A Distributed Algorithm for Force Directed Edge Bundling

Yves Tuyishime, Yu Pan, Hongfeng Yu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Existing edge bundling algorithms typically require the global information structure of a graph. Therefore, with a simple division of the edges of a graph, it is challenging to conduct edge bundling in a distributed environment and achieve scalable performance. We select a representative edge bundling algorithm, Force-Directed Edge Bundling (FDEB), and parallelize it in a distributed environment. Particularly, to address the difficulties of partitioning and distributions of a large graph among processors, we first create a high dimensional space to represent the data distribution of a graph in FDEB. Second, we map each edge as a data point in this high dimensional space, and then partition and distribute the point cloud among processors. In this way, we can significantly reduce the data communication across processors, and ensure each processor assigned with a similar workload.

Original languageEnglish (US)
Title of host publicationProceedings - 2020 IEEE 10th Symposium on Large Data Analysis and Visualization, LDAV 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages53-54
Number of pages2
ISBN (Electronic)9781728184685
DOIs
StatePublished - Oct 2020
Event10th IEEE Symposium on Large Data Analysis and Visualization, LDAV 2020 - Virtual, Salt Lake City, United States
Duration: Oct 25 2020 → …

Publication series

NameProceedings - 2020 IEEE 10th Symposium on Large Data Analysis and Visualization, LDAV 2020

Conference

Conference10th IEEE Symposium on Large Data Analysis and Visualization, LDAV 2020
CountryUnited States
CityVirtual, Salt Lake City
Period10/25/20 → …

Keywords

  • Graph drawings
  • Human-centered computing
  • Visu-Alization techniques
  • Visualization

ASJC Scopus subject areas

  • Computer Science Applications
  • Information Systems and Management
  • Media Technology

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