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Erschienen in: Artificial Intelligence Review 7/2022

18.02.2022

When CCN meets MCGDM: optimal cache replacement policy achieved by PRSRV with Pythagorean fuzzy set pair analysis

verfasst von: Xindong Peng, Haihui Huang, Zhigang Luo

Erschienen in: Artificial Intelligence Review | Ausgabe 7/2022

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Abstract

Cache replacement policy (CRP) in content-centric network (CCN) can reduce cache redundancy, optimize cache utility, and improve network performance. When assessing the CRPs in CCN, it is often full of great uncertainty. Set pair analysis (SPA) is a pioneering uncertainty theory, which consists of three components of the connection number (CN), and overlaps with Pythagorean fuzzy set. The goal of this article is to concentrate on multi-criteria group decision-making (MCGDM) method under Pythagorean fuzzy SPA environment. For it, some revised Pythagorean fuzzy aggregation operators are given for integrating multiple group information as one. Then, the CN has been constructed, and the distance measure between CNs is proposed. Later, the CN score function based distance measure is introduced for dealing with the comparison issue. In addition, the combined weight determining method by fusing the subjective weight preference and objective weight technology (water-filling theory) is shown. Subsequently, the PRSRV MCGDM approach fusing with aggregation operator, distance measure, score function and combined weight is developed for evaluating CRPs. In the end, a comparison with some existing approaches indicates that the developed approach has strong data adaptability.

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Metadaten
Titel
When CCN meets MCGDM: optimal cache replacement policy achieved by PRSRV with Pythagorean fuzzy set pair analysis
verfasst von
Xindong Peng
Haihui Huang
Zhigang Luo
Publikationsdatum
18.02.2022
Verlag
Springer Netherlands
Erschienen in
Artificial Intelligence Review / Ausgabe 7/2022
Print ISSN: 0269-2821
Elektronische ISSN: 1573-7462
DOI
https://doi.org/10.1007/s10462-022-10139-y

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