Distributed Control Applications

Within Sensor NetworksBruno 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

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ContentsIntroduction

PEGs (pursuit-evasion game)

Implementation

Methodology

Conclusion

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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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The goal of our research to design robust controllers for distributed systemsevaluation on a distributed control application testbeda 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 featuresgraceful performance degradation

SN can fail

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PEGs

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Distributed PEG (DPEG) scenario issuesTimeCommunicationLocationCooperationPowerSecurity

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Implementation Hardware

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NesC, TinyOS Time

two time management protocols global Network Time Protocol (NTP)-like synchronization protocol local time protocol with the means to transform time readings between i

ndividual 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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Localization top-to-bottom localization framework

Coordinationapplication-specific grouping algorithmsgeneral-purpose grouping services

Power Security

OS level

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Indoorminiature car

remotely controlledSN

remotely controlled a pan-tilt-zoomcamera

to track the caruniform grid of 25motesdetects local magnetic fieldshared positioning information

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Outdoor

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Methodology Scalability and Distributed Control

Natureants searching for food, bacteria foraging, and flight

formations of some birdsschooling in fish & cooperation in insect societies

food search, predator avoidance, colony survival for the species

AIdistributed agentsfree market systemscontinuous control community

process control, distributed systems, jitter compensation, scheduling

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Models of Computation (MOC)Continuous time dynamical systems

stability and reachabilityfor distributed control applications in SNs

not able to capture communication delays, time skew between clocks or discrete de

cision making

discrete time dynamical systemsdoes not directly address sensing and actuation jittercan be taken into account by augmenting with time delay bet

ween the plant and the controllerhybrid automaton

continuous flow and discrete jumps

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discrete event systems work well for mode changes or task scheduling and characterizes hardw

are platform allow for system to be event-triggered not support continuous variables, not correlate time steps of the model w

ith 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 rea

ctive language no relation between time steps of the language and real time

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Design Approachesa hierarchical system representation

assume sensor

reading come with an accurate time stamp

sensors know their location in space

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Low-level controllertime based

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The proposed design methodology (high-level)event based

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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 m

ethodologies in distributed control systems on our proposed DPEG testbed

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