计算机科学 ›› 2013, Vol. 40 ›› Issue (6): 80-83.

• 网络与通信 • 上一篇    下一篇

相对误差受限的数据流流量测量算法

张进,赵文栋,彭来献,吴泽民   

  1. 解放军理工大学通信工程学院 南京210007;解放军理工大学通信工程学院 南京210007;解放军理工大学通信工程学院 南京210007;解放军理工大学通信工程学院 南京210007
  • 出版日期:2018-11-16 发布日期:2018-11-16
  • 基金资助:
    本文受江苏省自然科学基金项目(BK2010103)资助

Per-Flow Traffic Measurement Algorithm with Restrained Relative Error

ZHANG Jin,ZHAO Wen-dong,PENG Lai-xian and WU Ze-min   

  • Online:2018-11-16 Published:2018-11-16

摘要: 数据流流量测量的精度采用错误概率和相对误差进行衡量。现有的流量测量算法主要关注如何降低错误概率,而对如何减小相对误差则缺乏研究。考虑到减小相对误差对于流量计费等应用的重要意义,提出了一种相对误差受限的数据流流量测量算法MT-dlCBF(Multi-Tier d-left Counting Bloom Filter)。MT-dlCBF由多层dlCBF(d-left Counting Bloom Filter)构成,且随着层数的提高,dlCBF中数据流指纹长度和流量计数器宽度也逐步增加,这样,可减轻长流对于短流的干扰,从而达到减小相对误差的目的。理论分析和仿真实验的结果表明,与dlCBF相比,MT-dlCBF的错误概率略有增大,但相对误差显著减小。此外,在典型的参数条件下,MT-dlCBF的空间效率略优于dlCBF。

关键词: 流量测量,布鲁姆过滤器,相对误差

Abstract: The accuracy of per-flow traffic measurement is evaluated using the metrics of both error probability and rela-tive error.Current research on flow traffic measurement mainly focuses on reducing error probability,while little attention has been paid to alleviating relative error.Motivated by the importance of reducing relative error in certain applications such as usage accounting,this study presented a new algorithm named MT-dlCBF (Multi-Tierd-left Counting Bloom Filter) with restrained relative error.MT-dlCBF consists of several tiers of dlCBF (d-left Counting Bloom Filter),and dlCBF at higher tier has longer flow fingerprints and wider flow traffic counters than that of dlCBF at lower tier respectively.In this way,the interference of long flow to short ones can be alleviated significantly,resulting in restrained relative error.Analytical and experimental results show that MT-dlCBF provides significant decrement in relative error and trivial increment in error probability compared to dlCBF.Moreover,MT-dlCBF has higher space efficiency than dlCBF under typical parameter settings.

Key words: Traffic measurement,Bloom filter,Relative error

[1] Trammell B,Boschi E.An introduction to ip flow information export[J].IEEE Communications Magazine,2011,49(4):89-95
[2] Systems C.NetFlow.http://www.cisco.com/web/go/netflow
[3] Estan C.New Directions in Traffic Measurement and Accoun-ting[C]∥Proc.of ACM Sigcomm.2002:323-336
[4] Kumar A,Xu Jun.Space-Code Bloom Filter for Efficient Per-Flow Traffic Measurement[C]∥Proc.of IEEE Infocom.2004:315-328
[5] Lu Yi,Montanari A,Prabhakar B.Counter Braids:A NovelCounter Architecture for Per-Flow Measurement[C]∥Proc.ACM SIGMETRICS.2008:121-132
[6] Lu Yi,Prabhakar B.Robust Counting Via Counter Braids:AnError-Resilient Network Measurement Architecture[C]∥Proc.IEEE Infocom.2009:522-530
[7] Lieven P,Scheuermann B.High-Speed Per-Flow Traffic Mea-surement with Probabilistic Multiplicity Counting[C]∥Proc.of IEEE Infocom.2010:1253-1261
[8] Li Tao,Chen Shi-gang,Ling Yi-bei.Fast and Compact Per-Flow Traffic Measurement through Randomized Counter Sharing[C]∥Proc.of IEEE Infocom.2011:1799-1807
[9] Fan L,Cao P,Almeida J,et al.Summary Cache:a Scalable Widea-rea Web Cache Sharing Protocol [J].IEEE/ACM Transactions on Networking,2000,8(3):281-293
[10] Bonomi F,Mitzenmacher M,Panigrahy R,et al.An ImprovedConstruction for Counting Bloom Filters[C]∥Proc.of Euro-pean Symposium on Algorithms.2006:678-680
[11] Tsidon E,Hanniel I,Keslassy I.Estimators Also Need Shared Values to Grow Together[C]∥Proc.IEEE Infocom.2012:1390-1398
[12] 周明中.大规模网络IP流行为特性及其测量算法研究[D].南京:东南大学,2006.8

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