Local Fractional Strong Metric Dimension of Certain Complex Networks

Faiza Jamil, Agha Kashif, Sohail Zafar, Michael Onyango Ojiema and Miaomiao Wang

Complexity, 2023, vol. 2023, 1-8

Abstract: Fractional variants of distance-based parameters have application in the fields of sensor networking, robot navigation, and integer programming problems. Complex networks are exceptional networks which exhibit significant topological features and have become quintessential research area in the field of computer science, biology, and mathematics. Owing to the possibility that many real-world systems can be intelligently modeled and represented as complex networks to examine, administer and comprehend the useful information from these real-world networks. In this paper, local fractional strong metric dimension of certain complex networks is computed. Building blocks of complex networks are considered as the symmetric networks such as cyclic networks Cn, circulant networks Cn1,2, mobious ladder networks M2n, and generalized prism networks Gmn. In this regard, it is shown that LSFMD of Cnn≥3 and Gmnn≥6 is 1 when n is even and n/n−1 when n is odd, whereas LSFMD of M2n is 1 when n is odd and n/n−1 when n is even. Also, LSFMD of Cn1,2 is n/2⌈m+1/2⌉ where n≥6 and m=⌈n−5/4⌉.

Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:hin:complx:3635342

DOI: 10.1155/2023/3635342

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