CUDA-accelerated task scheduling in vehicular clouds with opportunistically available V2I

Yassine Maalej, Ahmed Abderrahim, Mohsen Guizani, Bechir Hamdaoui

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

1 Citation (Scopus)

Abstract

In this paper, we consider the use of CUDA-based Graphics Processing Units (GPUs) as high performance parallel computing for the purpose of accelerating the application task scheduling in Vehicular Cloud Computing (VCC) systems. We leverage the Single Instruction Multiple Data (SIMD) mode in General-Purpose Graphic Processing Units (GPGPUs) to solve the value iteration algorithm of the defined Markov Decision Process (MDP) of task scheduling on real VCC. We consider opportunistically available Vehicle to Infrastructure (V2I) communication in Dedicated Short Range Communication (DSRC) used in Vehicular ad hoc networks (VANETs) for the vehicular clouds.

Original languageEnglish
Title of host publication2017 IEEE International Conference on Communications, ICC 2017
EditorsMerouane Debbah, David Gesbert, Abdelhamid Mellouk
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781467389990
DOIs
Publication statusPublished - 28 Jul 2017
Externally publishedYes
Event2017 IEEE International Conference on Communications, ICC 2017 - Paris, France
Duration: 21 May 201725 May 2017

Publication series

NameIEEE International Conference on Communications
ISSN (Print)1550-3607

Conference

Conference2017 IEEE International Conference on Communications, ICC 2017
Country/TerritoryFrance
CityParis
Period21/05/1725/05/17

Keywords

  • CUDA
  • GPUs
  • MDP
  • SIMD
  • V2I
  • VANETs
  • VCC

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