[go: up one dir, main page]
More Web Proxy on the site http://driver.im/ Skip to main content
Log in

Non-adaptive group testing on graphs with connectivity

  • Published:
Journal of Combinatorial Optimization Aims and scope Submit manuscript

Abstract

Group testing refers to any procedure which groups arbitrary subsets of items into pools, and then tests each pool to identify the “sparse” defective items. This paper focuses on a probing scheme in non-adaptive group testing with graph-based constraints. Assume that all nodes function properly but there is at most one failed edge in an undirected graph. By sending probing signals in diagnosis process, we try to know if there is any edge failed, and if there is, to identify the failed edge. Each probing set is allowed only if the induced subgraph by the set is connected. The objective of this model is to identify the failed edge by the fewest possible probes. This paper gives a deterministic optimal probing scheme for complete graphs, and an essentially optimal probing scheme for torus grid graphs.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
£29.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (United Kingdom)

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  • Cheraghchi M, Karbasi A, Mohajer S, Saligrama V (2012) Graph-constrained group testing. IEEE Trans Inf Theory 58:248–262

    Article  MathSciNet  MATH  Google Scholar 

  • Du DZ, Hwang FK (2006) Pooling designs and nonadaptive group testing: important tools for DNA sequencing, vol 18. Series on applied mathematics. World Scientific Publishing Co. Pte. Ltd., Hackensack

    MATH  Google Scholar 

  • D’yachkov AG, Rykov VV (1982) Bounds for the length of disjunctive codes. Probl Inf Transm 18:7–13

    MathSciNet  MATH  Google Scholar 

  • Harvey NJ, Patrascu M, Wen Y, Yekhanin S, Chan VW (2007) Non-adaptive fault diagnosis for all-optical networks via combinatorial group testing on graphs. In: Proceedings of the IEEE INFOCOM 2007—26th IEEE international conference on computer communications, pp 697–705

  • Karbasi A, Zadimoghaddam M (2012) Sequential group testing with graph constraints. In: 2012 IEEE information theory workshop, pp 292–296

  • Kautz W, Singleton R (1964) Nonrandom binary superimposed codes. IEEE Trans Inf Theory 10:363–377

    Article  MATH  Google Scholar 

  • Li CS, Ramaswami R (1997) Automatic fault detection, isolation, and recovery in transparent all-optical networks. J Lightwave Technol 15:1784–1793

    Article  Google Scholar 

  • Mas C, Tomkos I, Tonguz OK (2005) Failure location algorithm for transparent optical networks. IEEE J Sel Areas Commun 23:1508–1519

    Article  Google Scholar 

  • Tapolcai J, Ronyai L, Ho PH (2010) Optimal solutions for single fault localization in two dimensional lattice networks. In: 2010 Proceedings IEEE INFOCOM, pp 1–5

  • Ufimtsev V, Bhowmick S (2013) Application of group testing in identifying high betweenness centrality vertices in complex networks. In: Proceedings of eleventh workshop on mining and learning with graphs

  • Wen Y, Chan VWS, Zheng L (2005) Efficient fault-diagnosis algorithms for all-optical wdm networks with probabilistic link failures. J Lightwave Technol 23:3358–3371

    Article  Google Scholar 

  • Wu B, Yeung KL (2007) Monitoring cycle design for fast link failure detection in all-optical networks. In: IEEE GLOBECOM 2007—IEEE global telecommunications conference, pp 2315–2319

  • Zeng H, Huang C, Vukovic A (2006) A novel fault detection and localization scheme for mesh all-optical networks based on monitoring-cycles. Photonic Netw Commun 11:277–286

    Article  Google Scholar 

Download references

Acknowledgements

The authors express their gratitude to the two anonymous reviewers for their detailed and constructive comments which are very helpful to the improvement of the presentation of this paper. This research is supported in part by the JSPS Grant-in-Aid for Scientific Research (B) under Grant Nos. 18H01133 and 16H03118.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Maiko Shigeno.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Luo, S., Matsuura, Y., Miao, Y. et al. Non-adaptive group testing on graphs with connectivity. J Comb Optim 38, 278–291 (2019). https://doi.org/10.1007/s10878-019-00379-0

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10878-019-00379-0

Keywords

Navigation