1. Bandwidth Allocation in Sense-and-Respond Systems Vincenzo Liberatore Research supported in part by NSF CCR-0329910, Department of Commerce TOP 39-60-04003, NASA NNC04AA12A, and an OhioICE training grant.

2. Sense-And-Respond Computing in the physical world Components Sensors, actuators Sensors, actuators Controllers Controllers Networks Networks

3. Sense-and-Respond Enables Industrial automation [BL04] Industrial automation [BL04] Distributed instrumentation [ACRKNL03] Distributed instrumentation [ACRKNL03] Unmanned vehicles [LNB03] Unmanned vehicles [LNB03] Home robotics [NNL02] Home robotics [NNL02] Distributed virtual environments [LCCK05] Distributed virtual environments [LCCK05] Power distribution [P05] Power distribution [P05] Building structure control [SLT05] Building structure control [SLT05] Merge cyber- and physical- worlds Networked control and tele-epistemology [G01] Networked control and tele-epistemology [G01] Sensor networks Not necessarily wireless or energy constrained Not necessarily wireless or energy constrained One component of sense-actuator networks One component of sense-actuator networks

4. Characteristics Heterogeneous collection of networked sensors, actuators, controllers Heterogeneous collection of networked sensors, actuators, controllers Power Power Often plentiful, sometimes limited Communication Communication Often wired, sometimes low-bandwidth wireless Critical requirements: Critical requirements:SafetyStabilityDependabilityRobustnessQoSScalabilityAdaptability

5. Information Flow Flow Sensor data Sensor data Remote controller Remote controller Control packets Control packets Timely delivery Stability Stability Safety Safety Performance Performance

6. Outline Outline Introduction to Sense-and-Respond Introduction to Sense-and-Respond Bandwidth Allocation Bandwidth Allocation Future of Cyber-Physical Infrastructure Future of Cyber-Physical InfrastructureWarning Most EE-oriented talk I could possibly give Most EE-oriented talk I could possibly give Avoid redundancy with previous talks Avoid redundancy with previous talks

7. Bandwidth Allocation

8. Definition Multiple sense-and-respond flows Multiple sense-and-respond flows Contention for network bandwidth Contention for network bandwidthDesiderata Stability and performance of control systems Stability and performance of control systems Must account for physics Efficiency and fairness Efficiency and fairness Fully distributed, asynchronous, and scalable Fully distributed, asynchronous, and scalable Dynamic and self- reconfigurable Dynamic and self- reconfigurable

9. Control and Networks Control over Networks (Cover N) NCSs, DCSs, SANETs, CPs, … NCSs, DCSs, SANETs, CPs, … Control of Networks (Cof N) Efficient BW allocation Efficient BW allocation Regulate the packet injection rate “Cof N” scheme to better serve “Cover N”

10. Control of Networks A bandwidth allocation scheme Formulate the scheme as a Control problem Control systems regulate sending rate based on congestion signal fed back from the network

11. Sampling Rate and Network Congestion h=1/r l1l1 l2l2

12. Problem Formulation Define a utility fn U(r) that is Monotonically increasing Monotonically increasing Strictly concave Strictly concave Defined for r ≥ r min Defined for r ≥ r min Optimization formulation

13. Distributed Implementation Two independent algorithms End-systems (plants) algorithm End-systems (plants) algorithm Router algorithm (later on) Router algorithm (later on) Plant Controller Router pp p

14. NCS-AQM Control Loop tftf q(t) f(q(t)) q`=Σr(t) - C p(t) tbtb PlantQueue Model Plant P(s) =Model Plant P(s) = Controller G(s)

15. Queue Controller G(s) Proportional (P) Controller G P (s) = k p G P (s) = k p Proportional-Integral (PI) Controller G PI (s) = k p + k i /s G PI (s) = k p + k i /s q(s) G(s) P(s) q0q0 + _ eu

16. Determination of k p and k i Stability region in the k i –k p plane Stabilizes the NCS-AQM closed-loop system for delays less or equal d Stabilizes the NCS-AQM closed-loop system for delays less or equal d Analysis of quasi-polynomials, f(s,e s )

17. Simulations & Results 50 Plants: [Branicky et al. 2002] [Zhang et al. 2001]

18. Simulations & Results (cont.) PI ¤ P¤P¤

19. Related Work Congestion Control Primarily addresses elastic flows Primarily addresses elastic flows Active Queue Management (AQM) Active Queue Management (AQM) Utility maximization and controllers often viewed as alternative approaches Utility maximization and controllers often viewed as alternative approaches Multi-media congestion control E.g., Equation-based E.g., Equation-based Smooth rate variation Smooth rate variation No physically relevant utility No physically relevant utilityTime-scales Approach to define time-varying utility functions Approach to define time-varying utility functions “C of N” missing “C of N” missing

20. Outline Outline Introduction to Sense-and-Respond Introduction to Sense-and-Respond Bandwidth Allocation Bandwidth Allocation Future of Cyber-Physical Infrastructure Future of Cyber-Physical InfrastructureWarning Most EE-oriented talk I could possibly give Most EE-oriented talk I could possibly give Avoid redundancy with previous talks Avoid redundancy with previous talks

21. Cyber-Physical Systems Foundations and technologies for rapid and reliable development and integration of computer- centric physical and engineered systems “Globally virtual, locally physical” Major NSF initiative planned

22. Needs and Directions New Calculus New Calculus Merge time- and event-based systems New Tools New Tools E.g., co-simulation for co-design New Networks methods New Networks methods Bandwidth allocation, play-back buffers New Education New Education Multi-disciplinary education Telltale sign: New Metrics Network-oriented metrics Network-oriented metrics Delay, jitter, loss rates, bandwidth Impacts physics, but different from physics behavior Control-Theoretical metrics Control-Theoretical metrics Overshoot, rise time, settling time, etc. Hard to relate to network conditions Multi-disciplinary metrics Multi-disciplinary metrics E.g., plant tracking in terms of network bandwidth allocation An E-Model for cyber-physical systems?

23. Example PI ¤ P¤P¤

24. Metrics (not sure) Stability (and safety) Objective Objective Remote controller makes unstable system stable Extensive research Extensive research [Z01] and references therein Problem Problem Errors, network partitions, failures make stability impossible Tracking Objective Objective The S&R system should do what it is supposed to In spite of network non- determinism (failures, security, etc.) Problem Problem Benchmarks (NIST?) Disturbance cancellation Objective The S&R system should do what it is supposed to do In spite of network non- determinism and uncertainty in the environment Way out Use simple tasks Scalability [L04] Number of nodes Space networks? “Geographic” Administrative FunctionalConclusion RT S&R benchmarks needed!

25. Acknowledgments Students Ahmad al-Hammouri Ahmad al-Hammouri David Rosas David Rosas Zakaria Al-Qudah Zakaria Al-Qudah Huthaifa Al-Omari Huthaifa Al-Omari Nathan Wedge Nathan Wedge Qingbo Cai Qingbo Cai Prayas Arora Prayas AroraColleagues Michael S. Branicky Michael S. Branicky Wyatt S. Newman Wyatt S. Newman

26. Conclusions Sense-and-Respond Merge cyber-world and physical world Merge cyber-world and physical world Critically depends on physical time Critically depends on physical time Bandwidth Allocation Control of Networks to aid Control over Networks Control of Networks to aid Control over Networks Complete characterization of the stability region Complete characterization of the stability region Evaluation Evaluation Peak detection Peak detection Cyber-physical systems http://home.case.edu/~vxl11/NetBots/