• DocumentCode
    163681
  • Title

    Self-Similarity Analysis of Mobile Instant Messaging Applications´ Traffic and Server

  • Author

    Qizhao Zhou ; Ke Yu ; Xiaofei Wu ; Jiaxi Di ; Xinyu Zhang

  • Author_Institution
    Sch. of Inf. & Commun. Eng., Beijing Univ. of Posts & Telecommun., Beijing, China
  • fYear
    2014
  • fDate
    14-17 Sept. 2014
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    In modern times, mobile online communication through Instant Messaging is a part of many people´s daily lives, which in turn forms a very complex and huge social network on Internet. In this paper, based on real traffic flow data collected from operational networks of Mobile Internet Service Provider, we analyze the traffic of several popular Mobile Instant Messaging Service in China, i.e. WECHAT, QQ, FETION. By constructing flow graphs of IM services, we list Top-five busiest IM servers, and investigate the statistical characteristics of the IM applications and servers. The traffic data is divided into data samples by a second, we aggregate packets for each group and sum packets number in different time scale, and the Self-similarity in the IM services´ traffic are proposed, then the existence of Self-similarity in the IM traffic is studied and compared. Our extensive researches of the mobile traffic show that the traffic of Instant Messaging services has the characteristics of self- similarity, especially WECHAT.
  • Keywords
    Internet; electronic messaging; flow graphs; mobile communication; telecommunication traffic; IM services traffic; WECHAT; flow graphs; mobile Internet service provider; mobile instant messaging; operational networks; real traffic flow data; self-similarity analysis; traffic data; Aggregates; Correlation; Instant messaging; Mobile communication; Mobile computing; Servers;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Vehicular Technology Conference (VTC Fall), 2014 IEEE 80th
  • Conference_Location
    Vancouver, BC
  • Type

    conf

  • DOI
    10.1109/VTCFall.2014.6966174
  • Filename
    6966174