The price of incorrectly aggregating coverage values in sensor selection

Amotz Bar-Noy; Matthew P. Johnson; Nooreddin Naghibolhosseini; Dror Rawitz; Simon Shamoun

doi:10.1109/DCOSS.2015.24

The price of incorrectly aggregating coverage values in sensor selection

Amotz Bar-Noy, Matthew P. Johnson, Nooreddin Naghibolhosseini, Dror Rawitz, Simon Shamoun

Bar-Ilan University - The Alexander Kofkin Faculty of Engineering

City University of New York

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

7 Scopus citations

Abstract

An important problem in the study of sensor networks is how to select a set of sensors that maximizes coverage of other sensors. Given pair wise coverage values, three commonly found functions give some estimate of the aggregate coverage possible by a set of sensors: maximum coverage by any selected sensor (MAX), total coverage by all selected sensors (SUM), and the probability of correct prediction by at least one sensor (PROB). MAX and SUM are two extremes of possible coverage, while PROB, based on an independence assumption, is in the middle. This paper addresses the following question: what guarantees can be made of coverage that is evaluated by an unknown sub-modular function of coverage when sensors are selected according to MAX, SUM, or PROB? We prove that the guarantees are very bad: In the worst case, coverage differs by a factor of sqrt(n), where n is the number of sensors. We show in simulations on synthetic and real data that the differences can be quite high as well. We show how to potentially address this problem using a hybrid of the coverage functions.

Original language	English
Title of host publication	Proceedings - IEEE International Conference on Distributed Computing in Sensor Systems, DCOSS 2015
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	98-107
Number of pages	10
ISBN (Electronic)	9781479988563
DOIs	https://doi.org/10.1109/DCOSS.2015.24
State	Published - 22 Jul 2015
Event	11th IEEE International Conference on Distributed Computing in Sensor Systems, DCOSS 2015 - Fortaleza, Brazil Duration: 10 Jun 2015 → 12 Jun 2015

Publication series

Name	Proceedings - IEEE International Conference on Distributed Computing in Sensor Systems, DCOSS 2015

Conference

Conference	11th IEEE International Conference on Distributed Computing in Sensor Systems, DCOSS 2015
Country/Territory	Brazil
City	Fortaleza
Period	10/06/15 → 12/06/15

Bibliographical note

Publisher Copyright:
© 2015 IEEE.

Access to Document

10.1109/DCOSS.2015.24

Cite this

Bar-Noy, A., Johnson, M. P., Naghibolhosseini, N., Rawitz, D., & Shamoun, S. (2015). The price of incorrectly aggregating coverage values in sensor selection. In Proceedings - IEEE International Conference on Distributed Computing in Sensor Systems, DCOSS 2015 (pp. 98-107). Article 7165028 (Proceedings - IEEE International Conference on Distributed Computing in Sensor Systems, DCOSS 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/DCOSS.2015.24

Bar-Noy, Amotz ; Johnson, Matthew P. ; Naghibolhosseini, Nooreddin et al. / The price of incorrectly aggregating coverage values in sensor selection. Proceedings - IEEE International Conference on Distributed Computing in Sensor Systems, DCOSS 2015. Institute of Electrical and Electronics Engineers Inc., 2015. pp. 98-107 (Proceedings - IEEE International Conference on Distributed Computing in Sensor Systems, DCOSS 2015).

@inproceedings{f2f292fadd99494987743fd92492b898,

title = "The price of incorrectly aggregating coverage values in sensor selection",

abstract = "An important problem in the study of sensor networks is how to select a set of sensors that maximizes coverage of other sensors. Given pair wise coverage values, three commonly found functions give some estimate of the aggregate coverage possible by a set of sensors: maximum coverage by any selected sensor (MAX), total coverage by all selected sensors (SUM), and the probability of correct prediction by at least one sensor (PROB). MAX and SUM are two extremes of possible coverage, while PROB, based on an independence assumption, is in the middle. This paper addresses the following question: what guarantees can be made of coverage that is evaluated by an unknown sub-modular function of coverage when sensors are selected according to MAX, SUM, or PROB? We prove that the guarantees are very bad: In the worst case, coverage differs by a factor of sqrt(n), where n is the number of sensors. We show in simulations on synthetic and real data that the differences can be quite high as well. We show how to potentially address this problem using a hybrid of the coverage functions.",

author = "Amotz Bar-Noy and Johnson, {Matthew P.} and Nooreddin Naghibolhosseini and Dror Rawitz and Simon Shamoun",

note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 11th IEEE International Conference on Distributed Computing in Sensor Systems, DCOSS 2015 ; Conference date: 10-06-2015 Through 12-06-2015",

year = "2015",

month = jul,

day = "22",

doi = "10.1109/DCOSS.2015.24",

language = "אנגלית",

series = "Proceedings - IEEE International Conference on Distributed Computing in Sensor Systems, DCOSS 2015",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "98--107",

