research-article

Adaptive Lookup of Open WiFi Using Crowdsensing

Authors:

Julie A. McCann,

Amelia C. Regan,

Nalini VenkatasubramanianAuthors Info & Claims

IEEE/ACM Transactions on Networking (TON), Volume 24, Issue 6

Pages 3634 - 3647

https://doi.org/10.1109/TNET.2016.2533399

Published: 01 December 2016 Publication History

Abstract

Open WiFi access points APs are demonstrating that they can provide opportunistic data services to moving vehicles. We present CrowdWiFi, a novel system to look up roadside WiFi APs located outdoors or inside buildings. CrowdWiFi consists of two components: online compressive sensing CS and offline crowdsourcing. Online CS presents an efficient framework for the coarse-grained estimation of nearby APs along the driving route, where received signal strength RSS values are recorded at runtime, and the number and location of the APs are recovered immediately based on limited RSS readings and adaptive CS operations. Offline crowdsourcing assigns the online CS tasks to crowd-vehicles and aggregates answers on a bipartite graphical model. Crowd-server also iteratively infers the reliability of each crowd-vehicle from the aggregated sensing results, and then refines the estimation of the APs using weighted centroid processing. Extensive simulation results and real testbed experiments confirm that CrowdWiFi can successfully reduce the computation cost and energy consumption of roadside WiFi lookup, while maintaining satisfactory localization accuracy.

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cover image IEEE/ACM Transactions on Networking

IEEE/ACM Transactions on Networking Volume 24, Issue 6

December 2016

635 pages

ISSN:1063-6692

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Copyright © 2016.

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IEEE Press

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Published: 01 December 2016

Published in TON Volume 24, Issue 6

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Cited By

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https://dl.acm.org/doi/10.5555/3691992.3692056
Guo HWu XLiu JMao BChen X(2024)Adaptive and Reliable Location Privacy Risk Sensing in Internet of VehiclesIEEE Transactions on Intelligent Transportation Systems10.1109/TITS.2024.338446425:9(12696-12708)Online publication date: 17-May-2024
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Wu DNie XAsmare EArkhipov DQin ZLi RMcCann JLi K(2020)Towards Distributed SDN: Mobility Management and Flow Scheduling in Software Defined Urban IoTIEEE Transactions on Parallel and Distributed Systems10.1109/TPDS.2018.288343831:6(1400-1418)Online publication date: 1-Jun-2020
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Eskandarian A(2020)Scanning the IssueIEEE Transactions on Intelligent Transportation Systems10.1109/TITS.2020.300182221:7(2689-2695)Online publication date: 26-Jun-2020
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Kim S(2019)Effective crowdsensing and routing algorithms for next generation vehicular networksWireless Networks10.1007/s11276-017-1632-925:4(1815-1827)Online publication date: 1-May-2019
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Darakeh FMohammad-Khani GAzmi P(2018)CRWSNPWireless Networks10.5555/3287990.328802724:8(2881-2897)Online publication date: 1-Nov-2018
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Lima EAguiar ACarvalho P(2017)Offloading Surrogates Characterization via Mobile CrowdsensingProceedings of the First ACM Workshop on Mobile Crowdsensing Systems and Applications10.1145/3139243.3139253(7-12)Online publication date: 6-Nov-2017
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