When D2D meets cloud: Hybrid mobile task offloadings in fog computing

Xu Chen, Junshan Zhang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

50 Scopus citations

Abstract

In this paper we propose HyFog, a novel hybrid task offloading framework in fog computing, where device users have the flexibility of choosing among multiple options for task executions, including local mobile execution, Device-to-Device (D2D) offloaded execution, and Cloud offloaded execution. We further develop a novel three-layer graph matching algorithm for efficient hybrid task offloading among the devices. Specifically, we first construct a three-layer graph to capture the choice space enabled by these three execution approaches, and then the problem of minimizing the total task execution cost is recast as a minimum weight matching problem over the constructed three-layer graph, which can be efficiently solved using the Edmonds's Blossom algorithm. Numerical results demonstrate that the proposed three-layer graph matching solution can achieve superior performance, with more than 50% cost reduction over the case of local task executions by all the devices.

Original languageEnglish (US)
Title of host publication2017 IEEE International Conference on Communications, ICC 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781467389990
DOIs
StatePublished - Jul 28 2017
Event2017 IEEE International Conference on Communications, ICC 2017 - Paris, France
Duration: May 21 2017May 25 2017

Other

Other2017 IEEE International Conference on Communications, ICC 2017
CountryFrance
CityParis
Period5/21/175/25/17

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Electrical and Electronic Engineering

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    Chen, X., & Zhang, J. (2017). When D2D meets cloud: Hybrid mobile task offloadings in fog computing. In 2017 IEEE International Conference on Communications, ICC 2017 [7996590] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICC.2017.7996590