Imperial College London


Faculty of EngineeringDepartment of Computing

Professor of Computer Systems



+44 (0)20 7594 8375j.mccann Website




Miss Teresa Ng +44 (0)20 7594 8300




260ACE ExtensionSouth Kensington Campus






BibTex format

author = {Wu, D and Liu, Q and Li, Y and McCann, JA and Regan, AC and Venkatasubramanian, N},
doi = {10.1109/TNET.2016.2533399},
journal = {IEEE/ACM Transactions on Networking},
pages = {3634--3647},
title = {Adaptive Lookup of Open WiFi Using Crowdsensing},
url = {},
volume = {24},
year = {2016}

RIS format (EndNote, RefMan)

AB - Open WiFi access points (APs) are demonstratingthat they can provide opportunistic data services to movingvehicles. We present CrowdWiFi, a novel system to lookup roadside WiFi APs located outdoors or inside buildings.CrowdWiFi consists of two components: online compressivesensing (CS) and offline crowdsourcing. Online CS presents anefficient framework for the coarse-grained estimation of nearbyAPs along the driving route, where received signal strength (RSS)values are recorded at runtime, and the number and location ofthe APs are recovered immediately based on limited RSS readingsand adaptive CS operations. Offline crowdsourcing assigns theonline CS tasks to crowd-vehicles and aggregates answers on abipartite graphical model. Crowd-server also iteratively infersthe reliability of each crowd-vehicle from the aggregated sensingresults, and then refines the estimation of the APs using weightedcentroid processing. Extensive simulation results and real testbedexperiments confirm that CrowdWiFi can successfully reducethe computation cost and energy consumption of roadside WiFilookup, while maintaining satisfactory localization accuracy.
AU - Wu,D
AU - Liu,Q
AU - Li,Y
AU - McCann,JA
AU - Regan,AC
AU - Venkatasubramanian,N
DO - 10.1109/TNET.2016.2533399
EP - 3647
PY - 2016///
SN - 1063-6692
SP - 3634
TI - Adaptive Lookup of Open WiFi Using Crowdsensing
T2 - IEEE/ACM Transactions on Networking
UR -
UR -
UR -
VL - 24
ER -