Hashtable(); private Hashtable appSessions = new Hashtable();
private String id; private long creationTime = System.currentTimeMillis();;
private long thisAccessTime = creationTime; private long lastAccessed = creationTime;
private int inactiveInterval = -1;
ServerSession(String id) { this.id = id;
}
public String getId() { return id;
}
public long getCreationTime() { return creationTime;
}
public long getLastAccessedTime() { return lastAccessed;
}
public ApplicationSession getApplicationSession(Context context, boolean create) {
ApplicationSession appSession = (ApplicationSession)appSessions.get(context);
if (appSession == null && create) {
// XXX // sync to ensure valid?
appSession = new ApplicationSession(id, this, context);
appSessions.put(context, appSession); }
// XXX // make sure that we haven't gone over the end of our // inactive interval -- if so, invalidate and create
// a new appSession
return appSession; }
void removeApplicationSession(Context context) { appSessions.remove(context);
}
/** * Called by context when request comes in so that accesses and
* inactivities can be dealt with accordingly. */
void accessed() { // set last accessed to thisAccessTime as it will be left over
// from the previous access
lastAccessed = thisAccessTime; thisAccessTime = System.currentTimeMillis();
}
void validate()
Software Control Systems
Crosses Interdisciplinary Boundaries
Why is CPS Hard?
• Disciplinary boundaries need to be realigned• New fundamentals need to be created• New technologies and tools need to be developed• Education need to be restructured
Heterogeneity and Modeling Languages
ComputingSystemCompositionDomain
PhysicalSystem CompositionDomain
Physicalinstantiation
Logical specification(source code)
Physical systemcharacteristics
• Physical Models• Modeling Languages
– Structure– Behaviors
• Physical Laws– Physical variables– Physical Units
• “Cyber” Models• Modeling Languages
– Structure– Behaviors
• Mathematical Domains– traces/state variables– no reference semantics
or “semantic units”
Modeling ControllerSynthesis
System Analysis
CodeSynthesis
ValidationVerification
TargetAnalysis
Platform
SimulinkStateflowECSL/GMEPtolemy
MatlabSimulatorCheckmateSALTejaUP ReachCharon
R-TWorkshopECSL/GMEKestrelPtolemy
CheckmateCharon
WindViewAIRES
CheckmateAIRES
MPC555/OSEKPENTIUM/QNX
Platform Models
Plant Model Integrated Model
Design Feedback
Valid Model Code/Model
Test Vectors
Valid Code/Model
Design Feedback
Download
Valid Model
BACKPLANE Open Tool Integration Framework
Metamodeling
MetamodelComposition &Validation
Metagenerators
UML/OCLGME/Meta
GME/Meta
MIC/GENKestrel
Comp/PlatfModeling
ComponentImplement.
System Modeling
ComponentIntegration
ValidationVerification
TargetAnalysis Platform
UML/RoseESML/GME
ManualESML/GMEHoneywellCMU
ESML/GMEHoneywellTimeWeaver
AIRESSWRI/ASCTimeWiz
AIRESSWRI/ASCESML/GME
PENTIUM/TAO/BOLD-STROKE
Platform Models
Partial Model System Model
Design Feedback
Component Code
Interaction/Fault mgmt/… Models
Valid Code/Model
Design Feedback
DownloadIntegrated CodeModelComponent Model
Design Feedback
• Integrated Physical/Computational Modeling and Analysis • Generative Programming• Hybrid System Analysis• Customizable (metaprogrammable) modeling tools and generators• Open tool integration framework; configurable design flow and composable design environments
Automotive Design Flow Avionics Design Flow
Goal: Heterogeneous and Composable Design Flows
Change in CPS Applications: Networked Systems
COP
Distributed DatabaseInformation LayerInteroperableexport
WIN-T
UE/HQESO
Standards-BasedOpen Software
Architecture
L COP L COP L COP L COP
Common OperatingPicture
HQESO
EPLRSSINCGARSVHF
Link 4ALink 11Link 16WIN T
Hierarchical Ad-Hoc Network
DataImagesVoiceVideo
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Computing and Networking
Warfighter Interface
Vetronics
Common VehicleSubsystems
HQ
BattleCommand
EO/IR EO/IRSAR/MTI
UGS
WNW
Reachback
HHQ
WNW
Joint CommonDatabase
XX
stubnet
DB Synchronization
Information Management
PlatformNetworked Command
InteroperabilityFIOP
Foundation Infrastr uctur e – (e.g, Network with: COMS EC C rypto Services, Mobility Enhancements, IP Network Appliqué's, )Operating System
Operating System Abst raction Ser vices
Network Infrastructure Services
SOS Framework Ser vicesCOTSND I
SOS Operations ServicesInfor mation Assurance (IA) Network Mgt (NM ) Infor mation Dissemination M gt (IDM)
Applicat io n Program Interfaces – Common Services
Vehicle Ap plicat ions Mission Applicat ions Business App licat ions Administration Applicatio ns
Human Machin e Interface /Mach ine-Machine Interface
COTSNDI
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Foundation Infrastr uctur e – (e.g, Network with: COMS EC C rypto Services, Mobility Enhancements, IP Network Appliqué's, )Operating System
Operating System Abst raction Ser vices
Network Infrastructure Services
SOS Framework Ser vicesCOTSND I
SOS Operations ServicesInfor mation Assurance (IA) Network Mgt (NM ) Infor mation Dissemination M gt (IDM)
SOS Operations ServicesInfor mation Assurance (IA) Network Mgt (NM ) Infor mation Dissemination M gt (IDM)
Applicat io n Program Interfaces – Common Services
Vehicle Ap plicat ions Mission Applicat ions Business App licat ions Administration Applicatio ns
Human Machin e Interface /Mach ine-Machine Interface
COTSNDI
Mis
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Pla
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Pre
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JTRS
Future Systems in the Field• Heterogeneous CPS • Open Dynamic Architecture - heterogeneous networking - heterogeneous components
• Very high level concurrency with complex interactions
• Challenge: understanding system interactions and analyzing (bounding) behavior
CPS – Concept Map