Post on 20-Jan-2016
Research Unit for Integrated Sensor Systems
From Synchronized Clocks to Integrable Networks
Sensor Network Research at the Austrian Academy of Sciences
Thilo Sauter
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Status
• Start in April 2004– One of 60 research entities of the Austrian Academy of
Sciences– Funded by Austrian National Bank and the province of Lower
Austria• 28 researchers in an international team
– Austria, Germany, Russia, Pakistan, Italy, Serbia, China• Intensive cooperation with Vienna University of Technology
– Technology support• Part of “Technopol” Wiener Neustadt
– Research institutes and companies working in – Surface technology– Electrochemistry– Tribology– Microsystems
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Integration – Our Mission
• Functional integration– Signal conditioning and processing– Self diagnosis capabilities and adaptability– Sensor fusion
• System integration– Horizontal and vertical communication – Distributed sensor networks– Networked embedded systems
• Circuit integration– Miniaturization– EMC and energy consumption optimization
• Expert integration– Inclusion of all relevant competencies from the beginning on– Co-operation with external partners to complement own
technology and application know-how
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Areas of Expertise
• Basis for integrative, system-oriented solutions• Focus on system design• Open for cooperations
Sen-sors
Circuit Design
Commu-nication
Modelling
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Operative Approach
• Multi-disciplinary combination of traditionally separated know-how areas– Sensor technology– Microelectronics, integrated circuit design– Embedded systems– Algorithm design, software engineering– Network and communication technology
• Basis for integrative, system-oriented solutions• Focus on system design
– “Closed-loop” (active) sensor principles– Robustness– Transducers, controller structures, and networks optimized for
system integration– System modelling and simulation (analytical, numerical)
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Research Focus and Expertise
• Resonant and inertial sensors– Viscosity measurement– Magnetic field measurement
• Miniaturized thermal sensors– Flow measurement– Thermal conductivity measurement
• Capacitive sensors• Smart sensor system architectures
– Modular FPGA-based system-on-chip architectures
– Signal processing for smart sensors
• Clock synchronization in sensor networks
– Hard- and software support
• Security aspects• Vertical integration
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Clock Synchronization … or how to bring real time into real-time networks…
• Goals– Give all distributed nodes in a network a consistent notion of
time– Make synchronization as accurate as possible
• Applications– Distributed measurement systems– Distributed control systems– Reliable data transmission– Secure data transmission– Network access
• Approach– Measurement of network delays– Minimization of jitter– Time stamping of data packets
on lowest possible layer– IEEE 1588 as common standard
Master Slave
Master Time Slave Time
Delay Request
ST1
ST2MT2
Delay Response
ST3MT3
ST4
1
2
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Accuracy
• Hardware-assisted time stamping at MAC level– High-resolution adder-based clock– FPGA-based evaluation platforms for NIC and switch– 10/100/1000 Base-T support– World record: sub-ns synchronization accuracy– Implementation in standard µP: HyNet
Sync. DriverSync. Driver
PTPPTP
PHYPHY
CSCCSC
IPIP
Device DriverDevice Driver
UDPUDP
MACMAC
MIISMIIS
PHYPHY
CSCCSC
Switch FabricSwitch Fabric
MACMAC
MIISMIIS
PHYPHY
MACMAC
otherother
Jitter
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Robustness
• Deficiencies of IEEE 1588– Master is single point of failure– Long switch-over times
• New approach: Master Group– Democratic group of nodes– Fault tolerant– Some nodes with GPS– Backup nodes
• IEEE1588 Slaves– Synchronized standard compliant– Less traffic between Master
Group speaker and slaves (compared to pure democratic approaches)
• Part of new version of standard
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Security
• No security measures considered in IEEE 1588– Typical for automation networks…
• Security introduces jitter• Ressource limited devices• Handling of intermediate nodes
– Switches, transparent clocks– mixed secure and insecure
• Approach– Vulnerability analysis– Definition of parameters– Minimum sync cycles– Limited set of messages– Implementation– First published results
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Master Network Element Slave
