Crowdsensing Mobile Content and Context Data: Lessons Learned in the Wild - Archive ouverte HAL Access content directly
Conference Papers Year : 2017

Crowdsensing Mobile Content and Context Data: Lessons Learned in the Wild

Abstract

This paper discusses the design and development efforts made to collect data using an opportunistic crowdsensing mobile application. Relevant issues are underlined, and solutions proposed within the CHIST-ERA Macaco project for the specifics of collecting fine-grained content and context data are highlighted. Global statistics on the data gathered for over a year of collection show its quality: Macaco data provides a longterm and fine-grained sampling of the user behavior and network usage that is relevant to model and analyse for future content and context-aware networking developments.
Fichier principal
Vignette du fichier
jaffresrunser_18977.pdf (455.88 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-01787388 , version 1 (07-05-2018)

Identifiers

  • HAL Id : hal-01787388 , version 1
  • OATAO : 18977

Cite

Katia Jaffrès-Runser, Gentian Jakllari, Tao Peng, Vlad-Tiberiu Nitu. Crowdsensing Mobile Content and Context Data: Lessons Learned in the Wild. IEEE International Conference on Pervasive Computing and Communications Workshops: Workshop on Data Analytics for Mobile Networking (PerCom Workshops 2017), Mar 2017, Kona, Hawai, United States. pp. 1-4. ⟨hal-01787388⟩
69 View
48 Download

Share

Gmail Facebook X LinkedIn More