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SEAD Counter: Self-Adaptive Counters With Different Counting Ranges

文献类型：期刊论文

作者Liu, Xilai6,7; Xu, Yan1; Liu, Peng5; Yang, Tong5; Xu, Jiaqi4; Wang, Lun3; Xie, Gaogang2,6; Li, Xiaoming5; Uhlig, Steve4
刊名IEEE-ACM TRANSACTIONS ON NETWORKING
出版日期2021-09-13
页码17
关键词Memory management Mice Arrays Random access memory System-on-chip Hash functions Computer science Estimator sketches generic counter network measurement compression self-adaptive
ISSN号1063-6692
DOI10.1109/TNET.2021.3107418
英文摘要The Sketch is a compact data structure useful for network measurements. However, to cope with the high speeds of the current data plane, it needs to be held in the small on-chip memory (SRAM). Therefore, the product of the counter size and the number of counters must be below a certain limit. With small counters, some will overflow. With large counters, the total number of counters will be small, but each counter will be shared by more flows, leading to poor accuracy. To address this issue, we propose a generic technique: self-adaptive counters (SEAD Counter). When the value of the counter is small, it works as a standard counter. When the value of the counter is large however, we increment it using a predefined probability, so as to represent this large value. Moreover, in the SEAD Counter, the probability decreases when the value increases. We show that this technique can significantly improve the accuracy of counters. This technique can be adapted to different circumstances. We theoretically analyze the improvements achieved by the SEAD Counter. We further show that our SEAD Counter can be extended to three typical sketches and Bloom filters. We conduct extensive experiments on three real datasets and one synthetic dataset. The experimental results show that, compared with the state-of-the-art, sketches using the SEAD Counter improve the accuracy by up to 13.6 times, while the Bloom filters using SEAD Counter can reduce the false positive rate by more than one order of magnitude.
资助项目National Key Research and Development Program of China[2018YFB1800201] ; National Science Foundation of China (NSFC)[U20A20179]
WOS研究方向Computer Science ; Engineering ; Telecommunications
语种英语
WOS记录号WOS:000732147300001
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
源URL[http://119.78.100.204/handle/2XEOYT63/17924]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Yang, Tong; Xie, Gaogang
作者单位1.Univ Maryland, Dept Comp Sci, College Pk, MD 20742 USA
2.Chinese Acad Sci, Comp Network Informat Ctr, Beijing 100190, Peoples R China
3.Univ Calif Berkeley, Dept Elect Engn & Comp Sci, Berkeley, CA 94720 USA
4.Queen Mary Univ London, Sch Elect Engn & Comp Sci, London E1 4NS, England
5.Peking Univ, Dept Comp & Sci, Beijing 100871, Peoples R China
6.Univ Chinese Acad Sci UCAS, Sch Comp Sci & Technol, Beijing 100190, Peoples R China
7.Chinese Acad Sci, Inst Comp Technol, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714		 Liu, Xilai,Xu, Yan,Liu, Peng,et al. SEAD Counter: Self-Adaptive Counters With Different Counting Ranges[J]. IEEE-ACM TRANSACTIONS ON NETWORKING,2021:17.
APA Liu, Xilai.,Xu, Yan.,Liu, Peng.,Yang, Tong.,Xu, Jiaqi.,...&Uhlig, Steve.(2021).SEAD Counter: Self-Adaptive Counters With Different Counting Ranges.IEEE-ACM TRANSACTIONS ON NETWORKING,17.
MLA Liu, Xilai,et al."SEAD Counter: Self-Adaptive Counters With Different Counting Ranges".IEEE-ACM TRANSACTIONS ON NETWORKING (2021):17.

入库方式： OAI收割

来源：计算技术研究所

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