Crowd-Cache: Leveraging on spatio-temporal correlation in content popularity for mobile networking in proximity

Kanchana Thilakarathna, Fang Zhou Jiang*, Sirine Mrabet, Mohamed Ali Kaafar, Aruna Seneviratne, Gaogang Xie

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)


Mobile capped plans are being increasingly adopted by mobile operators due to an exponential data traffic growth. Users then often suffer high data consumption costs as well as poor quality of experience. In this paper, we introduce a novel content access scheme, Crowd-Cache, which enables mobile networking in proximity by exploiting the transient co-location of devices, the epidemic nature of content popularity, and the capabilities of smart mobile devices. Crowd-Cache provides mobile users access to popular content cheaply with low latency while improving the overall quality of experience. We model the Crowd-Cache system in a probabilistic framework using a real-life dataset of video content access. The simulation results show that, in a public transportation scenario, more than 80% of the passengers can save at least 40% on their cellular data usage during a typical average city bus commute of 10 minutes. Finally, we show the practical viability of the system by implementing and evaluating the system on Android devices.

Original languageEnglish
Pages (from-to)104-117
Number of pages14
JournalComputer Communications
Publication statusPublished - 1 Mar 2017
Externally publishedYes


  • Crowd-sourcing
  • Mobile content distribution
  • Mobile networking in proximity
  • Mobile off-loading
  • Opportunistic content sharing


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