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Efficient Heavy Hitters Identification over Speed Traffic Streams
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作者 shuzhuang zhang Hao Luo +3 位作者 Zhigang Wu Yanbin Sun Yuhang Wang Tingting Yuan 《Computers, Materials & Continua》 SCIE EI 2020年第4期213-222,共10页
With the rapid increase of link speed and network throughput in recent years,much more attention has been paid to the work of obtaining statistics over speed traffic streams.It is a challenging problem to identify hea... With the rapid increase of link speed and network throughput in recent years,much more attention has been paid to the work of obtaining statistics over speed traffic streams.It is a challenging problem to identify heavy hitters in high-speed and dynamically changing data streams with less memory and computational overhead with high measurement accuracy.In this paper,we combine Bloom Filter with exponential histogram to query streams in the sliding window so as to identify heavy hitters.This method is called EBF sketches.Our sketch structure allows for effective summarization of streams over time-based sliding windows with guaranteed probabilistic accuracy.It can be employed to address problems such as maintaining frequency statistics and finding heavy hitters.Our experimental results validate our theoretical claims and verifies the effectiveness of our techniques. 展开更多
关键词 Traffic stream heavy hitter sliding window frequency statistics
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