1. Distributed Control Applications Within Sensor Networks
Bruno Sinopoli, Sourtney Sharp, Luca Schenato, Shawn Schaffery, S. Shankar Sastry
Robotics and Intelligent Machines Laboratory / UC Berkeley
Proceedings of the IEEE, VOL. 91, No.8, August 2003
Seo, Dongmahn

2. Contents Introduction PEGs (pursuit-evasion game) Implementation
Methodology
Conclusion
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3. Introduction Embedded computers Sensor Networks
Crossbow, Millennial, Sensoria, Smart Dust
various fields of research
extensive experimentation of structural response to earthquakes
habitat monitoring
intelligent transportation systems
home and building automation
military applications
research community
time services, localization services, routing services, tracking services
system design and implementations
longevity, self configuration, self upgrade, adaptation to changing environmental conditions
control applications
location determination, time synchronization, reliable communication, power consumption management, cooperation and coordination, and security
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4. The goal of our research
to design robust controllers for distributed systems
evaluation on a distributed control application testbed
a pursuit-evasion game (PEG) application
research problems
tracking, control design, security, robustness
multiple-vehicle tracking
distinguish pursuers from evaders
dynamic routing structure
to deliver information to pursuers in minimal time
security features
graceful performance degradation
SN can fail
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5. PEGs
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7. Distributed PEG (DPEG) scenario issues
Time
Communication
Location
Cooperation
Power
Security
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8. Implementation
Hardware
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13. NesC, TinyOS Time Communication two time management protocols
global Network Time Protocol (NTP)-like synchronization protocol
local time protocol with the means to transform time readings between individual motes
Communication
propose a general routing framework
that supports a number of routing methodologies
routing to geographic regions
routing based on geographic direction
routing to symbolic network identifiers
for dynamically routing to physically moving destinations within the network
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14. Localization Coordination Power Security
top-to-bottom localization framework
Coordination
application-specific grouping algorithms
general-purpose grouping services
Power
Security
OS level
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17. Indoor miniature car SN remotely controlled
remotely controlled a pan-tilt-zoom camera
to track the car
uniform grid of 25motes
detects local magnetic field
shared positioning information
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18. Outdoor
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19. Methodology Scalability and Distributed Control Nature AI
ants searching for food, bacteria foraging, and flight formations of some birds
schooling in fish & cooperation in insect societies
food search, predator avoidance, colony survival for the species AI
distributed agents
free market systems
continuous control community
process control, distributed systems, jitter compensation, scheduling
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20. Models of Computation (MOC)
Continuous time dynamical systems
stability and reachability
for distributed control applications in SNs
not able to capture
communication delays, time skew between clocks or discrete decision making
discrete time dynamical systems
does not directly address sensing and actuation jitter
can be taken into account by augmenting with time delay between the plant and the controller
hybrid automaton
continuous flow and discrete jumps
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21. discrete event systems
work well for mode changes or task scheduling and characterizes hardware platform
allow for system to be event-triggered
not support continuous variables, not correlate time steps of the model with real time
dataflow MOCs
useful for characterizing several communicating processes
awkward for control
synchronous reactive languages
support a broad range of formal verification tools to aid in debugging
possible to generate code for platform directly from the synchronous reactive language
no relation between time steps of the language and real time
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22. Design Approaches a hierarchical system representation assume
sensor reading come with an accurate time stamp
sensors know their location in space
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23. Low-level controller
time based
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24. The proposed design methodology (high-level)
event based
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25. Conclusion overview of research activities
dealing with distributed control in SNs
SNs and related research issues
hardware and software platforms
SNs for distributed control applications
suggested a general approach to control design
using a hierarchical model composed of
continuous time-triggered components at the low level
discrete event-triggered components at the high level
future work
will focus on implementation, verification, and testing of our methodologies in distributed control systems on our proposed DPEG testbed
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26. Thank you!
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