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  • MEGEE Mobile Edge computing Geared v2x for E-mobility Ecosystem

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MEGEE: Mobile Edge computer Geared v2x for E-Mobility Ecosystem

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Published
  • Yue Cao
  • Celimuge Wu
  • Xu Zhang
  • William Liu
  • Linyu Peng
  • Muhammad Khalid
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Publication date15/04/2019
Host publication2019 IEEE Wireless Communications and Networking Conference (WCNC)
PublisherIEEE
Number of pages6
ISBN (Electronic)9781538676462
ISBN (Print)9781538676479
<mark>Original language</mark>English

Abstract

The introduction of Electric Vehicles (EVs) leads to new concern on the E-Mobility. Making charging reservation, by considering the EV's arrival time and its expected charging time at Charging Stations (CSs) has been studied to predict the dynamic status of CSs. In this paper, we propose a Mobile Edge computer Geared v2x for E-mobility Ecosystem (MEGEE), as a decentralized alternative to the conventional centralized cloud based architecture. MEGEE enables the Vehicular Delay/Disruption Tolerant Networking (VDTN)-driven anycasting for information delivery, and Mobile Edge Computing (MEC) functioned CSs for information mining and aggregation. MEGEE efficiently and timely processes essential charging reservations and charging control information, through the Internet of EVs and MEC servers. Our studies show that MEGEE can achieve the close charging performance as performed by the centralized system, while offers a significant saving in communications cost.

Bibliographic note

©2019 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.