Paper Info
Title
Waiting Time Minimized Charging and Discharging Strategy Based on Mobile Edge Computing Supported by Software-Defined Network
Abstract
With the increasing number of electric vehicles (EVs), temporary charging demands grow rapidly. Unlike charging at home or workplace, temporary charging requires less waiting time. In this article, a mobile edge computing (MEC)-enabled charging and discharging networking system algorithm (CDNSA) is proposed to minimize the waiting time for EVs in charging stations (CSs). A software-defined network (SDN) paradigm is adopted to enhance the data transmission efficiency for MEC servers. In CDNSA, the optimization problem is formulated as a mixed-integer nonlinear programming (MINLP). A heuristic algorithm is proposed to solve the optimal CS selection variables for EVs that needs to be charged (EVCs) and EVs that can be discharged (EVDs), and then a remaining problem nonlinear programming (NLP) is obtained. By verifying the convexity of each continuous variable, the NLP is solved by adopting the block coordinate descent (BCD) method. In simulation, the optimality of CDNSA is verified by comparing with the exhaustive algorithm in terms of minimizing maximal waiting time (MMWT) of CSs. We also compare CDNSA with other benchmarks to illustrate its advantage.
Year
DOI
Venue
2020
10.1109/JIOT.2019.2957124
IEEE Internet of Things Journal
Keywords
DocType
Volume
Servers,Electric vehicle charging,Cascading style sheets,Optimal scheduling,Internet of Things,Charging stations,Energy management
Journal
7
Issue
ISSN
Citations 
7
2327-4662
2
PageRank 
References 
Authors
0.39
0
5
Name
Order
Citations
PageRank
Qiang Tang123132.00
Kezhi Wang263741.20
Yun Song362.13
Feng Li492.51
Jonghyuk Park520620.70