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Adaptive LRFU replacement policy for named data network in industrial IoTopen access

Authors
Putra, Made Adi ParamarthaKim, Dong-SeongLee, Jae-Min
Issue Date
Jun-2022
Publisher
ELSEVIER
Keywords
Adaptive LRFU; Content caching; Industrial IoT; NDN replacement policy; Deep Learning (DL) approach [2-4]
Citation
ICT EXPRESS, v.8, no.2, pp 258 - 263
Pages
6
Journal Title
ICT EXPRESS
Volume
8
Number
2
Start Page
258
End Page
263
URI
https://scholarworks.bwise.kr/kumoh/handle/2020.sw.kumoh/21311
DOI
10.1016/j.icte.2021.10.004
ISSN
2405-9595
2405-9595
Abstract
In this paper, an adaptive least recently frequently used (LRFU) replacement policy is proposed for named data network (NDN) in the industrial internet of things (IIoT) environment. Low-latency network communication has become the main focus in IIoT development. By applying NDN architecture with the proposed replacement policy, the system can minimize the network latency of IIoT due to the NDN router's capabilities to cache content. The simulation result shows that the proposed adaptive LRFU outperforms other popular replacement policies based on various network performances metrics. In addition, future research trends regarding the testbed implementation NDN replacement policy are suggested. (C) 2021 The Authors. Published by Elsevier B.V. on behalf of The Korean Institute of Communications and Information Sciences. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
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