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Sponsored by the Center for Science and Technology Development of the Ministry of Education
Supervised by Ministry of Education of the People's Republic of China
In high-speed network monitoring, the ever-growing traffic calls for a high-performance solution for the computation of items' frequencies. The increasing number of cores in current commodity multi-core processors opens up new opportunities in parallelization. In this paper, we present a novel method that exploits the great parallel capability of multi-cores to speed up the famous Count-Min sketch algorithm. The proposed parallel Count-Min sketch algorithm equally distributes the input data stream into sub-threads which use the original Count-Min sketch algorithm to process the sub-streams. The counters in each local Count-Min sketch with frequency increments exceeding a pre-defined threshold are sent to a merging thread which is able to return the estimated frequencies satisfying the (epsilon, delta)-approximation requirement. The theoretical correctness and complexity analyses are presented. Experiments with real traffic traces confirm the theoretical analyses and demonstrate the excellent performance as well as the effects of parameters. The results show that the proposed parallel Count-Min sketch algorithm achieves near-linear speedup at the cost of greater memory use.
Keywords:Count-Min sketch; Parallel algorithms; Data streams