Wireless Sensor and Actuator Networks WSANs research at TKK

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Wireless Sensor and Act(uat)or Networks (WSANs)-
research at TKK

• Riku Jäntti, riku.jantti_at_tkk.fi

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Wireless automation today

• Embedded systems where the different devices
  (sensors, controllers and actuators) communicate
  seamlessly using wireless technology
• Connection of field devices through a field bus
  requires a lot of network planning, wiring and
  troubleshooting as a result, for many automation
  systems the cost is all in the wires.

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Wireless automation today

• Wireless cable replacement systems
• In cable replacement systems, the objective has
  been to minimize the amount of changes needed in
  the existing hardware and software (protocols).
• Point-to-point links
• Master-slave-polling star topology configuration

C. Koumpis, L. Hanna, M. Andersson and M.
Johansson. "Wireless industrial control and
monitoring beyond cable replacement," Profibus
International Conference, June 2005
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Challenges

• Quality of service
• Real-time operation, delay bounds
• Robustness and reliability
• Interference
• Co-channel wireless links interfere with each
  other
• Co-existence of different networks
• Flexibility
• Limitation is network topology
• Configuration of wireless systems can require
  manual intervention
• On-demand growth of network is not supported

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Wireless automation development

• Quality of service
• New MAC solutions
• Synchronization
• Robustness and reliability
• Node redundancy
• Multi-path routing
• Multi-radio systems
• Interference
• Dynamic spectrum management
• Situation awareness
• Location information
• Timing
• Diagnostics

• Flexibility
• Self-configuration and self-optimization
• On-demand growth via wireless mesh networking
• Limitation is network topology
• Security

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Multi-disciplinary research
Control Automation

• (Wireless)
• Communications

Computer Science Software Engineering
WSANs
Electronics Embedded systems
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On-going research activity

• Wireless Sensor and Actuator Networks for
  Measurement and control (WISA)
• Department of Computer Science, University of
  Vaasa
• Communications Laboratory, Helsinki University of
  Technology (TKK)
• Control Engineering Laboratory, Helsinki
  University of Technology (TKK)
• Radio Communication Systems Group, Royal
  Institute of Technology (KTH), Sweden
• Automatic Control Group, Royal Institute of
  Technology (KTH), Sweden

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WISA

Quality of service
Increase robustness Decrease jitter
Requirement for control
Data fusion PID Controller tuning New control
algorithms
Increase jitter margin and tolerance to errors
Wireless automation systems
Coexistence protocols Multi-path routing
(mesh) Synchronization
Performance of Wireless networks
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WISA

• WP1 MAC-layer (scheduling)
• Coexistence of WiFi and IEEE802.15.4
• WiFi is an efficient jammer for IEEE802.15.4
  networks
• Spectrum monitoring Detect strong interference
• Interference avoidance via dynamic channel
  assignment Transmitter and receiver start
  hopping sequence in order to find free channel

Strong interference signal
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3

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WISA

• WP1 MAC-layer (scheduling)
• Optimization of random access based on traffic
  profiles
• Periodic measurements
• Virtual time division
• Correlated events
• Optimization of backoff window size in CSMA

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WISA

• WP2 Network layer
• Hierarchical routing
• Cluster heads control the traffic inside their
  radio range.
• Methods for the inter-cluster communications that
  guarantee end-to-end quality of service.
• Synchronization
• Avoid unnecessary collisions
• Save energy by using sleep mode
• Common time reference (synchronization of data)
• Reliability
• Multipath routing with robustness and delay
  constraints set by the control application.
• Auto-configuration
• Allocate network addresses
• In hierarchical systems only cluster heads
  require global addresses

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Hierarchical routing

• Network overheads usually take significant amount
  of energy, especially when the network size
  grows.
• Flat ad hoc routing protocols are not applicable
  in large-scale networks.
• Dividing the whole network into clusters will
  results in much less overhead transmission/recepti
  on.
• Most ad hoc networks are heterogeneous, i.e.,
  nodes have different capacities such as radio
  range and battery size.
• Hierarchical network
• Reduce the required network layer overhead
• Supports synchronization and efficient energy
  management

