Hybrid Centrality Measures for Service Coverage Problem

Singh, Anuj Kumar; Singh, Rishi Ranjan; Iyengar, S. R. S.

doi:10.1007/978-3-030-34980-6_11

Cited by 2 publications

(1 citation statement)

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“…It is an expanded and extended version of the results that appeared in CSoNet 2019 [1]. The conference version titled "Hybrid Centrality Measures for Service Coverage Problem" discussed a hybridization of centrality measures to solve Service Coverage problem based on the formulation for node-weighted centrality measures.…”

Section: Communication Network: In Communication Network Nodes Arementioning

confidence: 99%

Node-weighted centrality: a new way of centrality hybridization

Singh

Iyengar

2020

Comput Soc Netw

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Centrality measures have been proved to be a salient computational science tool for analyzing networks in the last two to three decades aiding many problems in the domain of computer science, economics, physics, and sociology. With increasing complexity and vividness in the network analysis problems, there is a need to modify the existing traditional centrality measures. Weighted centrality measures usually consider weights on the edges and assume the weights on the nodes to be uniform. One of the main reasons for this assumption is the hardness and challenges in mapping the nodes to their corresponding weights. In this paper, we propose a way to overcome this kind of limitation by hybridization of the traditional centrality measures. The hybridization is done by taking one of the centrality measures as a mapping function to generate weights on the nodes and then using the node weights in other centrality measures for better complex ranking.

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Section: Communication Network: In Communication Network Nodes Arementioning

confidence: 99%