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A survey of intelligent network slicing management for industrial IoT: Integrated approaches for smart transportation, smart energy, and smart factory
Network slicing has been widely agreed as a promising technique to accommodate diverse
services for the Industrial Internet of Things (IIoT). Smart transportation, smart energy, and …
services for the Industrial Internet of Things (IIoT). Smart transportation, smart energy, and …
Edge-cloud architectures for hybrid energy management systems: a comprehensive review
This article provides an overview of recent research on edge-cloud architectures in hybrid
energy management systems (HEMSs). It delves into the typical structure of an IoT system …
energy management systems (HEMSs). It delves into the typical structure of an IoT system …
[HTML][HTML] Edge intelligence in Smart Grids: A survey on architectures, offloading models, cyber security measures, and challenges
The rapid development of new information and communication technologies (ICTs) and the
deployment of advanced Internet of Things (IoT)-based devices has led to the study and …
deployment of advanced Internet of Things (IoT)-based devices has led to the study and …
Integration of ICN and MEC in 5G and beyond networks: Mutual benefits, use cases, challenges, standardization, and future research
Multi-access Edge Computing (MEC) is a novel edge computing paradigm that moves
cloudbased processing and storage capabilities closer to mobile users by implementing …
cloudbased processing and storage capabilities closer to mobile users by implementing …
Dynamic federated learning for GMEC with time-varying wireless link
S Zhai, X **, L Wei, H Luo, M Cao - IEEE Access, 2021 - ieeexplore.ieee.org
Smart grid applications, such as predicting energy consumption, grid user behavior analysis
and predicting energy theft, etc., are data-driven applications that require machine learning …
and predicting energy theft, etc., are data-driven applications that require machine learning …
Power flow adjustment for smart microgrid based on edge computing and multi-agent deep reinforcement learning
In current power grids, a massive amount of power equipment raises various emerging
requirements, eg, data perception, information transmission, and real-time control. The …
requirements, eg, data perception, information transmission, and real-time control. The …
Edge computing application in smart grid-a review
M Anuradha - 2021 Second International Conference on …, 2021 - ieeexplore.ieee.org
The exponential demand for power has led to serious concerns related to reliability and
efficiency when transporting power to far-flung areas. The power grid is an essential …
efficiency when transporting power to far-flung areas. The power grid is an essential …
Edge computing supported fault indication in smart grid
P Raussi, J Kilpi… - … for Smart Grids …, 2022 - ieeexplore.ieee.org
The distribution of smart grid applications to different physical devices not interconnected
with physical sensors has opened the possibility for software virtualization allowing flexible …
with physical sensors has opened the possibility for software virtualization allowing flexible …
Cossimulação de Interconexão entre Redes Elétricas Inteligentes e Plataforma de Cidades Inteligentes via Comunicação Massiva do Tipo Máquina-Máquina
LHN Rodrigues, CFM Almeida - 2023 XV Brazilian Conference …, 2023 - ieeexplore.ieee.org
Com o advento da Indústria 5.0 o setor elétrico foi contemplado com dispositivos
inteligentes que impulsionam uma elevada penetração da microgeração de energia …
inteligentes que impulsionam uma elevada penetração da microgeração de energia …
Communicating smart grid demand response and control data through LTE network related solutions
J Markkula - 2023 - oulurepo.oulu.fi
A smart grid (SG) is a modernized electrical grid utilizing new electronic information,
communications, and control technologies. The smart grid enables the efficient use of …
communications, and control technologies. The smart grid enables the efficient use of …