(backup-Master)
(active Master)
Malicous (e.g. byzantine) Master
Malicous Traffic Inserter
Information Flow
(1)
(4)(3)
(6)
(2)
(5)
(7)
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Methodology
• Prototyping– Only reasonable for
a few nodes
– Cost intensive
– Nevertheless needed for proof of concept
• Simulation– Large number of
nodes can be investigated
– High-precision clock synchronization requires adequate (very fine grained) simulation models
– Computational expensive
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Position Determination in Wireless Networks
• Project running since May 2007• Goal: find the position of a (unmodified) node in a WLAN
network• Applications: Sensor Localization, Security, new Services
04/21/23 12
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Method for Localization
• Inverse GPS principle– Works with mobile COTS
devices
• Methodology– Delta measurements– Smart Timing Repeaters
are clock synchronized– 3 ns accuracy
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Scalability and QoS in Mixed Wired/Wireless Networks
• FP7 Project FlexWARE – Flexible Wireless Automation in Real-Time Environments
• QoS across network borders– Deterministic behavior– Timing
guarantees
• Scalability– Dynamic growth– Bandwidth
transparency
• Flexible pathsand roaming– Positioning – Interruption free
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Valve Controller
Zone of uncertain connection
Path A
Alternate Path B
Coverage Area A
Coverage Area B Wireless temperature
sensor
J
Co
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Lo
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Production goods on cart
Real Time Backbone Network
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Scalability and QoS in Mixed Wired/Wireless Networks
• Network Management– Reservation of real-time
bandwidth– Access lists– Inter-controller
communication– Prescheduled roaming
• Safety and Security– Deterministic cyclic
exchange due to synchronized timeslots
– Seamless roaming and handover
– Execution time– Context-aware reaction
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Integrable Networks – Why?
• Interconnection with application - Vertical Integration– Different resource capabilities
(energy, execution time,...)– Different notion of “real-time”
(layer-specific, just-in-time)– Interconnecting wired and wireless
domains– Scalable protocols
(network size and platform)
• Challenges– Low resources of sensor devices– Extensibility and scalability– Long-time deployment– (Security) management – Costs – Management and configuration
ADC µC
n=0
n=1
n=8
dt
dKv
Integrated Sensor
)(tn NCO
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Flexible Integration
• Autonomous software agents– Handling of distributed systems (MES)– Agent system design– Definition and implementation of security strategy
• Resource-efficient agent platform for sensor (like) systems
ERP
Order AgentSupervisor
Resource AgentSupervisorInformation
Collector
Ability Broker
Product DataRepository
ERP
MES
Resource
Field control
Resource
Resource Agent
Resource Agent
Order Agent
Order Agent
Order Agent
Order Agent
Communicationvia ACL
ERP
Order AgentSupervisor
Resource AgentSupervisorInformation
Collector
Product DataRepository
ERP
MES
Resource
Field control
Resource
Resource Agent
Order Agent
Order Agent
Order Agent
Order Agent
Communication via Web Services
Communicationvia ACL
Resource Agent
Ability Broker
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Agent Runtime Environment for RFIT
• Scalable solution• FIPA compliant
communication– Advanced message
handling
– Parallel behavior execution
• Highly optimized for resource-limited hardware
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MTS and ACC
FrameworkC-
Agent
FIPA-compliant Agent
TCP-Queue
Behav. 1 Behav. 2 Behav. n...
TCP-Queue
HTTP
TCP-Queue Message
Templates
TCP-Server
Receiver/Decoder
HTTPHTTPHTTP
TCP-Server
HTTP
Sender/Encoder
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Future Challenges
• Scalable communication protocols
– Comprehensive protocol family instead of heterogeneous networks
– Reduced complexity for network integration
• Mixed parallel secure and non-secure systems– Resource optimized security systems
• Overall topic: power awareness– Optimized transducers– Improved data processing architectures and algorithms– Communication interfaces and networks
• New topic for long-term research: bio-inspired approaches for– Sensors– Data processing– Interfaces and networks
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Thank you for your attention
Thilo.Sauter@oeaw.ac.at