Bandwidth Allocation in Sense-and-Respond Systems

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 • Controllers • Networks

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

4. Characteristics • Heterogeneous collection of networked sensors, actuators, controllers • Power • Often plentiful, sometimes limited • Communication • Often wired, sometimes low-bandwidth wireless • Critical requirements: • Safety • Stability • Dependability • Robustness • QoS • Scalability • Adaptability

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

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

7. Bandwidth Allocation

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

9. Control and Networks • Control over Networks (Cover N) • NCSs, DCSs, SANETs, CPs, … • Control of Networks (Cof N) • 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. h=1/r l2 l1 Sampling Rate and Network Congestion

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

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

14. Model Plant P(s) = Queue ControllerG(s) NCS-AQM Control Loop Plant Queue f(q(t)) q`=Σr(t) - C p(t) q(t) tf tb

15. q0 q(s) e u G(s) P(s) _ + Queue Controller G(s) • Proportional (P) Controller • GP(s) = kp • Proportional-Integral (PI) Controller • GPI(s) = kp+ ki/s

16. Determination of kpand ki • Stability region in the ki–kp plane • Stabilizes the NCS-AQM closed-loop system for delays less or equal d • Analysis of quasi-polynomials, f(s,es)

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

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

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

20. Outline • Outline • Introduction to Sense-and-Respond • Bandwidth Allocation • Future of Cyber-Physical Infrastructure • Warning • Most EE-oriented talk I could possibly give • 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 • Needs and Directions • New Calculus • Merge time- and event-based systems • New Tools • E.g., co-simulation for co-design • New Networks methods • Bandwidth allocation, play-back buffers • New Education • Multi-disciplinary education • Telltale sign: New Metrics • Network-oriented metrics • Delay, jitter, loss rates, bandwidth • Impacts physics, but different from physics behavior • Control-Theoretical metrics • Overshoot, rise time, settling time, etc. • Hard to relate to network conditions • Multi-disciplinary metrics • E.g., plant tracking in terms of network bandwidth allocation • An E-Model for cyber-physical systems?

23. Example PI ¤ P ¤

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

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