Generalized Sketch Families for Network Traffic Measurement

被引:0
|
作者
Zhou Y. [1 ]
Zhang Y. [1 ]
Ma C. [1 ]
Chen S. [1 ]
Odegbile O.O. [1 ]
机构
[1] University of Florida, Gainesville, FL
来源
Performance Evaluation Review | 2020年 / 48卷 / 01期
基金
美国国家科学基金会;
关键词
big network data; generalized sketch families; network traffic measurement;
D O I
10.1145/3393691.3394191
中图分类号
学科分类号
摘要
Traffic measurement provides critical information for network management, resource allocation, traffic engineering, and attack detection. Most prior art has been geared towards specific application needs with specific performance objectives. To support diverse requirements with efficient and future-proof implementation, this paper takes a new approach to establish common frameworks, each for a family of traffic measurement solutions that share the same implementation structure, providing a high level of generality, for both size and spread measurements and for all flows. The designs support many options of performance-overhead tradeoff with as few as one memory update per packet and as little space as several bits per flow on average. Such a family-based approach will unify implementation by removing redundancy from different measurement tasks and support reconfigurability in a plug-n-play manner. We demonstrate the connection and difference in the design of these traffic measurement families and perform experimental comparisons on hardware/software platforms to find their tradeoff, which provide practical guidance for which solutions to use under given performance goals. © 2020 Copyright is held by the owner/author(s).
引用
收藏
页码:63 / 64
页数:1
相关论文
共 50 条
  • [1] Generalized Sketch Families for Network Traffic Measurement
    Zhou, You
    Zhang, Youlin
    Ma, Chaoyi
    Chen, Shigang
    Odegbile, Olufemi O.
    PROCEEDINGS OF THE ACM ON MEASUREMENT AND ANALYSIS OF COMPUTING SYSTEMS, 2019, 3 (03)
  • [2] Prob-CS: A Probabilistic Cuckoo Sketch for Accurate Network Traffic Measurement
    Wang, Chao
    Li, Xu
    Zeng, Jiuzhen
    Yin, Weimin
    Zhou, Ping
    IEEE INTERNET OF THINGS JOURNAL, 2024, 11 (22): : 36965 - 36978
  • [3] Effective Network-Wide Traffic Measurement: A Lightweight Distributed Sketch Deployment
    Li, Fuliang
    Guo, Kejun
    Shen, Jiaxing
    Wang, Xingwei
    IEEE INFOCOM 2024-IEEE CONFERENCE ON COMPUTER COMMUNICATIONS, 2024, : 181 - 190
  • [4] CS-Sketch: Compressive Sensing Enhanced Sketch for Full Traffic Measurement
    Li, Linxi
    Xie, Kun
    Pei, Shuyu
    Wen, Jigang
    Liang, Wei
    Xie, Gaogang
    IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING, 2024, 11 (03): : 2338 - 2352
  • [5] ALSketch: An adaptive learning-based sketch for accurate network measurement under dynamic traffic distribution
    Cheng, Xiaojun
    Jing, Xuyang
    Yan, Zheng
    Li, Xian
    Wang, Pu
    Wu, Wei
    JOURNAL OF NETWORK AND COMPUTER APPLICATIONS, 2023, 216
  • [6] A survey on sliding window sketch for network measurement
    Zeng, Zijie
    Cui, Lin
    Qian, Mimi
    Zhang, Zhen
    Wei, Kaimin
    COMPUTER NETWORKS, 2023, 226
  • [7] Spatial Sketch Configuration for Traffic Measurement in Software Defined Networks
    Yao, Da
    Xu, Hongli
    Wang, Haibo
    Huang, Liusheng
    Tu, Huaqing
    WIRELESS ALGORITHMS, SYSTEMS, AND APPLICATIONS, WASA 2021, PT III, 2021, 12939 : 375 - 389
  • [8] A Sketch Algorithm to Monitor High Packet Delay in Network Traffic
    Zhu, Jiaqi
    Zhang, Kai
    Huang, Qun
    ACM International Conference Proceeding Series, 2021, : 43 - 49
  • [9] A Flexible Sketch-Based Network Traffic Monitoring Infrastructure
    Wellem, Theophilus
    Lai, Yu-Kuen
    Huang, Chao-Yuan
    Chung, Wen Yaw
    IEEE ACCESS, 2019, 7 : 92476 - 92498
  • [10] HBL-Sketch: A New Three-Tier Sketch for Accurate Network Measurement
    Zhao, Keyan
    Wang, Junxiao
    Qi, Heng
    Xie, Xin
    Zhou, Xiaobo
    Li, Keqiu
    ALGORITHMS AND ARCHITECTURES FOR PARALLEL PROCESSING (ICA3PP 2019), PT I, 2020, 11944 : 48 - 59