Behbehani, FS, Musa, M, Elgorashi, T et al. (1 more author) (2019) Energy-Efficient Distributed Processing in Vehicular Cloud Architecture. In: 2019 21st International Conference on Transparent Optical Networks (ICTON). ICTON 2019: 21st International Conference on Transparent Optical Networks, 09-13 Jul 2019, Angers, France. IEEE ISBN 9781728127798
Abstract
Facilitating the revolution for smarter cities, vehicles are getting smarter and equipped with more resources to go beyond transportation functionality. On-Board Units (OBU) are efficient computers inside vehicles that serve safety and non-safety based applications. However, much of these resources are underutilised. On the other hand, more users are relying now on cloud computing which is becoming costly and energy consuming. In this paper, we develop a Mixed Integer linear Programming (MILP) model that optimizes the allocation of processing demands in an architecture that encompasses the vehicles, edge and cloud computing with the objective of minimizing power consumption. The results show power savings of 70% - 90% compared to conventional clouds for small demands. For medium and large demand sizes, the results show 20% - 30% power saving as the cloud was used partially due to capacity limitations on the vehicular and edge nodes.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Keywords: | distributed processing, wireless, edge nodes, vehicular networks. |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Institute of Communication & Power Networks (Leeds) |
Funding Information: | Funder Grant number EPSRC EP/H040536/1 EPSRC EP/K016873/1 EPSRC EP/R511717/1 EPSRC EP/S016570/1 |
Depositing User: | Symplectic Publications |
Date Deposited: | 24 Jul 2019 10:52 |
Last Modified: | 05 Nov 2019 15:20 |
Published Version: | https://ieeexplore.ieee.org/xpl/conhome/1000766/al... |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/ICTON.2019.8840335 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:148916 |