Discount Counting for Fast Flow Statistics on Flow Size and Flow Volume

被引:30
|
作者
Hu, Chengchen [1 ]
Liu, Bin [2 ]
Zhao, Hongbo [3 ]
Chen, Kai [4 ]
Chen, Yan [5 ]
Cheng, Yu [6 ]
Wu, Hao [2 ]
机构
[1] Xi An Jiao Tong Univ, Dept Comp Sci & Technol, MOE KLINNS Lab, Xian 710000, Peoples R China
[2] Tsinghua Univ, Dept Comp Sci & Technol, Beijing 100084, Peoples R China
[3] MeshSr Co Ltd, Nanjing 211100, Jiangsu, Peoples R China
[4] Hong Kong Univ Sci & Technol, Dept Comp Sci & Engn, Hong Kong, Hong Kong, Peoples R China
[5] Northwestern Univ, Dept Elect Engn & Comp Sci, Evanston, IL 60208 USA
[6] IIT, Dept Elect & Comp Engn Technol, Chicago, IL 60616 USA
基金
美国国家科学基金会;
关键词
Counter; flow statistics; network measurement; unbiased estimation; ARCHITECTURE;
D O I
10.1109/TNET.2013.2270439
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
A complete flow statistics report should include both flow size (the number of packets in a flow) counting and flow volume (the number of bytes in a flow) counting. Although previous studies have contributed a lot to the flow size counting problem, it is still a great challenge to well support the flow volume statistics due to the demanding requirements on both memory size and memory bandwidth in monitoring device. In this paper, we propose a DIScount COunting (DISCO) method, which is designed for both flow size and flow bytes counting. For each incoming packet of length, DISCO increases the corresponding counter assigned to the flow with an increment that is less than. With an elaborate design on the counter update rule and the inverse estimation, DISCO saves memory consumption while providing an accurate unbiased estimator. The method is evaluated thoroughly under theoretical analysis and simulations with synthetic and real traces. The results demonstrate that DISCO is more accurate than related work given the same counter sizes. DISCO is also implemented on the network processor Intel IXP2850 for a performance test. Using only one microengine (ME) in IXP2850, the throughput can reach up to 11.1 Gb/s under a traditional traffic pattern. The throughput increases to 39 Gb/s when employing four MEs.
引用
收藏
页码:970 / 981
页数:12
相关论文
共 50 条
  • [1] Fast flow volume estimation
    Ben Basat, Ran
    Einziger, Gil
    Friedman, Roy
    PERVASIVE AND MOBILE COMPUTING, 2018, 48 : 101 - 117
  • [2] Fast Flow Volume Estimation
    Ben Basat, Ran
    Einziger, Gil
    Friedman, Roy
    ICDCN'18: PROCEEDINGS OF THE 19TH INTERNATIONAL CONFERENCE ON DISTRIBUTED COMPUTING AND NETWORKING, 2018,
  • [3] A Fast People Counting Method Based on Optical Flow
    Tokta, Aybars
    Hocaoglu, Ali Koksal
    2018 INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND DATA PROCESSING (IDAP), 2018,
  • [4] A FLOW ULTRAMICROSCOPE FOR PARTICLE COUNTING AND SIZE DISTRIBUTION ANALYSIS
    WALSH, DJ
    ANDERSON, J
    PARKER, A
    DIX, MJ
    COLLOID AND POLYMER SCIENCE, 1981, 259 (10) : 1003 - 1009
  • [5] Traffic Flow Prediction Method Based on Fast Statistics of Traffic Flow and Graph Convolutional Network
    Jiang, Dan
    Hou, Qun
    Liu, Xin
    Gao, Shidi
    2023 IEEE 8th International Conference on Intelligent Transportation Engineering, ICITE 2023, 2023, : 54 - 59
  • [6] Flow: Statistics, visualization and informatics for flow cytometry
    Frelinger, Jacob
    Kepler, Thomas B.
    Chan, Cliburn
    SOURCE CODE FOR BIOLOGY AND MEDICINE, 2008, 3 (01):
  • [7] Flow analysis-based fast-moving flow calibration for a people-counting system
    Park, Jae Hyeon
    Cho, Sung In
    MULTIMEDIA TOOLS AND APPLICATIONS, 2021, 80 (21-23) : 31671 - 31685
  • [8] Flow analysis-based fast-moving flow calibration for a people-counting system
    Jae Hyeon Park
    Sung In Cho
    Multimedia Tools and Applications, 2021, 80 : 31671 - 31685
  • [9] A FAST, DATA-FLOW-ORIENTED PREPROCESSOR FOR CLUSTER COUNTING
    IMHOF, M
    NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT, 1995, 360 (1-2): : 356 - 358
  • [10] Fast and Accurate Flow Counting Algorithm for the Management of IP Networks
    Zhu, Shan
    Ohta, Satoru
    PROCEEDINGS OF THE 2010 IEEE-IFIP NETWORK OPERATIONS AND MANAGEMENT SYMPOSIUM, 2010, : 918 - 921