2019
DOI: 10.3934/amc.2019026
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Exponential generalised network descriptors

Abstract: In communication networks theory the concepts of networkness and network surplus have recently been defined. Together with transmission and betweenness centrality, they were based on the assumption of equal communication between vertices. Generalised versions of these four descriptors were presented, taking into account that communication between vertices u and v is decreasing as the distance between them is increasing. Therefore, we weight the quantity of communication by λ d (u,v) where λ ∈ 0, 1 . Extremal … Show more

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Cited by 1 publication
(3 citation statements)
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“…It can be easily seen that i) is obtained for the sequence (n − 1, 0, ..., 0), ii) for the sequence (2, ..., 2) and iii) for the sequence (2, ..., 2, 1). Moreover, it can be easily seen that T n (2, ..., 2) > T n (n − 1, 0, ..., 0) if and only if α ≥ 4 3+n , and that T n (2, ..., 2, 1) > T n (n − 1, 0, ..., 0) if and only if α ≥ 4n−12 n 2 −8 . Hence, it is sufficient to prove that for all n:…”
Section: Results -Lower and Upper Boundsmentioning
confidence: 99%
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“…It can be easily seen that i) is obtained for the sequence (n − 1, 0, ..., 0), ii) for the sequence (2, ..., 2) and iii) for the sequence (2, ..., 2, 1). Moreover, it can be easily seen that T n (2, ..., 2) > T n (n − 1, 0, ..., 0) if and only if α ≥ 4 3+n , and that T n (2, ..., 2, 1) > T n (n − 1, 0, ..., 0) if and only if α ≥ 4n−12 n 2 −8 . Hence, it is sufficient to prove that for all n:…”
Section: Results -Lower and Upper Boundsmentioning
confidence: 99%
“…As this is not a case in real life networks we searched for a descriptor which amends this problem and gives a more realistic representation of the actual communication dynamic in the network. In the paper [3] we presented one way of fixing this by defining a generalized version of the observed descriptors, where the amount of communication was weighted by d(u, v) λ , for λ < 0, and in paper [4] by weighting the amount of communication by λ d (u,v) , for λ ∈ 0, 1 .…”
Section: Introductionmentioning
confidence: 99%
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