Discovering the network backbone from traffic activity data

Sanjay Chawla, Kiran Garimella, Aristides Gionis, Dominic Tsang

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

1 Citation (Scopus)

Abstract

We introduce a new computational problem, the BACKBONE-DISCOVERY problem, which encapsulates both functional and structural aspects of network analysis. While the topology of a typical road network has been available for a long time (e.g., through maps), it is only recently that fine-granularity functional (activity and usage) information about the network (like source-destination traffic information) is being collected and is readily available. The combination of functional and structural information provides an efficient way to explore and understand usage patterns of networks and aid in design and decision making. We propose efficient algorithms for the BACKBONEDISCOVERY problem including a novel use of edge centrality. We observe that for many real world networks, our algorithm produces a backbone with a small subset of the edges that support a large percentage of the network activity.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages409-422
Number of pages14
Volume9651
ISBN (Print)9783319317526
DOIs
Publication statusPublished - 2016
Event20th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2016 - Auckland, New Zealand
Duration: 19 Apr 201622 Apr 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9651
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other20th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2016
CountryNew Zealand
CityAuckland
Period19/4/1622/4/16

Fingerprint

Backbone
Traffic
Electric network analysis
Set theory
Decision making
Centrality
Road Network
Topology
Network Analysis
Network Algorithms
Granularity
Percentage
Efficient Algorithms
Decision Making
Subset

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Chawla, S., Garimella, K., Gionis, A., & Tsang, D. (2016). Discovering the network backbone from traffic activity data. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9651, pp. 409-422). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9651). Springer Verlag. https://doi.org/10.1007/978-3-319-31753-3_33

Discovering the network backbone from traffic activity data. / Chawla, Sanjay; Garimella, Kiran; Gionis, Aristides; Tsang, Dominic.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 9651 Springer Verlag, 2016. p. 409-422 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9651).

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

Chawla, S, Garimella, K, Gionis, A & Tsang, D 2016, Discovering the network backbone from traffic activity data. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 9651, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9651, Springer Verlag, pp. 409-422, 20th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2016, Auckland, New Zealand, 19/4/16. https://doi.org/10.1007/978-3-319-31753-3_33
Chawla S, Garimella K, Gionis A, Tsang D. Discovering the network backbone from traffic activity data. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 9651. Springer Verlag. 2016. p. 409-422. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-319-31753-3_33
Chawla, Sanjay ; Garimella, Kiran ; Gionis, Aristides ; Tsang, Dominic. / Discovering the network backbone from traffic activity data. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 9651 Springer Verlag, 2016. pp. 409-422 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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