Waiting Time Minimized Charging and Discharging Strategy Based on Mobile Edge Computing Supported by Software-Defined Network

Research output: Contribution to journalArticlepeer-review

56 Scopus citations

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.

Original languageEnglish
Article number8930011
Pages (from-to)6088-6101
Number of pages14
JournalIEEE Internet of Things Journal
Volume7
Issue number7
DOIs
StatePublished - Jul 2020

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • Charging and discharging
  • minimizing maximal waiting time (MMWT)
  • mobile edge computing (MEC)
  • software-defined network (SDN)

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