Spatial-temporal analysis of passive TCP measurements

In this paper we look at TCP data which was passively collected from an edge ISP, and analyze it to obtain some new results and deeper understanding of TCP loss process. The focus of our study is to identify the ´root cause´ links, i.e., the links that are responsible for the majority of the losses or reorders found on the end-to-end TCP connection. We suggest a new root cause criterion and a cost-effective algorithm to identify the root cause links. The algorithm incorporates a new out-of-sequence packet classification technique which is interesting by itself. We test our algorithm on the collected and simulated data and analytically justify its correctness. The simulation results show that the algorithm has a 95% detection rate with 10% false detection rate. We also analyze TCP temporal loss process, and found that the burst loss size is geometrically distributed. We analyze the TCP time-out loss indication under the Bernoulli loss model, which is the simplest model that can cause a geometric distribution, and show that the behavior of the TCP loss process is not different than when tail drop is assumed.