Performance Analysis of a New Packet Trace Compressor based on TCP Flow Clustering

In this paper we study the properties of a new packet trace compression method based on clustering of TCP flows. With our proposed method, the compression ratio that we achieve is around 3%, reducing the file size, for instance, from 100 MB to 3 MB. Although this specification defines a lossy compressed data format, it preserves important statistical properties present into original trace. In order to validate the method, memory performance studies were done with the Radix Tree algorithm executing a trace generated by our method. To give support to these studies, measurements were taken of memory access and cache miss ratio. For the time, the results have showed that our proposed method provides a good solution for packet trace compression