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Peer-to-Peer Networking and Applications

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29-06-2023

RIS-assisted device-edge collaborative edge computing for industrial applications

Authors: Mian Guo, Chengyuan Xu, Mithun Mukherjee

Published in: Peer-to-Peer Networking and Applications | Issue 5/2023

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Abstract

In the Industrial Internet of Things (IIoT), a significant amount of perceived data is generated from massive IoT devices, which requires timely computing for value maximization. Multi-access edge computing (MEC), which deploys computing nodes close to the data source, is a promising computing paradigm for IIoT applications. However, due to the limited computation resource, it is challenging for edge nodes to provide a low delay to massive data. In addition, the wireless transmission environment varies with IoT devices over time. Some data even cannot be uploaded to the edge server due to the worse link quality. Reconfigurable intelligent surface (RIS), which deploys passive reflecting elements between end users and base station to reflect wireless signals, is a new technique for changing the wireless transmission performance via reconfiguring the phase shift of RIS. It is beneficial to apply RIS in MEC for reducing transmission delay and achieving green edge computing. This paper considers a RIS-assisted device-edge collaborative MEC for industrial applications. We propose to minimize the energy consumption of IoT devices constrained to the delay requirements via jointly optimizing the offloading decisions between end and edge computing nodes, the phase shift of RIS, CPU resource allocation of edge server, and transmission power of IoT devices. A distributed and cooperative scheme, called RIS-assisted DAEM, which includes the DAECO and DCEM algorithms for CO and PORA subproblems, respectively, is proposed to solve the formulated problem. The simulation results have illustrated the efficiency of the proposal for energy consumption reduction constrained to the delay requirements.

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Title: RIS-assisted device-edge collaborative edge computing for industrial applications
Authors: Mian Guo
Chengyuan Xu
Mithun Mukherjee
Publication date: 29-06-2023
Publisher: Springer US
Published in: Peer-to-Peer Networking and Applications / Issue 5/2023
Print ISSN: 1936-6442
Electronic ISSN: 1936-6450
DOI: https://doi.org/10.1007/s12083-023-01522-9

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