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https://hdl.handle.net/1822/52706
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Campo DC | Valor | Idioma |
---|---|---|
dc.contributor.author | Lima, Emanuel | por |
dc.contributor.author | Aguiar, Ana | por |
dc.contributor.author | Carvalho, Paulo | por |
dc.date.accessioned | 2018-03-18T18:59:21Z | - |
dc.date.issued | 2017 | - |
dc.identifier.isbn | 9781450354783 | por |
dc.identifier.uri | https://hdl.handle.net/1822/52706 | - |
dc.description.abstract | This paper uses data mining of a mobile crowdsensed dataset of passive WiFi scans to define attributes that can characterize a chaotic WiFi deployment with respect to offloading opportunities. Besides indicators of signal quality, we define indicators of contact windows and contact opportunities with an Access Point (AP). We apply k-means clustering to identify classes of APs, and observe that interference metrics are more relevant than plain RSSI; that contact window metrics can be estimated using only APs’ coverage data; and that popularity and importance can characterize APs whether the offloading targets many or only a few users. | por |
dc.description.sponsorship | (undefined) | por |
dc.language.iso | eng | por |
dc.publisher | Association for Computing Machinery (ACM) | por |
dc.rights | restrictedAccess | por |
dc.subject | Attributes | por |
dc.subject | Characterization | por |
dc.subject | Offloading | por |
dc.subject | Wi-Fi | por |
dc.title | Offloading surrogates characterization via mobile crowdsensing | por |
dc.type | conferencePaper | por |
dc.peerreviewed | yes | por |
oaire.citationStartPage | 7 | por |
oaire.citationEndPage | 12 | por |
dc.date.updated | 2018-03-15T12:07:02Z | - |
dc.identifier.doi | 10.1145/3139243.3139253 | por |
dc.description.publicationversion | info:eu-repo/semantics/publishedVersion | por |
sdum.export.identifier | 4527 | - |
sdum.conferencePublication | CrowdSenSys 2017 - Proceedings of the 1st ACM Workshop on Mobile Crowdsensing Systems and Applications, Part of SenSys 2017 | por |
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Ficheiro | Descrição | Tamanho | Formato | |
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Crowdsense 2017.pdf Acesso restrito! | 864,29 kB | Adobe PDF | Ver/Abrir |