Bandwidth Allocation in Sense-and-Respond Systems

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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.
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Sense-And-Respond

• Computing in the physical world
• Components
• Sensors, actuators
• Controllers
• Networks

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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

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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

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Information Flow

• Flow
• Sensor data
• Remote controller
• Control packets
• Timely delivery
• Stability
• Safety
• Performance

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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

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Bandwidth Allocation
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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

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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
  

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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

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Sampling Rate and Network Congestion
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Problem Formulation

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

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Distributed Implementation

• Two independent algorithms
• End-systems (plants) algorithm
• Router algorithm (later on)

Plant
Router
Controller
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NCS-AQM Control Loop
Plant
Queue
f(q(t))
qSr(t) - C
p(t)
q(t)
tf
tb
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Queue Controller G(s)

• Proportional (P) Controller
• GP(s) kp
• Proportional-Integral (PI) Controller
• GPI(s) kp ki/s

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Determination of kp and ki

• Stability region in the kikp plane
• Stabilizes the NCS-AQM closed-loop system for
  delays less or equal d
• Analysis of quasi-polynomials, f(s,es)

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Simulations Results
Branicky et al. 2002
Zhang et al. 2001
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Simulations Results (cont.)
PI
P
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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

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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

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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

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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?

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Example
PI
P
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Metrics (not sure)

• Stability (and safety)
• Objective
• Remote controller makes unstable system stable
• Extensive research
• Z01 and references therein
• Problem
• Errors, network partitions, failures make
  stability impossible
• Tracking
• Objective
• The SR system should do what it is supposed to
• In spite of network non-determinism (failures,
  security, etc.)
• Problem
• Benchmarks (NIST?)

• Disturbance cancellation
• Objective
• The SR 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
• Functional
• Conclusion
• RT SR benchmarks needed!

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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

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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

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