Open AccessResource allocation method based on mobile edge computing in smart grid
Author(s) -
Ningli Qin,
Bo Li,
Da Li,
Xiaosong Jing,
Changyu Du,
Chunyi Wan
Publication year - 2021
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/634/1/012054
Subject(s) - computer science , overhead (engineering) , energy consumption , smart grid , distributed computing , mobile edge computing , enhanced data rates for gsm evolution , efficient energy use , data transmission , resource allocation , computer network , real time computing , server , engineering , telecommunications , operating system , electrical engineering
Mobile edge computing(MEC) refers to offloading the collected data to the mobile edge server, which can calculate data efficiently, further improve the operating efficiency of the smart grid and reduce energy consumption. In the face of increasing data, the spectrum overhead and energy consumption of the network are becoming increasingly severe. Based on this, this paper proposes to use massive multiple input multiple output (MIMO) technology to improve the spectrum and energy efficiency of the system, and proposes a massive MIMO-MEC smart grid system framework. In addition, considering that it is easy to be eavesdropped in the process of offloading data, we propose to use physical layer security technology to ensure user information security. In order to minimize the energy consumption of applications such as smart meters, this paper proposes a sequential iterative optimization algorithm to jointly optimize the offloading rate and transmission power. The simulation results prove that as the number of antennas increases, the transmission rate of the system increases, which reduces the total energy consumption of the system.