Beamforming Scheme for MIMO Relay Based 5G and beyond Wireless Network

Ali, Ali Mahamoud; Adoum, Bakhit Amine; Bachar, Idriss Saleh; Khayal, Mahamoud Youssouf

doi:10.4236/ojapps.2021.1110087

Cited by 1 publication

(1 citation statement)

References 29 publications

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“…Edge computing deploys computing, storage and other resources at the network edge to meet some applications that are demanding on delay [1,2]. The user equipment can unload the computing multi-objective tasks to the edge server for execution in whole or in part through the wireless network, thereby reducing delay and local energy consumption [3,4], thus obtaining a good user experience. Low voltage substation area refers to the low voltage power supply area of transformer, which provides data basis for distribution network management.…”

Section: Introductionmentioning

confidence: 99%

Multi objective task resource allocation method based on hierarchical Bayesian adaptive sparsity for edge computing in low voltage stations

Liu

Bofeng

2023

IET Cyber-Phy Sys Theory & Ap

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In order to achieve more efficient and optimised resource scheduling, this research carried out a multi‐objective task resource allocation method for low‐voltage station edge computing based on hierarchical Bayesian adaptive sparsity. Based on hierarchical Bayesian adaptive sparsity, the multi‐objective task resource allocation technical framework for edge computing in low‐voltage stations is established, which is composed of end pipe edge cloud; After collecting real‐time operation data of power distribution equipment, substation terminals, transmission terminals, etc. in the architecture end, it is transmitted to the data middle platform and service middle platform of the Internet of Things management platform in the cloud through the edge Internet of Things agent; Set and solve the constraint conditions, and build a multi type flexible load hierarchical optimal allocation model; The abnormal area topology identification sub module of multi‐objective task resource of low‐voltage station area edge computing is used to identify the abnormal area topology of the current low‐voltage station area; Taking it as input, the multi‐objective task resources of edge computing are allocated, and the multi‐objective task resources allocation method of edge computing in low pressure platform area is realized under the differential evolution algorithm. The experimental results show that the proposed method has good convergence effect, strong distribution ability, relatively gentle increase in energy consumption, and the calculated results are basically consistent with the actual values, with good effectiveness.

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