Skip to main content

A Chained Forwarding Mechanism for Large Messages

  • Conference paper
  • First Online:
Algorithms and Architectures for Parallel Processing (ICA3PP 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14487))

  • 98 Accesses

Abstract

The proliferation of wide-bandwidth network services, e.g. high-definition video (HD video), has made the fragmentation mechanism necessary. However, conventional fragmentation mechanisms apply the same treatment to fragmented and unfragmented packets, thus impeding efficiency and impairing the quality of service. To address this issue, we propose a novel chained forwarding mechanism that integrates the typical features of large message transmission. The proposed mechanism is uniquely confined to the data plane, providing seamless chained forwarding capabilities. Specifically, network devices exclusively process the initial fragment, exempting subsequent fragments from further processing. This reduces the processing delay in network devices, attenuating the forwarding latency caused by Access Control List (ACL) and Longest Prefix Match (LPM). Evaluation results based on the P4 simulator show that the proposed chained forwarding mechanism can reduce 10% of the forwarding latency. Furthermore, the mechanism demonstrates substantial scalability and provides significant performance improvements in large-scale networks.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 59.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 79.99
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

References

  1. Yeo, H., Lim, H., Kim, J., Jung, Y., Ye, J., Han, D.: Neuroscaler: Neural video enhancement at scale. In: Proceedings of the ACM SIGCOMM 2022 Conference. New York, NY, USA (2022). https://doi.org/10.1145/3544216.3544218

  2. Cisco: Cisco visual networking index report. Tech. rep. (2022). http://www.cisco.com/c/en/us/solutions/collateral/service-provider/visual-networking-index-vni/complete-white-paper-c11-481360.pdf

  3. Li, J., et al.: Livenet: a low-latency video transport network for large-scale live streaming. In: Proceedings of the ACM SIGCOMM 2022 Conference, pp. 812–825 (2022)

    Google Scholar 

  4. Yang, J., Jiang, Y., Wang, S.: Enhancement or super-resolution: learning-based adaptive video streaming with client-side video processing. In: IEEE International Conference on Communications, vol. 2022-May, pp. 739–744 (2022). https://doi.org/10.1109/ICC45855.2022.9839262

  5. Jin, X., Xia, C., Guan, N., Zeng, P.: Joint algorithm of message fragmentation and no-wait scheduling for time-sensitive networks. IEEE/CAA J. Autom. Sinica 8(2), 478–490 (2021). https://doi.org/10.1109/JAS.2021.1003844

    Article  MathSciNet  Google Scholar 

  6. Bialon, R., Tolkes, J., Graffi, K.: Improving message delivery in opportunistic networks with fragmentation and network coding. In: 2019 International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData) (2019)

    Google Scholar 

  7. Tran Thai, T., Chaganti, V.G., Lochin, E., Lacan, J., Dubois, E., Gelard, P.: Enabling e2e reliable communications with adaptive re-encoding over delay tolerant networks. In: IEEE International Conference on Communications. vol. 2015-September, pp. 928–933 (2015). https://doi.org/10.1109/ICC.2015.7248441

  8. Wang, J., Liao, J., Zhu, X.: On preventing unnecessary fast retransmission with optimal fragmentation strategy. In: IEEE International Conference on Communications, pp. 85–89 (2008)

    Google Scholar 

  9. Dong, L., Liu, H., Zhang, Y., Paul, S., Raychaudhuri, D.: On the cache-and-forward network architecture. In: IEEE International Conference on Communications (2009). https://doi.org/10.1109/ICC.2009.5199249

  10. Fogli, M., Giannelli, C., Stefanelli, C.: Edge-powered in-network processing for content-based message management in software-defined industrial networks. In: IEEE International Conference on Communications. vol. 2022-May, pp. 1438–1443 (2022). https://doi.org/10.1109/ICC45855.2022.9838863

  11. Xi, J., Kong, F., Kong, L., Wei, L., Peng, Z.: Reliability and temporality optimization for multiple coexisting wirelesshart networks in industrial environments. IEEE Trans. Indust. Electron. PP(8), 1–1 (2017)

    Google Scholar 

  12. Tang, J., Shim, B., Quek, T.Q.: Service multiplexing and revenue maximization in sliced c-ran incorporated with urllc and multicast embb. IEEE J. Sel. Areas Commun. 37(4), 881–895 (2019)

    Article  Google Scholar 

  13. Kong, L., et al.: Data loss and reconstruction in wireless sensor networks. IEEE Transactions on Parallel and Distributed Systems (2013)

    Google Scholar 

  14. Saldana, J., Wing, D., Fernandez-Navajas, J., Ruiz-Mas, J., Perumal, M.A.M., Camarillo, G.: Widening the scope of a standard: Real time flows tunneling, compressing and multiplexing. In: IEEE International Conference on Communications, pp. 6906–6910 (2012)

    Google Scholar 

  15. Ma, Z., Bi, J., Zhang, C., Zhou, Y., Dogar, A.B.: Cachep4: a behavior-level caching mechanism for p4. In: ACM Special Interest Group on Data Communication (2017)

    Google Scholar 

  16. Cisco: Cisco annual internet report (2018–2023) white paper. Tech. rep. (2021). https://www.cisco.com/c/en/us/solutions/collateral/executive-perspectives/annual-internet-report/white-paper-c11-741490.html

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Tao Feng .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2024 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Lin, J., Feng, T., Zhou, N., Gao, X., Jiang, S. (2024). A Chained Forwarding Mechanism for Large Messages. In: Tari, Z., Li, K., Wu, H. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2023. Lecture Notes in Computer Science, vol 14487. Springer, Singapore. https://doi.org/10.1007/978-981-97-0834-5_12

Download citation

  • DOI: https://doi.org/10.1007/978-981-97-0834-5_12

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-97-0833-8

  • Online ISBN: 978-981-97-0834-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics