Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (1)
  • Open Access

    ARTICLE

    Preserving the Efficiency and Quality of Contributed Data in MCS via User and Task Profiling

    Dingwen Wang, Ming Zhao*

    Journal of Cyber Security, Vol.2, No.2, pp. 63-68, 2020, DOI:10.32604/jcs.2020.07229 - 14 July 2020

    Abstract Mobile crowdsensing is a new paradigm with powerful performance for data collection through a large number of smart devices. It is essential to obtain high quality data in crowdsensing campaign. Most of the existing specs ignore users’ diversity, focus on solving complicated optimization problem, and consider devices as instances of intelligent software agents which can make reasonable choices on behalf of users. Thus, the efficiency and quality of contributed data cannot be preserved simultaneously. In this paper, we propose a new scheme for improving the quality of contributed data, which recommends tasks to users based More >

Displaying 1-10 on page 1 of 1. Per Page