Skip to main content
SpringerLink
Log in

A Heuristic Approach for Large-Scale Orchestration of the In-band Data Plane Telemetry Problem

  • Conference paper
  • First Online:
Advanced Information Networking and Applications (AINA 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1151))

Abstract

In-band network telemetry (INT) is an emerging network monitoring paradigm aimed to collect data plane telemetry statistics. INT is able to improve network-wide visibility considerably, providing timely discovery of issues such as micro-burst. Previous researches have focused on optimally orchestrating the collection of in-band network telemetry statistics from the network, providing little or none scalability to be applied in realistic environments. In this work, we tackled the scalability limitation of existing approaches by proposing an iterated local search procedure. Results show that our algorithm outperforms state-of-the-art orchestration solutions by a factor of 2 with respect to the number monitoring applications requirements satisfied, while keeping the solution close to the optimum (less than 5%) – demanding a few seconds to execute.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    For instance: Barefoot Advanced Network Telemetry and Broadcom Trident 3.

  2. 2.

    In-band Network Telemetry: https://p4.org/assets/INT-current-spec.pdf.

References

  1. Albert, R., Barabasi, A.L.: Topology of evolving networks: local events and universality. Phys. Rev. Lett. 85, 5234–5237 (2000)

    Article  Google Scholar 

  2. Cisco: (2018). https://www.cisco.com/c/en/us/solutions/service-provider/cloud-scale-networking-solutions/model-driven-telemetry.html

  3. Feo, T.A., Resende, M.G.C.: Greedy randomized adaptive search procedures. J. Glob. Optim. 6(2), 109–133 (1995)

    Article  MathSciNet  Google Scholar 

  4. Gupta, A., Harrison, R., Canini, M., Feamster, N., Rexford, J., Willinger, W.: Sonata: query-driven streaming network telemetry. In: Proceedings of ACM SIGCOMM 2018. ACM, New York, USA (2018)

    Google Scholar 

  5. Hohemberger, R., Castro, A.G., Vogt, F.G., Mansilha, R.B., Lorenzon, A.F., Rossi, F.D., Luizelli, M.C.: Orchestrating in-band data plane telemetry with machine learning. IEEE Commun. Lett. 23(12), 2247–2251 (2019)

    Article  Google Scholar 

  6. Jeyakumar, V., Alizadeh, M., Geng, Y., Kim, C., Mazières, D.: Millions of little minions: using packets for low latency network programming and visibility. In: Proceedings of the ACM SIGCOMM 2014, pp. 3–14. ACM, New York, USA (2014)

    Google Scholar 

  7. Liu, Z., Bi, J., Zhou, Y., Wang, Y., Lin, Y.: Netvision: towards network telemetry as a service. In: 2018 IEEE 26th International Conference on Network Protocols (ICNP), pp. 247–248, September 2018

    Google Scholar 

  8. Marques, J.A., Luizelli, M.C., Da Costa, R.I.T., Gaspary, L.P.: An optimization-based approach for efficient network monitoring using in-bandnetwork telemetry. J. Internet Serv. Appl. 10(1), 12 (2019)

    Article  Google Scholar 

  9. Medina, A., Lakhina, A., Matta, I., Byers, J.: Brite: an approach to universal topology generation. In: Proceedings of the IEEE MASCOTS, pp. 346–353, August 2001

    Google Scholar 

  10. Pan, T., Song, E., Bian, Z., Lin, X., Peng, X., Zhang, J., Huang, T., Liu, B.,Liu, Y.: INT-path: towards optimal path planning for in-band network-wide telemetry. In: IEEE INFOCOM 2019, pp. 1–9, April 2019

    Google Scholar 

  11. Putina, A., Rossi, D., Bifet, A., Barth, S., Pletcher, D., Precup, C., Nivaggioli, P.: Telemetry-based stream-learning of bgp anomalies. In: Proceedings of the ACM Workshop Big-DAMA 2018, pp. 15–20. ACM, New York, USA (2018)

    Google Scholar 

  12. Tammana, P., Agarwal, R., Lee, M.: Simplifying datacenter network debugging with pathdump. In: 12th USENIX OSDI 16, pp. 233–248, Savannah, GA (2016)

    Google Scholar 

  13. Tammana, P., Agarwal, R., Lee, M.: Distributed network monitoring and debugging with switchpointer. In: 15th USENIX NSDI 18, pp. 453–456, Renton, WA (2018)

    Google Scholar 

  14. Zhu, Y., Kang, N., Cao, J., Greenberg, A., Lu, G., Mahajan, R., Maltz, D., Yuan, L., Zhang, M., Zhao, B.Y., Zheng, H.: Packet-level telemetry in large datacenter networks. In: Proceedings of the ACM SIGCOMM 2015, pp. 479–491. ACM, New York, USA (2015)

    Google Scholar 

Download references

Acknowledgements

This work was partially funded by National Council for Scientific and Technological Development (CNPq 2018/427814), Foundation for Research of the State of Sao Paulo (FAPESP 2018/23092-1), and Foundation for Research of the State of Rio Grande do Sul (19/2551-0001224-1,19/2551-0001266-7).

Author information

Authors and Affiliations

  1. Federal University of Pampa (UNIPAMPA), Alegrete, Brazil

    Arthur Francisco Lorenzon & Marcelo Caggiani Luizelli

  2. Federal Institute Farroupilha (IFFAR), Alegrete, Brazil

    Rumenigue Hohemberger & Fábio Diniz Rossi

Authors
  1. Rumenigue Hohemberger
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Arthur Francisco Lorenzon
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Fábio Diniz Rossi
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Marcelo Caggiani Luizelli
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Marcelo Caggiani Luizelli .

Editor information

Editors and Affiliations

  1. Department of Information and Communication Engineering, Faculty of Information Engineering, Fukuoka Institute of Technology, Fukuoka, Japan

    Leonard Barolli

  2. Department of Electrical Engineering and Information Technology, University of Naples “Frederico II”, Naples, Italy

    Flora Amato

  3. Department of Political Science, University of Campania “Luigi Vanvitelli”, Caserta, Italy

    Francesco Moscato

  4. Faculty of Business Administration, Rissho University, Tokyo, Japan

    Tomoya Enokido

  5. Department of Advanced Sciences, Faculty of Science and Engineering, Hosei University, Tokyo, Japan

    Makoto Takizawa

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Hohemberger, R., Lorenzon, A.F., Rossi, F.D., Luizelli, M.C. (2020). A Heuristic Approach for Large-Scale Orchestration of the In-band Data Plane Telemetry Problem. In: Barolli, L., Amato, F., Moscato, F., Enokido, T., Takizawa, M. (eds) Advanced Information Networking and Applications. AINA 2020. Advances in Intelligent Systems and Computing, vol 1151. Springer, Cham. https://doi.org/10.1007/978-3-030-44041-1_35

Download citation

Publish with us

Policies and ethics

Search

Navigation