Page 453 - 《软件学报》2025年第7期

3374 软件学报 2025 年第 36 卷第 7 期

[25] Wang MM, Zhou MX, Shi SQ, Qian C. Vacuum filters: More space-efficient and faster replacement for bloom and cuckoo filters. Proc.
of the VLDB Endowment, 2019, 13(2): 197–210. [doi: 10.14778/3364324.3364333]
[26] Wang HC, Dai HP, Li M, Yu J, Gu R, Zheng JQ, Chen GH. Bamboo filters: Make resizing smooth. In: Proc. of the 38th Int’l Conf. on
Data Engineering. Kuala Lumpur: IEEE, 2022. 979–991. [doi: 10.1109/ICDE53745.2022.00078]
[27] Xie RB, Li M, Miao ZY, Gu R, Huang H, Dai HP, Chen GH. Hash adaptive bloom filter. In: Proc. of the 37th Int’l Conf. on Data
Engineering. Chania: IEEE, 2021. 636–647. [doi: 10.1109/ICDE51399.2021.00061]
[28] Mitzenmacher M, Pontarelli S, Reviriego P. Adaptive cuckoo filters. ACM Journal of Experimental Algorithmics, 2020, 25(1.1): 1–20.
[doi: 10.1145/3339504]
[29] Kraska T, Beutel A, Chi EH, Dean J, Polyzotis N. The case for learned index structures. In: Proc. of the 2018 Int’l Conf. on Management
of Data. Houston: ACM, 2018. 489–504. [doi: 10.1145/3183713.3196909]
[30] Vaidya K, Knorr E, Kraska T, Mitzenmacher M. Partitioned learned bloom filter. arXiv:2006.03176, 2020.
[31] Deeds K, Hentschel B, Idreos S. Stacked filters: Learning to filter by structure. Proc. of the VLDB Endowment, 2020, 14(4): 600–612.
[doi: 10.14778/3436905.3436919]
[32] Luo LL, Guo DK, Rottenstreich O, Ma RTB, Luo XS, Ren BB. The consistent cuckoo filter. In: Proc. of the IEEE Conf. on Computer
Communications. Paris: IEEE, 2019. 712–720. [doi: 10.1109/INFOCOM.2019.8737454]
[33] Fu PT, Luo LL, Guo DK, Zhao X, Li SS, Wang HM. Jump filter: Dynamic sketch design for big data governance. Ruan Jian Xue
Bao/Journal of Software, 2023, 34(3): 1193–1212 (in Chinese with English abstract). http://www.jos.org.cn/1000-9825/6782.htm [doi: 10.
13328/j.cnki.jos.006782]
[34] Putze F, Sanders P, Singler J. Cache-, hash-, and space-efficient bloom filters. ACM Journal of Experimental Algorithmics, 2010, 14: 4.
[doi: 10.1145/1498698.1594230]
[35] CAIDA. https://www.caida.org/
[36] MAWI working group traffic archive. https://mawi.wide.ad.jp/mawi/

附中文参考文献:
[13] 谢鲲, 文吉刚, 张大方, 谢高岗. 布鲁姆过滤器查询算法. 软件学报, 2009, 20(1): 96–108. http://www.jos.org.cn/1000-9825/3458.htm
[doi: 10.3724/SP.J.1001.2009.03458]
[33] 符鹏涛, 罗来龙, 郭得科, 赵翔, 李尚森, 王怀民. 跳跃滤波: 一种面向大数据治理的动态数据摘要设计. 软件学报, 2023, 34(3):
1193–1212. http://www.jos.org.cn/1000-9825/6782.htm [doi: 10.13328/j.cnki.jos.006782]

李猛(1993－), 男, 博士, 助理研究员, CCF 专业 王瀚橙(1998－), 男, 博士生, CCF 学生会员, 主
会员, 主要研究领域为概率性数据结构, 物联网 要研究领域为数据索引和查询优化.
系统.

罗文啟(2001－), 男, 硕士生, 主要研究领域为高 顾荣(1988－), 男, 博士, 助理教授, 博士生导师,
性能网络. CCF 高级会员, 主要研究领域为大数据并行处
理系统.

戴海鹏(1985－), 男, 博士, 副教授, 博士生导师, 陈贵海(1963－), 男, 博士, 教授, 博士生导师,
CCF 杰出会员, 主要研究领域为物联网, 数据挖 CCF 会士, 主要研究领域为无线网络, 并行计算,
掘, 边缘计算, 移动计算. 算法设计.