Fog-based Data Offloading in Urban IoT Scenarios

Pranvera Kortoçi, Liang Zheng, Carlee Joe-Wong, Mario Di Francesco, Mung Chiang

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

24 Citations (Scopus)
266 Downloads (Pure)


Urban environments are a particularly important application scenario for the Internet of Things (IoT). These environments are usually dense and dynamic; in contrast, IoT devices are resource-constrained, thus making reliable data collection and scalable coordination a challenge. This work leverages the fog networking paradigm to devise a multi-tier data offloading protocol suitable for diverse data-centric applications in urban IoT scenarios. Specifically, it takes advantage of heterogeneity in the network so that sensors can collaboratively offload data to each other or to mobile gateways. Second, it evaluates the performance of this offloading process through the amount of data successfully reported to the cloud. In detail, it provides an analytical characterization of data drop-off rates as a random process and derives a light-weight yet efficient method for collaborative data offloading. Finally, it shows that the proposed fog-based solution significantly decreases the data drop-off rate through both analysis and extensive trace-driven simulations based on human mobility data from real urban settings.

Original languageEnglish
Title of host publicationINFOCOM 2019 - IEEE Conference on Computer Communications
Number of pages9
ISBN (Electronic)9781728105154
Publication statusPublished - 1 Apr 2019
MoE publication typeA4 Article in a conference publication
EventIEEE Conference on Computer Communications - Paris, France
Duration: 29 Apr 20192 May 2019
Conference number: 38

Publication series

NameProceedings - IEEE INFOCOM
ISSN (Print)0743-166X


ConferenceIEEE Conference on Computer Communications
Abbreviated titleINFOCOM


  • collaborative offloading
  • data drop-off rate
  • Fog networking
  • Internet of Things


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