1. Week 1 Lectures 1 Introduction to CPS Instructor: Prof. Fei Hu, ECE, Univ of Alabama

2. Computing Evolution

3. 3 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 (21 st 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

4. Trend 1: Data/Device Proliferation (By Moore’s Law)

5. Trend 2: Integration at Scale (Isolation has cost!)

6. Trend 3: Biological Evolution

7. Confluence of Trends

8. CPS Definition A 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

9. 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.”

10. What are Cyber-Physical Systems?

11. 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

12. 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

13. 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 systems o Reduce the cost of building and operating systems o Build complex systems that provide new capabilities  Technological and Economic Drivers o The decreasing cost of computation, networking, and sensing o Computers and communication are ubiquitous, enables national or o global scale CPSs o Social and economic forces require more efficient use of national o infrastructure.

14. 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

15. 15 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 race Image thanks to Sushil Birla, GMC

16. 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

17. 17  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

18. 18  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

19. Smart Buildings

20. 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

21. CPS Research Gaps

22. 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

23. 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?

24. 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

25. NSF-Funded Topics

29. 29 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 [duncan@eng.sun.com] * @author James Todd [gonzo@eng.sun.com] */ 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() SoftwareControl 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

30. Heterogeneity and Modeling Languages Computing System Composition Domain Physical System Composition Domain Physical instantiation Logical specification (source code) Physical system characteristics 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”

31. Modeling Controller Synthesis System Analysis Code Synthesis Validation Verification Target Analysis Platform Simulink Stateflow ECSL/GME Ptolemy Matlab Simulator Checkmate SAL Teja UP Reach Charon R-T Workshop ECSL/GME Kestrel Ptolemy Checkmate Charon WindView AIRES Checkmate AIRES MPC555/ OSEK PENTIUM/ 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 Metamodel Composition & Validation Metagenerators UML/OCL GME/Meta MIC/GEN Kestrel Comp/Platf Modeling Component Implement. System Modeling Component Integration Validation Verification Target Analysis Platform UML/Rose ESML/GME Manual ESML/GME Honeywell CMU ESML/GME Honeywell TimeWeaver AIRES SWRI/ASC TimeWiz AIRES SWRI/ASC ESML/GME PENTIUM/ TAO/ BOLD- STROKE Platform Models Partial Model System Model Design Feedback Component Code Interaction/Fault mgmt/… Models Valid Code/Model Design Feedback Download Integrated Code Model Component 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

32. Change in CPS Applications: Networked Systems COP Distributed Database Information Layer Interoperable export WIN-T UE/HQ ESO Standards-Based Open Software Architecture L COP Common Operating Picture HQ ESO EPLRS SINCGARS VHF Link 4A Link 11 Link 16 WIN T Hierarchical Ad-Hoc Network Data Images Voice Video Mission Planning & Prep Situation Understanding Battle Mgmt & Execution Sensor Fusion Target Recognition Integrated Sustainment Embedded Training Common Services Information Management Computing and Networking Warfighter Interface Vetronics Common Vehicle Subsystems HQ Battle Command EO/IR SAR/MTI UGS WNW Reachback HHQ WNW Joint Common Database XX stubnet DB Synchronization Information Management Platform Networked Command Interoperability FIOP 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

33. CPS – Concept Map