Leveraging knowledge for path exposure

Simon Shamoun, Jie Mei, Tarek Abdelzaher, Amotz Bar-Noy

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We study how knowledge of a moving object's path can be used to select sensors in a network that maximize the coverage of its path. We propose a mobility model that combines the shortest path between two points with random movement. Given the mobility model, we have different knowledge levels in terms of knowing nothing, the start, destination, movement model, and the whole path. We present a framework to assign weights to points on the movement grid based on the knowledge level and to greedily select sensors to maximize weighted coverage of the grid. We show in simulations of random movement that knowing more information generally has better performance, but for certain levels of knowledge, this decreases as the randomness increases. We also find that it is possible to obtain the maximum coverage by assuming the target follows the shortest path when the randomness is below a certain threshold. We verified these results on real human mobility traces.

Original languageEnglish (US)
Title of host publicationProceedings - 14th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages103-110
Number of pages8
ISBN (Electronic)9781538654705
DOIs
StatePublished - Oct 25 2018
Event14th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2018 - Bronx, United States
Duration: Jun 18 2018Jun 19 2018

Other

Other14th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2018
CountryUnited States
CityBronx
Period6/18/186/19/18

Fingerprint

Sensors
Sensor
Knowledge level
Shortest path
Grid
Randomness
Simulation
Destination

Keywords

  • mobility model
  • path coverage
  • path exposure
  • sensor coverage
  • sensor selection

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems and Management

Cite this

Shamoun, S., Mei, J., Abdelzaher, T., & Bar-Noy, A. (2018). Leveraging knowledge for path exposure. In Proceedings - 14th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2018 (pp. 103-110). [8510966] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/DCOSS.2018.00021

Leveraging knowledge for path exposure. / Shamoun, Simon; Mei, Jie; Abdelzaher, Tarek; Bar-Noy, Amotz.

Proceedings - 14th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 103-110 8510966.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Shamoun, S, Mei, J, Abdelzaher, T & Bar-Noy, A 2018, Leveraging knowledge for path exposure. in Proceedings - 14th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2018., 8510966, Institute of Electrical and Electronics Engineers Inc., pp. 103-110, 14th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2018, Bronx, United States, 6/18/18. https://doi.org/10.1109/DCOSS.2018.00021
Shamoun S, Mei J, Abdelzaher T, Bar-Noy A. Leveraging knowledge for path exposure. In Proceedings - 14th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 103-110. 8510966 https://doi.org/10.1109/DCOSS.2018.00021
Shamoun, Simon ; Mei, Jie ; Abdelzaher, Tarek ; Bar-Noy, Amotz. / Leveraging knowledge for path exposure. Proceedings - 14th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2018. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 103-110
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