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dc.contributor.authorTereshchenko, Vasyl
dc.contributor.authorChudakov, Semen
dc.contributor.editorSkala, Václav
dc.date.accessioned2020-07-27T10:45:15Z
dc.date.available2020-07-27T10:45:15Z
dc.date.issued2020
dc.identifier.citationWSCG 2020: full papers proceedings: 28th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision, p. 56-62.en
dc.identifier.isbn978-80-86943-35-0
dc.identifier.issn2464–4617 (print)
dc.identifier.issn2464–4625 (CD-ROM)
dc.identifier.urihttp://wscg.zcu.cz/WSCG2020/2020-CSRN-3001.pdf
dc.identifier.urihttp://hdl.handle.net/11025/38451
dc.format7 s.cs
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.publisherVáclav Skala - UNION Agencycs
dc.relation.ispartofseriesWSCG 2020: full papers proceedingsen
dc.rights© Václav Skala - UNION Agencycs
dc.subjectsjednocená struktura datcs
dc.subjectsimulační problémcs
dc.subjectsada vzájemně propojených problémůcs
dc.subjectjednotné algoritmické prostředícs
dc.subjectspojitelná frontacs
dc.titleApplication of concatenable queue for parallel computational geometry algorithmsen
dc.typeconferenceObjecten
dc.typekonferenční příspěvekcs
dc.rights.accessopenAccessen
dc.type.versionpublishedVersionen
dc.description.abstract-translatedThis paper is devoted to the development of an algorithmic model that solves a set of interrelated computational geometry problems efficiently. To do this, an algorithmic environment with a unified data structure is created, which allows to implement complex use cases efficiently with respect to required computational resources. We build the environment based on the “divide and conquer” strategy. Once a convex hull is a key to a set of computational geometry problems, we offer a concatenable queue data structure to maintain it. The data structure is in the form of a modified balanced binary tree. This allows us to perform operations needed in algorithms for a set of problems in O(log2 n) time. Furthermore we offer a way to execute the algorithms both sequentially and in parallel. In the future the algorithmic environment can be improved to support other computational models with similar properties for solving problems. As an example, the Voronoi diagram or the Delaunay triangulation can be considered.en
dc.subject.translatedunified data structureen
dc.subject.translatedsimulation problemen
dc.subject.translatedinterrelated problems seten
dc.subject.translatedunified algorithmic environmenten
dc.subject.translatedconcatenable queueen
dc.identifier.doihttps://doi.org/10.24132/CSRN.2020.3001.7
dc.type.statusPeer-revieweden
Appears in Collections:WSCG 2020: Full Papers Proceedings

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