Towards Energy Efficient and Robust Cyber-Physical Systems

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Towards Energy Efficient and Robust
Cyber-Physical Systems

• Sinem Coleri Ergen
• Wireless Networks Laboratory,
• Electrical and Electronics Engineering,
• Koc University

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Cyber-Physical Systems

• System of collaborating computational elements
  controlling physical entities

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Wireless Networked Control Systems

• Sensors, actuators and controllers connect
  through a wireless network

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Wireless Networked Control Systems

• Benefits of wireless
• Ease of installation and maintenance
• Low complexity and cost
• Large flexibility to accommodate modification and
  upgrade of components
• Backed up by several industrial organizations
• International Society of Automation (ISA)
• Highway Addressable Remote Transducer (HART)
• Wireless Industrial Networking Alliance (WINA)

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Trade-off for Communication and Control Systems

• Wireless communication system
• Non-zero packet error probability
• Unreliability of wireless transmissions
• Non-zero delay
• Packet transmission and shared wireless medium
• Sampling and quantization errors
• Signals transmitted via packets
• Limited battery resources
• Control system
• Stringent requirements on timing and reliability
• Smaller packet error probability, delay and
  sampling period
• Better control system performance
• More energy consumed in wireless communication

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Outline

• Optimization of communication system given
  requirements of control system
• Novel design of scheduling algorithms
• Joint optimization of control and communication
  systems
• Novel abstractions for control systems

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Outline

• Optimization of communication system given
  requirements of control system
• Novel design of scheduling algorithms
• Joint optimization of control and communication
  systems
• Novel abstractions for control systems

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Novel Scheduling Algorithm Design

• Packet generation period, transmission delay and
  reliability requirements
• Network Control Systems
• sensor data -gt real-time control of mechanical
  parts
• Fixed determinism better than bounded determinism
  in control systems

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Novel Scheduling Algorithm Design

• Adaptivity requirement
• Nodes should be scheduled as uniformly as possible

EDF
Uniform
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Novel Scheduling Algorithm Design

• Adaptivity requirement
• Nodes should be scheduled as uniformly as possible

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EDF
Uniform
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Novel Scheduling Algorithm Design

• Adaptivity requirement
• Nodes should be scheduled as uniformly as possible

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EDF
Uniform
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Medium Access Control Layer System Model

• given for each link l
• Choose subframe length as for uniform
  allocation
• Assume is an integer Allocate
  every subframes
• Uniform distribution minimize max subframe
  active time

max active time0.9ms
EDF
max active time0.6ms
?
Uniform
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Example Optimization Problem Formulation
Maximum active time of subframes
Periodic packet generation
Delay requirement
Energy requirement
Maximum allowed power by UWB regulations
Transmission time
Transmission rate of UWB for no concurrent
transmission case
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Outline

• Optimization of communication system given
  requirements of control system
• Novel design of scheduling algorithms
• Joint optimization of control and communication
  systems
• Novel abstractions for control systems

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Abstractions of Control System

• Maximum Allowable Transfer Interval (MATI)
  maximum allowed time interval between subsequent
  state vector reports from the sensor nodes to the
  controller
• Maximum Allowable Delay (MAD) maximum allowed
  packet delay for the transmission from the sensor
  node to the controller

Hard real-time guarantee not possible for
wireless -gt Packet error probability gt0 at any
point in time
MAD
MATI
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Abstractions of Control System

• Stochastic MATI keep time interval between
  subsequent state vector reports above MATI with a
  predefined probability to guarantee the stability
  of control systems
• Many control applications and standards already
  use it
• Industrial automation
• IEEE 802.15.4e
• Air transportation systems
• Cooperative vehicular safety
• Never been used in the joint optimization of
  control and communication systems

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Example Optimization Problem Formulation
Total energy consumption
Schedulability constraint
Stochastic MATI constraint
MAD constraint
Maximum transmit power constraint
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Projects at WNL

• Intra-Vehicular Wireless Sensor Networks
• Supported by Marie Curie Reintegration Grant
• Energy Efficient Robust Communication Network
  Design for Wireless Networked Control Systems
• Supported by TUBITAK (The Scientific and
  Technological Research Council of Turkey)
• Energy Efficient Machine-to-Machine
  Communications
• Supported by Turk Telekom
• Cross-layer Epidemic Protocols for
  Inter-vehicular Communication Networks
• Supported by Turk Telekom

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Thank You!

• Sinem Coleri Ergen sergen_at_ku.edu.tr
• Personal webpage http//home.ku.edu.tr/sergen
• Wireless Networks Laboratory http//wnl.ku.edu.tr