Betweenness centrality in sparse real world and wireless multi-hop networks

dc.authorscopusid57261535600
dc.authorscopusid55612037400
dc.contributor.authorTuzcu, Atakan
dc.contributor.authorArslan, Hilal
dc.date.accessioned2022-02-15T16:58:49Z
dc.date.available2022-02-15T16:58:49Z
dc.date.issued2022
dc.departmentBakırçay Üniversitesien_US
dc.descriptionInternational Conference on Intelligent and Fuzzy Systems, INFUS 2021 -- 24 August 2021 through 26 August 2021 -- -- 264409en_US
dc.description.abstractGraphs are one of the compact ways to represent information about real-life and intelligent system networks like wireless sensor networks. Betweenness centrality is an important network measure that evaluates the significance of a node based on the shortest paths and is widely used in biological, social, transportation, complex, and communication networks. In this study, we implement an efficient algorithm computing betweenness centrality of nodes for real-world and wireless multi-hop networks. Large sparse graphs are stored using compressed sparse row storage format and modified version of Dijkstra’s algorithm is used to compute shortest paths. We conduct a comprehensive experimental study on real-world networks as well as wireless sensor networks that are state-of-the-art technologies for different applications such as intelligence structures, industrial and home automation as well as health care. We evaluate the effect of network dimension on the time needed to compute betweenness centrality. Experimental results demonstrate that computation time required to compute betweenness centrality varies from 0.9 to 52.5 s when the number of vertices changes from 10,000 to 60,000. We also observe that the proposed algorithm efficiently computes betweenness centrality for networks coming from machine learning, power network, and networks obtained from optimization problems as well as computational fluid dynamics. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.en_US
dc.description.sponsorshipWe would like to express our appreciation to Furkan Nehir for his help and concern during implementations.en_US
dc.identifier.doi10.1007/978-3-030-85626-7_27
dc.identifier.endpage224en_US
dc.identifier.isbn9783030856250
dc.identifier.issn2367-3370
dc.identifier.scopus2-s2.0-85115050065en_US
dc.identifier.scopusqualityQ4en_US
dc.identifier.startpage217en_US
dc.identifier.urihttps://doi.org/10.1007/978-3-030-85626-7_27
dc.identifier.urihttps://hdl.handle.net/20.500.14034/471
dc.identifier.volume307en_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSpringer Science and Business Media Deutschland GmbHen_US
dc.relation.journalLecture Notes in Networks and Systemsen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectBetweenness centralityen_US
dc.subjectShortest pathsen_US
dc.subjectSparse networksen_US
dc.subjectWireless multi-hop networksen_US
dc.titleBetweenness centrality in sparse real world and wireless multi-hop networksen_US
dc.typeConference Objecten_US

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