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Accelerating the Kamada-Kawai Algorithm for Boundary Detection in a Mobile Ad Hoc Network
SE-HANG CHEONG; YAIN-WHAR SI
2017-02
Source PublicationACM Transactions on Sensor Networks
ISSN1550-4859
Volume13Issue:1
Abstract

Force-directed algorithms such as the Kamada-Kawai algorithm have shown promising results for solving the boundary detection problem in a mobile ad hoc network. However, the classical Kamada-Kawai algorithm does not scale well when it is used in networks with large numbers of nodes. It also produces poor results in non-convex networks. To address these problems, this article proposes an improved version of the Kamada-Kawai algorithm. The proposed extension includes novel heuristics and algorithms that achieve a faster energy level reduction. Our experimental results show that the improved algorithm can significantly shorten the processing time and detect boundary nodes with an acceptable level of accuracy.

KeywordKamada-kawai Boundary Detection Force-directed Algorithm
DOI10.1145/3005718
URLView the original
Indexed BySCIE
Language英語English
WOS Research AreaComputer Science ; Telecommunications
WOS SubjectComputer Science, Information Systems ; Telecommunications
WOS IDWOS:000395847800003
PublisherASSOC COMPUTING MACHINERY
The Source to ArticleWOS
Scopus ID2-s2.0-85008163170
Fulltext Access
Citation statistics
Document TypeJournal article
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
AffiliationUniversity of Macau
First Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
SE-HANG CHEONG,YAIN-WHAR SI. Accelerating the Kamada-Kawai Algorithm for Boundary Detection in a Mobile Ad Hoc Network[J]. ACM Transactions on Sensor Networks, 2017, 13(1).
APA SE-HANG CHEONG., & YAIN-WHAR SI (2017). Accelerating the Kamada-Kawai Algorithm for Boundary Detection in a Mobile Ad Hoc Network. ACM Transactions on Sensor Networks, 13(1).
MLA SE-HANG CHEONG,et al."Accelerating the Kamada-Kawai Algorithm for Boundary Detection in a Mobile Ad Hoc Network".ACM Transactions on Sensor Networks 13.1(2017).
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