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Online and stochastic survivable network design
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Annual ACM Symposium on Theory of Computing archive
Proceedings of the 41st annual ACM symposium on Theory of computing table of contents
Bethesda, MD, USA
SESSION: Approximation algorithms II table of contents
Pages 685-694  
Year of Publication: 2009
ISBN:978-1-60558-506-2
Authors
Anupam Gupta  Carnegie Mellon University, Pittsburgh, PA, USA
Ravishankar Krishnaswamy  Carnegie Mellon University, Pittsburgh, PA, USA
R. Ravi  Carnegie Mellon University, Pittsburgh, PA, USA
Sponsors
SIGACT: ACM Special Interest Group on Algorithms and Computation Theory
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

Consider the edge-connectivity survivable network design problem: given a graph G = (V,E) with edge-costs, and edge-connectivity requirements rij for every pair of vertices i,j, find an (approximately) minimum-cost network that provides the required connectivity. While this problem is known to admit good approximation algorithms in the offline case, no algorithms were known for this problem in the online setting.

In this paper, we give a randomized O(rmax log3 n) competitive online algorithm for this edge-connectivity network design problem, where rmax = maxij rij. Our algorithms use the standard embeddings of graphs into random subtrees (i.e., into singly connected subgraphs) as an intermediate step to get algorithms for higher connectivity.

Our results for the online problem give us approximation algorithms that admit strict cost-shares with the same strictness value. This, in turn, implies approximation algorithms for (a) the rent-or-buy version and (b) the (two-stage) stochastic version of the edge-connected network design problem with independent arrivals. For these two problems, if we are in the case when the underlying graph is complete and the edge-costs are metric (i.e., satisfy the triangle inequality), we improve our results to give O(1)-strict cost shares, which gives constant-factor rent-or-buy and stochastic algorithms for these instances.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Anupam Gupta: colleagues
Ravishankar Krishnaswamy: colleagues
R. Ravi: colleagues