Per-flow traffic measurement is essential for network management; billing, traffic engineering, mitigating denial of service attacks, to mention just a few. In this field, the fundamental problem is that the size of expensive SRAM is too small to hold traffic data from high-speed networks. In this paper, we propose a new method for per-flow traffic measurement, which is based on the virtual vector that was originally designed for the problem of spread estimation. We modify the original virtual vector and show that this simple change yields a highly effective per-flow traffic estimator. Experiments show that our proposed scheme outperforms the state-of-the-art method in terms of both processing time and space requirement.

Bloom filters are widely used for various network applications. Because of the limited size of on-chip memory and the large volume of network traffic, Bloom filters are often required to update their contents incrementally. Two techniques have been used for this purpose: cold cache and double buffering. Cold cache outperforms double buffering in terms of the average cache ratio. However, double buffering works much better than cold cache for the worst-case cache hit ratio. In this paper, we propose a new updating scheme for Bloom filters, which updates the contents of Bloom filter incrementally while the assigned memory space is fully utilized. The proposed scheme works better than cold cache in terms of the average cache hit ratio. At the same time, it outperforms double buffering for the worst-case cache hit ratio.