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Clustering Algorithm

• Each CH (Cluster Head) has a predetermined
  Cluster ID (CID) and a Slave Table (ST). The CID
  will be broadcast and shared by all its slaves.
• A CH periodically broadcasts Clustering Beacons
  (BEAC) with full transmit power. The period to
  broadcast is can be either fixed or variable.
• A LN should be always a slave of one and only one
  CH. If the radio range of a LN cannot reach a CH,
  either
• the LN increases its transmit power, or
• the LN uses multi-hop route to reach a CH,
  especially when the CH population is small.
• Cluster Forming When an LN is powered on, it sets
  itself as cluster-less. Upon the receive of the
  first BEAC, the LN marks itself as a slave of the
  corresponding CH and sends a Beacon Reply (BREP)
  back. The CH will add it as slave. The SL also
  records the SNR of the received BEAC. The SNR at
  here represents the link state.
• Cluster Updating If a SL received a new BEAC, it
  will compare the SNR of new one with the cached
  one. If the new one is better, it will update its
  CH by sending two packets a BREP to inform the
  new CH, and a CH Cancel (CCAN) to inform the old
  CH to remove it from the ST.

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Cluster Forming Example
Wide-band, high power
Narrow-band, low power

• Cluster head can be
• Chosen dynamically
• Signal strength
• Energy
• Computational resources

Mesh network between cluster heads
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Eaodv vs. Ecluster at differrent ?
? beacon rate / rerouting rate
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Synchronization

• Flooding of synchronization messages
• Offers a precision in one millisecond under
  current hardware achievement.

Probability that network is synchronized
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Multi-path routing

• Multi-path routing can be utilized to
• Increase throughput
• Balance load and reduce jitter
• Robustness against link breaks and jamming

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Load Balanced AODV

Motivation Minimize the number of bottleneck
nodes that would carry traffic of multiple flows
in order to decrease delay and jitter Solution W
e use three parameters that are available in
AODV the size of routing table L, the expiration
time of each route entry in the table and the
number of neighbours of each node, we use this
cost function to delay the re broadcast of the
routing packets
Scenario Route ACDE is better than ABE
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Load balanced AODV
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Multi-path routing

• AOMDV
• Set up node disjoint routes
• Route is selected by the source node
• LMNR (Localized Multiple next hop routing)
• Set up multiple routes
• Next hop is locally decided based on load,
  interference, and link availability
• gt Increase robustness against link faults
  (decrease the need for rerouting in case of
  failures)

AODV
AOMDV
LMNR
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WISA

• WP3 Data fusion and diagnostics
• Distributed data fusion methods
• Sub-optimal methods
• Hierarchical methods clustering
• Sensor diagnostics
• Detection of faulty sensors
• Methods for compensation of erroneous
  measurements

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Filtering and Estimation of Varying Delay

• Apply Kalman filter to estimate process state
  with varying delayed measurements
• Measurement delay is unknown and varying
• need to be estimated at every timestep
• Estimate based on delay distribution/Markov-chain
  delay model
• Maximise

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Filtering and Estimation of Varying Delay

• Delay estimation performance depends on
  measurement noise
• Filtering with delay estimation
• Better than assuming constant mean delay
• Almost as good as with known delay

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WISA

• WP4 Control
• PID control
• Controller tuning
• Robustness analysis of controllers with respect
  to time varying delays
• A coordination scheme based on distributed MPC
  method
• A iterative coordination scheme for Internal
  Model Control based loops

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Jitter-aware PID tuning

• Optimal tuning of the PID controller studied via
  simulations
• Multiobjective optimization performance, jitter
  margin and robustness maximized simultaneously
• Developed new tuning rules for varying time-delay
  systems
• Comparisons to AMIGO tuning

L. Eriksson, M. Johansson. PID controller tuning
rules for varying time-delay systems, Accepted
for publication in American Control Conference
2007, New York, USA, 11 - 13 July, 2007.
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Model predictive coordination of sensor and
actuator networks

