Leveraging knowledge for path exposure

Simon Shamoun; Jie Mei; Tarek F. Abdelzaher; Amotz Bar-Noy

doi:10.1109/dcoss.2018.00021

Leveraging knowledge for path exposure

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

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

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 language	English
Title of host publication	Proceedings - 14th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	103-110
Number of pages	8
ISBN (Electronic)	9781538654705
DOIs	https://doi.org/10.1109/dcoss.2018.00021
State	Published - 25 Oct 2018
Externally published	Yes
Event	14th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2018 - Bronx, United States Duration: 18 Jun 2018 → 19 Jun 2018

Publication series

Name	Proceedings - 14th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2018

Conference

Conference	14th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2018
Country/Territory	United States
City	Bronx
Period	18/06/18 → 19/06/18

Bibliographical note

Publisher Copyright:
© 2018 IEEE.

Funding

Research was sponsored by the Army Research Laboratory and was accomplished under Cooperative Agreement Number W911NF-09-2-0053. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Army Research Laboratory or the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation here on.

Funders	Funder number
Army Research Laboratory	W911NF-09-2-0053

Keywords

mobility model
path coverage
path exposure
sensor coverage
sensor selection

Access to Document

10.1109/dcoss.2018.00021

Cite this

Shamoun, S., Mei, J., Abdelzaher, T. F., & 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). Article 8510966 (Proceedings - 14th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/dcoss.2018.00021

Shamoun, Simon ; Mei, Jie ; Abdelzaher, Tarek F. et al. / 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 (Proceedings - 14th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2018).

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title = "Leveraging knowledge for path exposure",

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.",

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Shamoun, S, Mei, J, Abdelzaher, TF & Bar-Noy, A 2018, Leveraging knowledge for path exposure. in Proceedings - 14th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2018., 8510966, Proceedings - 14th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2018, 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, 18/06/18. https://doi.org/10.1109/dcoss.2018.00021

Leveraging knowledge for path exposure. / Shamoun, Simon; Mei, Jie; Abdelzaher, Tarek F. et al.
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 (Proceedings - 14th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2018).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Shamoun S, Mei J, Abdelzaher TF, 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. (Proceedings - 14th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2018). doi: 10.1109/dcoss.2018.00021

Leveraging knowledge for path exposure

Abstract

Publication series

Conference

Bibliographical note

Funding

Keywords

Access to Document

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