Resilient Sensor Placement for Fault Localization in Water Distribution Networks
Lina Sela Perelman, Waseem Abbas, Saurabh Amin, Xenofon Koutsoukos

Citation
Lina Sela Perelman, Waseem Abbas, Saurabh Amin, Xenofon Koutsoukos. "Resilient Sensor Placement for Fault Localization in Water Distribution Networks". 8th ACM/IEEE International Conference on Cyber-Physical Systems (ICCPS 2017), April, 2017.

Abstract
In this paper, we study the sensor placement problem in urban water networks that maximizes the localization of pipe failures given that some sensors give incorrect outputs. False output of a sensor might be the result of degradation in sensor's hardware, software fault, or might be due to a cyber attack on the sensor. Incorrect outputs from such sensors can have any possible values which could lead to an inaccurate localization of a failure event. We formulate the optimal sensor placement problem with erroneous sensors as a set multicover problem, which is NP-hard, and then discuss a polynomial time heuristic to obtain efficient solutions. In this direction, we first examine the physical model of the disturbance propagating in the network as a result of a failure event, and outline the multi-level sensing model that captures several event features. Second, using a combinatorial approach, we solve the problem of sensor placement that maximizes the localization of pipe failures by selecting $m$ sensors out of which at most $e$ give incorrect outputs. We propose various localization performance metrics, and numerically evaluate our approach on a benchmark and a real water distribution network. Finally, using computational experiments, we study relationships between design parameters such as the total number of sensors, the number of sensors with errors, and extracted signal features.

Electronic downloads

(No downloads are available for this publication.)

Citation formats

• HTML

  Lina Sela Perelman, Waseem Abbas, Saurabh Amin, Xenofon
  Koutsoukos. <a
  href="http://www.cps-forces.org/pubs/240.html"
  >Resilient Sensor Placement for Fault Localization in
  Water Distribution Networks</a>, 8th ACM/IEEE
  International Conference on Cyber-Physical Systems (ICCPS
  2017), April, 2017.

• Plain text

  Lina Sela Perelman, Waseem Abbas, Saurabh Amin, Xenofon
  Koutsoukos. "Resilient Sensor Placement for Fault
  Localization in Water Distribution Networks". 8th
  ACM/IEEE International Conference on Cyber-Physical Systems
  (ICCPS 2017), April, 2017.

• BibTeX

  @inproceedings{PerelmanAbbasAminKoutsoukos17_ResilientSensorPlacementForFaultLocalizationInWaterDistribution,
      author = {Lina Sela Perelman and Waseem Abbas and Saurabh
                Amin and Xenofon Koutsoukos},
      title = {Resilient Sensor Placement for Fault Localization
                in Water Distribution Networks},
      booktitle = {8th ACM/IEEE International Conference on
                Cyber-Physical Systems (ICCPS 2017)},
      month = {April},
      year = {2017},
      abstract = {In this paper, we study the sensor placement
                problem in urban water networks that maximizes the
                localization of pipe failures given that some
                sensors give incorrect outputs. False output of a
                sensor might be the result of degradation in
                sensor's hardware, software fault, or might be due
                to a cyber attack on the sensor. Incorrect outputs
                from such sensors can have any possible values
                which could lead to an inaccurate localization of
                a failure event. We formulate the optimal sensor
                placement problem with erroneous sensors as a set
                multicover problem, which is NP-hard, and then
                discuss a polynomial time heuristic to obtain
                efficient solutions. In this direction, we first
                examine the physical model of the disturbance
                propagating in the network as a result of a
                failure event, and outline the multi-level sensing
                model that captures several event features.
                Second, using a combinatorial approach, we solve
                the problem of sensor placement that maximizes the
                localization of pipe failures by selecting $m$
                sensors out of which at most $e$ give incorrect
                outputs. We propose various localization
                performance metrics, and numerically evaluate our
                approach on a benchmark and a real water
                distribution network. Finally, using computational
                experiments, we study relationships between design
                parameters such as the total number of sensors,
                the number of sensors with errors, and extracted
                signal features.},
      URL = {http://cps-forces.org/pubs/240.html}
  }
  

Posted by Waseem Abbas on 2 Mar 2017.
Groups: forces
For additional information, see the Publications FAQ or contact webmaster at cps-forces org.