Scaling Microblogging Services with Divergent Traffic Demands

  • Tianyin Xu
  • Yang Chen
  • Lei Jiao
  • Ben Y. Zhao
  • Pan Hui
  • Xiaoming Fu
Conference paper

DOI: 10.1007/978-3-642-25821-3_2

Part of the Lecture Notes in Computer Science book series (LNCS, volume 7049)
Cite this paper as:
Xu T., Chen Y., Jiao L., Zhao B.Y., Hui P., Fu X. (2011) Scaling Microblogging Services with Divergent Traffic Demands. In: Kon F., Kermarrec AM. (eds) Middleware 2011. Middleware 2011. Lecture Notes in Computer Science, vol 7049. Springer, Berlin, Heidelberg

Abstract

Today’s microblogging services such as Twitter have long outgrown their initial designs as SMS-based social networks. Instead, a massive and steadily-growing user population of more than 100 million is using Twitter for everything from capturing the mood of the country to detecting earthquakes and Internet service failures. It is unsurprising that the traditional centralized client-server architecture has not scaled with user demands, leading to server overload and significant impairment of availability. In this paper, we argue that the divergence in usage models of microblogging services can be best addressed using complementary mechanisms, one that provides reliable messages between friends, and another that delivers events from popular celebrities and media outlets to their thousands or even millions of followers. We present Cuckoo, a new microblogging system that offloads processing and bandwidth costs away from a small centralized server base while ensuring reliable message delivery. We use a 20-day Twitter availability measurement to guide our design, and trace-driven emulation of 30,000 Twitter users to evaluate our Cuckoo prototype. Compared to the centralized approach, Cuckoo achieves 30-50% server bandwidth savings and 50-60% CPU load reduction, while guaranteeing reliable message delivery.

Download to read the full conference paper text

Copyright information

© IFIP International Federation for Information Processing 2011

Authors and Affiliations

  • Tianyin Xu
    • 1
  • Yang Chen
    • 1
  • Lei Jiao
    • 1
  • Ben Y. Zhao
    • 2
  • Pan Hui
    • 3
  • Xiaoming Fu
    • 1
  1. 1.University of GoettingenGermany
  2. 2.U.C. Santa BarbaraUSA
  3. 3.Deutsche Telekom LaboratoriesGermany

Personalised recommendations