Adaptive LRFU replacement policy for named data network in industrial IoT
DC Field | Value | Language |
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dc.contributor.author | Putra, Made Adi Paramartha | - |
dc.contributor.author | Kim, Dong-Seong | - |
dc.contributor.author | Lee, Jae-Min | - |
dc.date.accessioned | 2022-08-16T01:40:05Z | - |
dc.date.available | 2022-08-16T01:40:05Z | - |
dc.date.issued | 2022-06 | - |
dc.identifier.issn | 2405-9595 | - |
dc.identifier.issn | 2405-9595 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/kumoh/handle/2020.sw.kumoh/21311 | - |
dc.description.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/). | - |
dc.format.extent | 6 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | ELSEVIER | - |
dc.title | Adaptive LRFU replacement policy for named data network in industrial IoT | - |
dc.type | Article | - |
dc.publisher.location | 네델란드 | - |
dc.identifier.doi | 10.1016/j.icte.2021.10.004 | - |
dc.identifier.wosid | 000810442900018 | - |
dc.identifier.bibliographicCitation | ICT EXPRESS, v.8, no.2, pp 258 - 263 | - |
dc.citation.title | ICT EXPRESS | - |
dc.citation.volume | 8 | - |
dc.citation.number | 2 | - |
dc.citation.startPage | 258 | - |
dc.citation.endPage | 263 | - |
dc.type.docType | Article | - |
dc.description.isOpenAccess | Y | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.description.journalRegisteredClass | kci | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Telecommunications | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Information Systems | - |
dc.relation.journalWebOfScienceCategory | Telecommunications | - |
dc.subject.keywordAuthor | Adaptive LRFU | - |
dc.subject.keywordAuthor | Content caching | - |
dc.subject.keywordAuthor | Industrial IoT | - |
dc.subject.keywordAuthor | NDN replacement policy | - |
dc.subject.keywordAuthor | Deep Learning (DL) approach [2-4] | - |
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