• 6 6 sensors in two clusters measuring a 2x2
  MIMO process
• 2 data fusion (Kalman filter) and PID control
  nodes
• MPC coordinator to compensate the cross-couplings
• Network simulated with ns2-simulator -gt delay
  traces

L. Eriksson, M. Pohjola, S. Nethi. Coordination
scheme for wireless networked control systems,
unpublished manuscript.
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WISA

• WP5 Testbed
• MoCoNet Testbed for real-time control of
  networked systems.
• Allows network emulation with NS2
• Easy to test the impact of new protocols
• Allows testing of large scale networks
• Distributed multi-site operation over the
  internet
• Control of real laboratory scale processes is
  possible
• Real implementation of communication protocols
  and controllers

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Testbed I

• Network simulated with ns-2
• More realistic network simulation than previously
• Different wired/wireless, traffic and topology
  scenarios can be tested
• Under development
• Integration with MoCoNet
• GUI for specifying the network

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Testbed II

• Implementation of wireless sensor network based
  measurement system for the trolley crane
• Calculation of the load angle based on ultrasound
  and radio
• Centralized control
• Comparison to wired system

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Publications

• Energy efficiency
• R. Jäntti and S.-L. Kim "Joint data rate and
  power allocation for lifetime maximization in
  interference limited ad hoc networks," To appear
  in IEEE Transactions on Wireless Communications,
  2005.
• M. Chowdhury and R. Jäntti, "Dependency of
  battery life and transmission power in wireless
  adhoc networks," To appear in ICECE2004,
  Bangladesh, 2004
• C. Gao and R. Jäntti, "Energy Capacity in
  Wireless Sensor Networks, " to apprar in Proc.
  5th international conference on Intelligent
  Transportation Systems (ITS) Telecommunications,
  2005.
• C. M. M. Rahman and Riku Jäntti, "On the Impact
  of Signaling on Lifetime of Wireless Ad Hoc
  Network," in Proc. ICNEWS06, Dhaka, Bangladesh,
  January 2006.

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Publications

• Routing
• R. Jäntti and S.-L. Kim, Energy-Efficient
  Routing in DSSS Ad Hoc Networks under Mean Rate
  Constraints in Proc. IEEE VTC2003 Spring, 2003.
• R. Jäntti and S.-L. Kim, "Joint data rate and
  power allocation in interference limited ad hoc
  networks," in Proc. SCI 2004, 2004.
• C. Gao and R. Jäntti, "Least-Hop Routing Analysis
  of On-Demand Routing Protocols" In Proc. IEEE
  ISWCS 2004, 2004.
• C. Gao and R. Jäntti, "A Reactive Power-Aware
  on-Demand Routing Protocols for Wireless Ad Hoc
  Networks," in Proc. IEEE VTC 2004 Spring, 2004.
• C. Gao and R. Jäntti, "Power-Aware Routing to
  Cope with Communication Gray Zones in Ad hoc
  Networks" in Proc. 5th international conference
  on Intelligent Transportation Systems (ITS)
  Telecommunications, 2005.

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Publications

• Flow control
• A. Penttinen, J. Virtamo and R. Jäntti,
  "Performance analysis of multi-hop radio networks
  with balanced fair resource sharing,"
  Telecommunication systems, Vol. 31, No. 4, April
  2006.
• Self-configuration
• C. Gao and R. Jäntti, "On Clustered Ad hoc
  Networks Link-State Clustering Algorithm and
  Energy Performance Study," to appear in Proc.
  INTERNATIONAL WORKSHOP ON CONVERGENT TECHNOLOGIES
  (IWCT) 2005, Oulu, Finland, 2005.
• C. Gao and R. Jäntti, "A Global Synchronization
  Scheme for Clustered Wireless Ad-hoc/Sensor
  Networks," in Proc. IEEE ITST2006 , Chengdu,
  China, June 2006.
• C. Gao and R. Jäntti, "Link-State Clustering
  Based on IEEE 802.15.4 MAC for Wireless
  Adhoc/Sensor Networks," n Proc. IEEE WCNC, Las
  Vegas, USA, April 2006.

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Questions?