research-article

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

Get Access

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.

References

[1]

C. Bettstetter, G. Resta, and P. Santi. The node distribution of the random waypoint mobility model for wireless ad hoc networks. Mobile Computing, IEEE Transactions on, 2(3), 2003.

Digital Library

Google Scholar

[2]

P. Hui, A. Chaintreau, J. Scott, R. Gass, J. Crowcroft, and C. Diot. Pocket switched networks and human mobility in conference environments. In WDTN, 2005.

Digital Library

Google Scholar

[3]

A. Keränen, J. Ott, and T. Kärkkäinen. The one simulator for dtn protocol evaluation. In Simutools, 2009.

Digital Library

Google Scholar

[4]

C. P. Mayer. osm2wkt - openstreetmap to well-known-text conversion. http://www.tm.kit.edu/mayer/osm2wkt, 2010.

Google Scholar

[5]

E.-H. Ngai, H. Huang, J. Liu, and M. Srivastava. Oppsense: Information sharing for mobile phones in sensing field with data repositories. In SECON, 2011.

Crossref

Google Scholar

[6]

J. Ott, E. Hyytia, P. Lassila, T. Vaegs, and J. Kangasharju. Floating content: Information sharing in urban areas. In PerCom, 2011.

Digital Library

Google Scholar

[7]

B. Pasztor, M. Musolesi, and C. Mascolo. Opportunistic mobile sensor data collection with scar. In MASS, 2007.

Crossref

Google Scholar

[8]

K. K. Rachuri, C. Mascolo, M. Musolesi, and P. J. Rentfrow. Sociablesense: Exploring the trade-offs of adaptive sampling and computation offloading for social sensing. MobiCom. ACM, 2011.

Digital Library

Google Scholar

[9]

R. K. Rana, C. T. Chou, S. S. Kanhere, N. Bulusu, and W. Hu. Ear-phone: An end-to-end participatory urban noise mapping system. IPSN, 2010.

Digital Library

Google Scholar

[10]

I. Rhee, M. Shin, S. Hong, K. Lee, S. J. Kim, and S. Chong. On the levy-walk nature of human mobility. IEEE/ACM Trans. Netw., 19(3), 2011.

Digital Library

Google Scholar

[11]

J. Soares and R. Rocha. Charon: Routing in low-density opportunistic wireless sensor networks. In Wireless Days (WD), IFIP, 2009.

Digital Library

Google Scholar

[12]

H. Xiong, D. Zhang, G. Chen, L. Wang, and V. Gauthier. Crowdtasker: Maximizing coverage quality in piggyback crowdsensing under budget constraint. In PerCom, 2015.

Crossref

Google Scholar

[13]

D. Zhao, H. Ma, and L. Liu. Energy-efficient opportunistic coverage for people-centric urban sensing. Wireless Networks, 20(6), 2014.

Digital Library

Google Scholar

[14]

D. Zhao, H. Ma, and S. Tang. Coupon: Cooperatively building sensing maps in mobile opportunistic networks. In MASS, Oct 2013.

Digital Library

Google Scholar

Cited By

View all

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

Recommendations

Sensor scheduling for p-percent coverage in wireless sensor networks

We study sensor scheduling problems of p-percent coverage in this paper and propose two scheduling algorithms to prolong network lifetime due to the fact that for some applications full coverage is not necessary and different subareas of the monitored ...
Connectivity preserving localized coverage algorithm for area monitoring using wireless sensor networks

Efficient network coverage and connectivity are the requisites for most Wireless Sensor Network (WSN) deployments, particularly those concerned with area monitoring. Due to the resource constraints of the sensor nodes, redundancy of coverage area must ...
Integrated Connectivity and Coverage Techniques for Wireless Sensor Networks
MobiWac '16: Proceedings of the 14th ACM International Symposium on Mobility Management and Wireless Access

A wireless sensor network (WSN) consists of a group of energy-constrained sensor nodes with the ability of both sensing and communication, which can be deployed in a field of interesting (FoI) for detecting or monitoring some special events and then ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

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]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 03 October 2016

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Qualifiers

Research-article

Conference

MobiCom'16

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

October 3 - 7, 2016

New York, New York City

Acceptance Rates

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

Overall Acceptance Rate 61 of 159 submissions, 38%

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

2
Total Citations
View Citations
85
Total Downloads

Downloads (Last 12 months)3
Downloads (Last 6 weeks)0

Reflects downloads up to 24 Sep 2024

Other Metrics

View Author Metrics

Citations

Cited By

View all

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

View Options

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

ePub

View this article in ePub.

ePub

Abstract

References

Cited By

Recommendations

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

Comments

Information

Published In

Publisher

Publication History

Permissions

Check for updates

Qualifiers

Conference

Acceptance Rates

Contributors

Other Metrics

Bibliometrics

Article Metrics

Other Metrics

Citations

Cited By

Get Access

Login options

Full Access

View options

PDF

eReader

ePub

Figures

Other

Share

Share this Publication link

Share on social media

Affiliations