booktitle = "Proceedings - IEEE International Conference on Distributed Computing in Sensor Systems, DCOSS 2015",

address = "ארצות הברית",

}

Bar-Noy, A, Johnson, MP, Naghibolhosseini, N, Rawitz, D & Shamoun, S 2015, The price of incorrectly aggregating coverage values in sensor selection. in Proceedings - IEEE International Conference on Distributed Computing in Sensor Systems, DCOSS 2015., 7165028, Proceedings - IEEE International Conference on Distributed Computing in Sensor Systems, DCOSS 2015, Institute of Electrical and Electronics Engineers Inc., pp. 98-107, 11th IEEE International Conference on Distributed Computing in Sensor Systems, DCOSS 2015, Fortaleza, Brazil, 10/06/15. https://doi.org/10.1109/DCOSS.2015.24

The price of incorrectly aggregating coverage values in sensor selection. / Bar-Noy, Amotz; Johnson, Matthew P.; Naghibolhosseini, Nooreddin et al.
Proceedings - IEEE International Conference on Distributed Computing in Sensor Systems, DCOSS 2015. Institute of Electrical and Electronics Engineers Inc., 2015. p. 98-107 7165028 (Proceedings - IEEE International Conference on Distributed Computing in Sensor Systems, DCOSS 2015).

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

TY - GEN

T1 - The price of incorrectly aggregating coverage values in sensor selection

AU - Bar-Noy, Amotz

AU - Johnson, Matthew P.

AU - Naghibolhosseini, Nooreddin

AU - Rawitz, Dror

AU - Shamoun, Simon

PY - 2015/7/22

Y1 - 2015/7/22

N2 - An important problem in the study of sensor networks is how to select a set of sensors that maximizes coverage of other sensors. Given pair wise coverage values, three commonly found functions give some estimate of the aggregate coverage possible by a set of sensors: maximum coverage by any selected sensor (MAX), total coverage by all selected sensors (SUM), and the probability of correct prediction by at least one sensor (PROB). MAX and SUM are two extremes of possible coverage, while PROB, based on an independence assumption, is in the middle. This paper addresses the following question: what guarantees can be made of coverage that is evaluated by an unknown sub-modular function of coverage when sensors are selected according to MAX, SUM, or PROB? We prove that the guarantees are very bad: In the worst case, coverage differs by a factor of sqrt(n), where n is the number of sensors. We show in simulations on synthetic and real data that the differences can be quite high as well. We show how to potentially address this problem using a hybrid of the coverage functions.

AB - An important problem in the study of sensor networks is how to select a set of sensors that maximizes coverage of other sensors. Given pair wise coverage values, three commonly found functions give some estimate of the aggregate coverage possible by a set of sensors: maximum coverage by any selected sensor (MAX), total coverage by all selected sensors (SUM), and the probability of correct prediction by at least one sensor (PROB). MAX and SUM are two extremes of possible coverage, while PROB, based on an independence assumption, is in the middle. This paper addresses the following question: what guarantees can be made of coverage that is evaluated by an unknown sub-modular function of coverage when sensors are selected according to MAX, SUM, or PROB? We prove that the guarantees are very bad: In the worst case, coverage differs by a factor of sqrt(n), where n is the number of sensors. We show in simulations on synthetic and real data that the differences can be quite high as well. We show how to potentially address this problem using a hybrid of the coverage functions.

UR - http://www.scopus.com/inward/record.url?scp=84945922348&partnerID=8YFLogxK

U2 - 10.1109/DCOSS.2015.24

DO - 10.1109/DCOSS.2015.24

M3 - ???researchoutput.researchoutputtypes.contributiontobookanthology.conference???

AN - SCOPUS:84945922348

T3 - Proceedings - IEEE International Conference on Distributed Computing in Sensor Systems, DCOSS 2015

SP - 98

EP - 107

BT - Proceedings - IEEE International Conference on Distributed Computing in Sensor Systems, DCOSS 2015

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 11th IEEE International Conference on Distributed Computing in Sensor Systems, DCOSS 2015

Y2 - 10 June 2015 through 12 June 2015

ER -

Bar-Noy A, Johnson MP, Naghibolhosseini N, Rawitz D, Shamoun S. The price of incorrectly aggregating coverage values in sensor selection. In Proceedings - IEEE International Conference on Distributed Computing in Sensor Systems, DCOSS 2015. Institute of Electrical and Electronics Engineers Inc. 2015. p. 98-107. 7165028. (Proceedings - IEEE International Conference on Distributed Computing in Sensor Systems, DCOSS 2015). doi: 10.1109/DCOSS.2015.24

The price of incorrectly aggregating coverage values in sensor selection

Abstract

Publication series

Conference

Bibliographical note

Access to Document

Other files and links

Fingerprint

Cite this