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Conference Paper: Optimal Citizen-Centric Sensor Placement for Citywide Environmental Monitoring - A Submodular Approach

TitleOptimal Citizen-Centric Sensor Placement for Citywide Environmental Monitoring - A Submodular Approach
Authors
Issue Date2018
PublisherIEEE.
Citation
2018 IEEE International Conference on Sensing, Communication and Networking (SECON Workshops), Hong Kong, 11 June 2018. In 2018 IEEE International Conference on Sensing, Communication and Networking (SECON Workshops) How to Cite?
AbstractThe general environmental monitoring problem refers to the task of placing sensors or stations to optimize certain objectives under budget constraints. Application scenarios include monitoring temperature, water contamination, air quality etc. As citizens are increasingly concerned about the surrounding environment, it is important to provide sufficient and accurate information to the public. In this study, we focus on the problem of optimal citizen-centric sensor placement, i.e, given a set of locations within the city, we aim at placing sensors or stations at locations that will benefit as many citizens as possible under budget constraints. We prove that the problem is NP-hard, yet the objective function has the nice non-decreasing and submodular property. Then the efficient greedy algorithm and its variants can be adopted with a guaranteed approximation ratio of (1-1/e) for the unit cost case and 1/2 (1-1/e) for the general cost case. Finally we demonstrate the effectiveness of the proposed approach by comparing with two baseline algorithms through a case study.
Descriptioneid_2-s2.0-85050553170
Persistent Identifierhttp://hdl.handle.net/10722/263547
ISBN

 

DC FieldValueLanguage
dc.contributor.authorSUN, C-
dc.contributor.authorLi, VOK-
dc.contributor.authorLam, JCK-
dc.date.accessioned2018-10-22T07:40:42Z-
dc.date.available2018-10-22T07:40:42Z-
dc.date.issued2018-
dc.identifier.citation2018 IEEE International Conference on Sensing, Communication and Networking (SECON Workshops), Hong Kong, 11 June 2018. In 2018 IEEE International Conference on Sensing, Communication and Networking (SECON Workshops)-
dc.identifier.isbn9781538652411-
dc.identifier.urihttp://hdl.handle.net/10722/263547-
dc.descriptioneid_2-s2.0-85050553170-
dc.description.abstractThe general environmental monitoring problem refers to the task of placing sensors or stations to optimize certain objectives under budget constraints. Application scenarios include monitoring temperature, water contamination, air quality etc. As citizens are increasingly concerned about the surrounding environment, it is important to provide sufficient and accurate information to the public. In this study, we focus on the problem of optimal citizen-centric sensor placement, i.e, given a set of locations within the city, we aim at placing sensors or stations at locations that will benefit as many citizens as possible under budget constraints. We prove that the problem is NP-hard, yet the objective function has the nice non-decreasing and submodular property. Then the efficient greedy algorithm and its variants can be adopted with a guaranteed approximation ratio of (1-1/e) for the unit cost case and 1/2 (1-1/e) for the general cost case. Finally we demonstrate the effectiveness of the proposed approach by comparing with two baseline algorithms through a case study.-
dc.languageeng-
dc.publisherIEEE.-
dc.relation.ispartof2018 IEEE International Conference on Sensing, Communication and Networking (SECON Workshops)-
dc.rights2018 IEEE International Conference on Sensing, Communication and Networking (SECON Workshops). Copyright © IEEE.-
dc.titleOptimal Citizen-Centric Sensor Placement for Citywide Environmental Monitoring - A Submodular Approach-
dc.typeConference_Paper-
dc.identifier.emailLi, VOK: vli@eee.hku.hk-
dc.identifier.emailLam, JCK: h9992013@hkucc.hku.hk-
dc.identifier.authorityLi, VOK=rp00150-
dc.identifier.authorityLam, JCK=rp00864-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/SECONW.2018.8396355-
dc.identifier.hkuros294330-
dc.identifier.hkuros292173-
dc.publisher.placeUnited States-

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