Packet clustering introduced by routers: Modeling, analysis and experiments

Utilizing a highly precise network measurement device, we investigate router´s inherent variation on packet processing time and its effect on interpacket delay and packet clustering. We propose a simple pipeline model incorporating the inherent variation and a metric to measure packet clustering. To isolate the effect of the inherent variation, we begin our analysis with no cross traffic and step through setups where the input streams have different data rate, packet size and go through different number of hops. We show that a homogeneous input stream with a sufficiently large interpacket gap will emerge at the router´s output with interpacket delays that are negative correlated with adjacent values and have symmetrical distributions. We show that for smaller interpacket gaps, the change in packet clustering is smaller. It is also shown that the degree of packet clustering could in fact decrease for a clustered input. We generalize our results by adding cross traffic. We apply these results to demonstrate how we could reduce jitter by minimizing interpacket gap. All the results predicted by the model are validated with experiments with real routers.