L’Ecole doctorale EDITE – Ecole doctorale informatique, t\u00e9l\u00e9communications et \u00e9lectronique et T\u00e9l\u00e9com SudParis avec le Laboratoire de recherche SAMOVAR – Services r\u00e9partis, Architectures, MOd\u00e9lisation, Validation, Administration des R\u00e9seaux<\/p>\n
pr\u00e9sentent<\/p>\n
l\u2019AVIS DE SOUTENANCE de Monsieur WANG Leye<\/strong> le mercredi 18 mai 2016 \u00e0 14 heures – Salle A003<\/strong><\/p>\n 9 Rue Charles Fourier, 91000 \u00c9vry<\/p>\n Membres du jury :<\/strong><\/p>\n Directeur de th\u00e8se : Abdallah MHAMED – Ma\u00eetre de conf\u00e9rences<\/p>\n Rapporteurs :<\/strong><\/p>\n Herv\u00e9 RIVANO – Charg\u00e9 de recherche – HDR – INRIA\/INSA Lyon<\/p>\n St\u00e9phane GALLAND – Professeur – HDR – Universit\u00e9 de technologie Belfort-Montb\u00e9liard<\/p>\n Examinateurs :<\/strong><\/p>\n Steven MARTIN – Professeur HDR – Universit\u00e9 Paris-Sud<\/p>\n Djamal ZEGHLACHE – Professeur HDR – T\u00e9l\u00e9com SudParis<\/p>\n Farid Na\u00eft ABDESSELAM – Professeur HDR – Universit\u00e9 Paris Descartes<\/p>\n Daqing ZHANG – Directeur d’\u00e9tudes – T\u00e9l\u00e9com SudParis<\/p>\n R\u00e9sum\u00e9 :<\/strong><\/p>\n La collecte participative des donn\u00e9es mobiles est un nouveau paradigme d\u00e9di\u00e9 aux applications de d\u00e9tection urbaines utilisant une foule de participants munis de t\u00e9l\u00e9phones intelligents. Pour mener \u00e0 bien les t\u00e2ches de collecte participative des donn\u00e9es mobiles, diverses pr\u00e9occupations relatives aux participants et aux organisateurs doivent \u00eatre soigneusement prises en consid\u00e9ration. Pour les participants, la principale pr\u00e9occupation porte sur la consommation d’\u00e9nergie, le co\u00fbt des donn\u00e9es mobiles, etc. Pour les organisateurs, la qualit\u00e9 des donn\u00e9es et le budget sont les deux pr\u00e9occupations essentielles. Dans cette th\u00e8se, deux m\u00e9canismes de collecte participative des donn\u00e9es mobiles sont propos\u00e9s : le t\u00e9l\u00e9chargement montant collaboratif des donn\u00e9es et la collecte clairsem\u00e9e des donn\u00e9es mobiles. Pour le t\u00e9l\u00e9chargement montant collaboratif des donn\u00e9es, deux proc\u00e9d\u00e9s sont propos\u00e9s 1) \u00ab effSense \u00bb, qui fournit la meilleure solution permettant d\u2019\u00e9conomiser la consommation d’\u00e9nergie aux participants ayant un d\u00e9bit suffisant, et de r\u00e9duire le co\u00fbt des communications mobiles aux participants ayant un d\u00e9bit limit\u00e9; 2) \u00ab ecoSense \u00bb, qui permet de r\u00e9duire le remboursement incitatif par les organisateurs des frais associ\u00e9s au co\u00fbt des donn\u00e9es mobiles des participants. Dans la collecte clairsem\u00e9e des donn\u00e9es mobiles, les corr\u00e9lations spatiales et temporelles entre les donn\u00e9es d\u00e9tect\u00e9es sont exploit\u00e9es pour r\u00e9duire de mani\u00e8re significative le nombre de t\u00e2ches allou\u00e9es et, par cons\u00e9quent, le budget associ\u00e9 aux organisateurs, tout en assurant la qualit\u00e9 des donn\u00e9es. De plus, l\u2019intimit\u00e9 diff\u00e9rentielle est afin de r\u00e9pondre au besoin de pr\u00e9servation de la localisation des participants.<\/p>\n Abstract:<\/strong><\/p>\n Mobile crowdsensing is a novel paradigm for urban sensing applications using a crowd of participants’ sensor-equipped smartphones. To successfully complete mobile crowdsensing tasks, various concerns of participants and organizers need to be carefully considered. For participants, primary concerns include energy consumption, mobile data cost, privacy, etc. For organizers, data quality and budget are two critical concerns. In this dissertation, to address both participants’ and organizers’ concerns, two mobile crowdsensing mechanisms are proposed – collaborative data uploading and sparse mobile crowdsensing. In collaborative data uploading, participants help each other through opportunistic encounters and data relays in the data uploading process of crowdsensing, in order to save energy consumption, mobile data cost, etc. Specifically, two collaborative data uploading procedures are proposed (1) effSense, which helps participants with enough data plan to save energy consumption, and participants with little data plan to save mobile data cost; (2) ecoSense, which reduces organizers’ incentive refund that is paid for covering participants’ mobile data cost. In sparse mobile crowdsensing, spatial and temporal correlations among sensed data are leveraged to significantly reduce the number of allocated tasks thus organizers’ budget, still ensuring data quality. Specifically, a sparse crowdsensing task allocation framework, CCS-TA, is implemented with compressive sensing, active learning, and Bayesian inference techniques. Furthermore, differential privacy is introduced into sparse mobile crowdsensing to address participants’ location privacy concerns.<\/p>\n","protected":false},"excerpt":{"rendered":" L’Ecole doctorale EDITE – Ecole doctorale informatique, t\u00e9l\u00e9communications et \u00e9lectronique et T\u00e9l\u00e9com SudParis avec le Laboratoire de recherche SAMOVAR – Services r\u00e9partis, Architectures, MOd\u00e9lisation, Validation, Administration des R\u00e9seaux pr\u00e9sentent l\u2019AVIS DE SOUTENANCE de Monsieur WANG Leye Autoris\u00e9 \u00e0 pr\u00e9senter ses travaux en vue de l\u2019obtention du Doctorat de T\u00e9l\u00e9com SudParis avec l’Universit\u00e9 Paris 6 : 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\nAutoris\u00e9 \u00e0 pr\u00e9senter ses travaux en vue de l\u2019obtention du Doctorat de T\u00e9l\u00e9com SudParis avec l’Universit\u00e9 Paris 6 :<\/p>\n