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Scalable approximations to k-cycle transversal problems on dynamic networks

  • Alan KuhnleEmail author
  • Victoria G. Crawford
  • My T. Thai
Regular Paper
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Abstract

We study scalable approximation algorithms for the k-cycle transversal problem, which is to find a minimum-size set of edges that intersects all simple cycles of length k in a network. This problem is relevant to network reliability through the important metric of network clustering coefficient of order k. We formulate two algorithms to be both scalable and have good solution quality in practice: CARL and DARC. DARC is able to efficiently update its solution under dynamic node and edge insertion and removal to the network. In our experimental evaluation, we demonstrate that DARC is able to run on networks with billions of 3-cycles within 2 h and is able to dynamically update its solution in microseconds.

Keywords

Dynamic networks Cycle transversal Triangle interdiction Scalable algorithms 

Notes

Acknowledgements

This work was supported in part by NSFCCF-1422116, DTRAHDTRA1-14-1-0055 and NSF EFRI 1441231.

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Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2018

Authors and Affiliations

  1. 1.Computer and Information Science and EngineeringUniversity of FloridaGainesvilleUSA

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