Peng Ji's Blog

Today's work

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调研文献

基于Sketch的流量特征提取

Yang T, Jiang J, Liu P, et al. Elastic Sketch: Adaptive and Fast Network-wide Measurements [C]//ACM SIGCOMM 2018.
Liu Z, Ben-Basat R, Einziger G, et al. NitroSketch: Robust and General Sketch-based Monitoring in Software Switches [C]//ACM SIGCOMM 2019.
Gong J, Yang T, Zhang H, et al. HeavyKeeper: An Accurate Algorithm for Finding Top-k Elephant Flows [C]//USENIX ATC 2018.
Tang L, Huang Q, Lee P P C. MV-Sketch: A Fast and Compact Invertible Sketch for Heavy Flow Detection [C]//IEEE INFOCOM 2019.
Li J, Li Z, Xu Y, et al. WavingSketch: An Unbiased and Generic Sketch for Finding Top-k Items [C]//ACM SIGKDD 2020.
Tang L, Huang Q, Lee P P C. SpreadSketch: Toward Invertible and Network-Wide Detection of Superspreaders [C]//IEEE INFOCOM 2020.
Zhang Y, Liu Z, Wang R, et al. CocoSketch: High-Performance Sketch-based Measurement over Arbitrary Partial Key Query [C]//ACM SIGCOMM 2021.
Li W, Patras P. P-Sketch: A Fast and Accurate Sketch for Persistent Item Lookup [J]. IEEE/ACM Transactions on Networking, 2023.
Liu X, Shao J, et al. PIB Sketch: Accurately Tracking Persistent and Infrequent Flows with Bursty Characteristic [C]//IEEE IPCCC 2024.
Liu Z, Manousis A, Vorsanger G, et al. One Sketch to Rule Them All: Rethinking Network Flow Monitoring with UnivMon [C]//ACM SIGCOMM 2016.
Huang Q, Sun H, Lee P P C, et al. OmniMon: Re-architecting Network Telemetry with Resource Efficiency and Full Accuracy [C]//ACM SIGCOMM 2020; [J] IEEE/ACM ToN 2024.
Sun H, Huang Q, Sun J, et al. AutoSketch: Automatic Sketch-Oriented Compiler for Query-driven Network Telemetry [C]//USENIX NSDI 2024.
Srivastava M, Hung S, et al. Raising the Level of Abstraction for Sketch-Based Network Telemetry with SketchPlan [C]//ACM IMC 2024.
Ding R, Yang S, Chen X, et al. BitSense: Universal and Nearly Zero-Error Optimization for Sketch Counters with Compressive Sensing [C]//ACM SIGCOMM 2023.

