TY - JOUR
T1 - Mobile edge computing for big-data-enabled electric vehicle charging
AU - Cao, Yue
AU - Song, Houbing
AU - Kaiwartya, Omprakash
AU - Zhou, Bingpeng
AU - Zhuang, Yuan
AU - Cao, Yang
AU - Zhang, Xu
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/3
Y1 - 2018/3
N2 - As one of the key drivers of smart grid, EVs are environment-friendly to alleviate CO2 pollution. Big data analytics could enable the move from Internet of EVs, to optimized EV charging in smart transportation. In this article, we propose a MECbased system, in line with a big data-driven planning strategy, for CS charging. The GC as cloud server further facilitates analytics of big data, from CSs (service providers) and on-the-move EVs (mobile clients), to predict the charging availability of CSs. Mobility-aware MEC servers interact with opportunistically encountered EVs to disseminate CSs' predicted charging availability, collect EVs' driving big data, and implement decentralized computing on data mining and aggregation. The case study shows the benefits of the MEC-based system in terms of communication efficiency (with repeated monitoring of a traffic jam) concerning the long-term popularity of EVs.
AB - As one of the key drivers of smart grid, EVs are environment-friendly to alleviate CO2 pollution. Big data analytics could enable the move from Internet of EVs, to optimized EV charging in smart transportation. In this article, we propose a MECbased system, in line with a big data-driven planning strategy, for CS charging. The GC as cloud server further facilitates analytics of big data, from CSs (service providers) and on-the-move EVs (mobile clients), to predict the charging availability of CSs. Mobility-aware MEC servers interact with opportunistically encountered EVs to disseminate CSs' predicted charging availability, collect EVs' driving big data, and implement decentralized computing on data mining and aggregation. The case study shows the benefits of the MEC-based system in terms of communication efficiency (with repeated monitoring of a traffic jam) concerning the long-term popularity of EVs.
UR - http://www.scopus.com/inward/record.url?scp=85044076043&partnerID=8YFLogxK
U2 - 10.1109/MCOM.2018.1700210
DO - 10.1109/MCOM.2018.1700210
M3 - Article
AN - SCOPUS:85044076043
VL - 56
SP - 150
EP - 156
JO - IEEE Communications Magazine
JF - IEEE Communications Magazine
SN - 0163-6804
IS - 3
ER -
