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Understanding the aggregate behavior of network host connectivity is important for network monitoring and traffic engineering. One characterization of such an aggregate behavior is the host distributions of distinct communicating peers or flows. For example, during the worm outbreak, the port scanning activities would cause many hosts with increasing number of (one-way) peers (or flows), and hence a change in the host distributions of distinct communicating peers or flows. In this paper, the authors develop an efficient streaming algorithm for tracking these host distributions of distinct elements, also called cardinality distributions, for a high speed network with a large number of hosts.
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