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.
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References
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
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
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)
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
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
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)
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
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)
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
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
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)
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)
Kong, L., et al.: Data loss and reconstruction in wireless sensor networks. IEEE Transactions on Parallel and Distributed Systems (2013)
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)
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)
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
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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
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DOI: https://doi.org/10.1007/978-981-97-0834-5_12
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