4.7 Article

FOG COMPUTING FOR SMART GRID SYSTEMS IN THE 5G ENVIRONMENT: CHALLENGES AND SOLUTIONS

期刊

IEEE WIRELESS COMMUNICATIONS
卷 26, 期 3, 页码 47-53

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/MWC.2019.1800356

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资金

  1. National Funding from the FCT - Fundacao para a Ciencia e a Tecnologia [UID/EEA/50008/2019]
  2. Finep under the Centro de Referencia em Radiocomunicacoes - CRR project of the Instituto Nacional de Telecomunicacoes (Inatel), Brazil [01.14.0231.00]
  3. Brazilian National Council for Research and Development (CNPq) [309335/2017-5]
  4. Finatel through the Inatel Smart Campus project

向作者/读者索取更多资源

Currently, the demand for electricity is increasing day by day, which necessitates upgrading of the existing power grid system. The conventional power grid has already been replaced with modern ICT-based infrastructure, which is known as smart grid (SG). In SG, smart meters generate a huge amount of data, and it is a challenging task to store, process, and analyze the data, which varies with respect to volume, velocity, and variety. The data generated in an SG system is generally stored and analyzed using cloud computing (CC), which provides real-time response for various applications. However, to handle the latency issue during the data analytics in SG, fog computing (FC) has emerged as a new technology that provides most of the computing resources in proximity of the end users. It acts as a bridge between SG and CC to fill the gap between processing power of remote data centers and smart devices in SG systems. To handle the aforementioned issues, there is a requirement to set up advanced sensors and measurement systems having communication network backbones in the upcoming fifth generation (5G). In this article, we discuss the architecture of SG in the context of FC for making the decision about energy requirements by the smart devices at the fog layer. Moreover, the communication and computing aspects are also explored in the context of 5G network infrastructure. We examine the influence of FC on response time, transmission delay, and energy management costs for delay-sensitive applications.

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