高频流量建模与检测

CCF A类 / SCI 一区

  1. **** T. Yang, J. Jiang, P. Liu, Q. Huang, J. Gong, Y. Zhou, R. Miao, X. Li, and S. Uhlig, "Elastic Sketch: Adaptive and Fast Network-wide Measurements," in Proceedings of the 2018 Conference of the ACM Special Interest Group on Data Communication (SIGCOMM), Budapest, Hungary, Aug. 2018, pp. 561–575.
  2. **** Z. Liu, R. Ben-Basat, G. Einziger, Y. Kassner, V. Braverman, R. Friedman, and V. Sekar, "NitroSketch: Robust and General Sketch-based Monitoring in Software Switches," in Proceedings of the ACM Special Interest Group on Data Communication (SIGCOMM), Beijing, China, Aug. 2019, pp. 334–350.
  3. **** Y. Zhang, Z. Liu, R. Wang, T. Yang, J. Li, R. Miao, P. Liu, R. Zhang, and J. Jiang, "CocoSketch: High-Performance Sketch-based Measurement over Arbitrary Partial Key Query," in Proceedings of the ACM SIGCOMM 2021 Conference, Virtual Event, Aug. 2021, pp. 207–222.
  4. **** H. Zhu, V. Gupta, S. S. Ahuja, Y. Tian, Y. Zhang, and X. Jin, "Network Planning with Deep Reinforcement Learning," in Proceedings of the ACM SIGCOMM 2021 Conference, Virtual Event, Aug. 2021, pp. 258–271. (NeuroPlan)
  5. **** D. Tang, Y. Yan, C. Gao, W. Liang, and W. Jin, "LtRFT: Mitigate the Low-Rate Data Plane DDoS Attack With Learning-To-Rank Enabled Flow Tables," IEEE Transactions on Information Forensics and Security (TIFS), vol. 18, pp. 3143–3157, May 2023.
  6. **** M. Ferriol-Galmés, J. Paillisse, J. Suárez-Varela, K. Rusek, S. Xiao, X. Shi, X. Cheng, P. Barlet-Ros, and A. Cabellos-Aparicio, "RouteNet-Fermi: Network Modeling With Graph Neural Networks," IEEE/ACM Transactions on Networking (ToN), vol. 31, no. 6, pp. 3080–3095, Dec. 2023.
  7. **** N. K. Sharma, M. Liu, K. Atreya, and A. Krishnamurthy, "Approximation Algorithms for Network Telemetry in Programmable Devices," IEEE/ACM Transactions on Networking, vol. 29, no. 3, pp. 1184-1197, 2021.
  8. **** G. Duan, H. Lv, H. Wang, G. Feng, and X. Li, "Practical Cyber Attack Detection with Continuous Temporal Graph in Dynamic Network System," IEEE Transactions on Information Forensics and Security, vol. 19, 2024.
  9. **** J. Suárez-Varela, P. Almasan, M. Ferriol-Galmés, K. Rusek, F. Geyer, X. Cheng, X. Shi, S. Xiao, F. Scarselli, A. Cabellos-Aparicio, and P. Barlet-Ros, "Graph Neural Networks for Communication Networks: Context, Use Cases and Opportunities," IEEE Network (Highly cited review related to JSAC specialized topic), vol. 37, no. 3, pp. 146–153, 2022.

CCF B类 / SCI 二区

  1. **** W. Feng, J. Gao, X. Chen, G. Antichi, R. B. Basat, M. M. Shao, Y. Zhang, and M. Yu, "F3: Fast and Flexible Network Telemetry with an FPGA coprocessor," in Proceedings of the ACM on Networking, vol. 2, issue CoNEXT4, Article 25, Dec. 2024.
  2. **** C. Güemes-Palau, M. F. Galmés, J. P. Vilanova, A. L. Brescó, P. Barlet-Ros, and A. Cabellos-Aparicio, "Wavelet-Enhanced Graph Neural Networks: Towards Non-Parametric Network Traffic Modeling," in Proceedings of the 3rd GNNet Workshop on Graph Neural Networking (GNNet@CoNEXT '24), Dec. 2024, pp. 14–19.
  3. **** P. G. Kannan, R. Joshi, and M. C. Chan, "Precise Time-Synchronized Network Debugging in the Data Plane," in 18th USENIX Symposium on Networked Systems Design and Implementation (NSDI 21), Apr. 2021, pp. 261–276. (SyNDB)
  4. **** Y. Liu, J. Han, K. Xue, J. Li, Q. Sun, and J. Lu, "Improving Congestion Control in Data Center Networks With Deep Reinforcement Learning," IEEE Transactions on Network and Service Management, vol. 20, no. 4, 2023.
  5. [ComNet 2025] Y. Tian, Z. Wang, X. Yin, X. Shi, J. Yang, and H. Zhang, "Adaptive traffic engineering with segment routing through deep reinforcement learning," Computer Networks, vol. 267, Article 111356, 2025.
  6. **** D. Shan, F. Ren, P. Cheng, R. Shu, and C. Guo, "Micro-Burst Traffic in Data Centers: Observations, Analysis, and Mitigation," IEEE/ACM Transactions on Networking (also related to TNSM works on microbursts), vol. 28, no. 1, pp. 98–111, 2020.
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