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Per-Flow Cardinality Estimation Based On Virtual LogLog Sketching
[article]
2018
arXiv
pre-print
Flow cardinality estimation is the problem of estimating the number of distinct elements in a data flow, often with a stringent memory constraint. It has wide applications in network traffic measurement and in database systems. The virtual LogLog algorithm proposed recently by Xiao, Chen, Chen and Ling estimates the cardinalities of a large number of flows with a compact memory. The purpose of this thesis is to explore two new perspectives on the estimation process of this algorithm. Firstly,
arXiv:1812.03040v1
fatcat:7qpsdp2obfhwtksz2tbbs7pmvq