Fog-based Data Offloading in Urban IoT Scenarios

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

Researchers

Research units

  • Princeton University
  • Carnegie Mellon University
  • Purdue University

Abstract

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.

Details

Original languageEnglish
Title of host publicationINFOCOM 2019 - IEEE Conference on Computer Communications
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

Publication series

NameProceedings - IEEE INFOCOM
Volume2019-April
ISSN (Print)0743-166X

Conference

ConferenceIEEE Conference on Computer Communications
Abbreviated titleINFOCOM
CountryFrance
CityParis
Period29/04/201902/05/2019

    Research areas

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

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