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Towards even coverage monitoring with opportunistic sensor networks

Authors:

Hjalmar Wennerström,

Christian RohnerAuthors Info & Claims

CHANTS '16: Proceedings of the Eleventh ACM Workshop on Challenged Networks

Pages 81 - 86

https://doi.org/10.1145/2979683.2979691

Published: 03 October 2016 Publication History

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Abstract

Opportunistic sensor networks typically rely on node mobility to monitor an area by collecting samples at different locations. In this paper we show how the mobility in combination with the periodic sampling of nodes causes large differences in the sensor coverage. We address this issue by leveraging simple heuristics based on local knowledge, employing an adaptive sampling scheme. The main insight is that areas where over-sampling is prevalent exhibit a high correlation with node contacts. Results obtained from both synthetic and real-world traces show that a dramatic decrease in oversampling of affected areas is achievable alongside a smaller increase of samples in more sparse areas.

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Kong DGao XChen G(2022)Collection Tree for Wireless Coverage Problem in Mobile Crowdsensing2022 16th International Conference on Ubiquitous Information Management and Communication (IMCOM)10.1109/IMCOM53663.2022.9721737(1-7)Online publication date: 3-Jan-2022
https://doi.org/10.1109/IMCOM53663.2022.9721737
Li YSu XLindgren AShi XCai XRiekki JQue X(2017)Distance Assisted Information Dissemination with Broadcast Suppression for ICN-Based VANETInternet of Vehicles – Technologies and Services10.1007/978-3-319-51969-2_15(179-193)Online publication date: 20-Jan-2017
https://doi.org/10.1007/978-3-319-51969-2_15

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Published In

CHANTS '16: Proceedings of the Eleventh ACM Workshop on Challenged Networks

October 2016

92 pages

ISBN:9781450342568

DOI:10.1145/2979683

Program Chairs:
Chiara Boldrini
IIT-CNR, Italy
,
Marcelo Dias de Amorim
UPMC/ LIP6, France

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

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Published: 03 October 2016

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MobiCom'16

MobiCom'16: The 22nd Annual International Conference on Mobile Computing and Networking

October 3 - 7, 2016

New York, New York City

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CHANTS '16 Paper Acceptance Rate 14 of 27 submissions, 52%;

Overall Acceptance Rate 61 of 159 submissions, 38%

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Kong DGao XChen G(2022)Collection Tree for Wireless Coverage Problem in Mobile Crowdsensing2022 16th International Conference on Ubiquitous Information Management and Communication (IMCOM)10.1109/IMCOM53663.2022.9721737(1-7)Online publication date: 3-Jan-2022
https://doi.org/10.1109/IMCOM53663.2022.9721737
Li YSu XLindgren AShi XCai XRiekki JQue X(2017)Distance Assisted Information Dissemination with Broadcast Suppression for ICN-Based VANETInternet of Vehicles – Technologies and Services10.1007/978-3-319-51969-2_15(179-193)Online publication date: 20-Jan-2017
https://doi.org/10.1007/978-3-319-51969-2_15

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Sensor scheduling for p-percent coverage in wireless sensor networks

Connectivity preserving localized coverage algorithm for area monitoring using wireless sensor networks

Integrated Connectivity and Coverage Techniques for Wireless Sensor Networks

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