Packet Clustering Introduced by Routers
Chiun Lin Lim, Ki Suh Lee, Han Wang, Hakim Weatherspoon, Ao Tang · ACM Transactions on Modeling and Performance Evaluation of Computing Systems · 2019
In this article, we investigate a 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 two metrics—one to measure packet clustering and one to quantify inherent variation. 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 rates, packet size, and go through a 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. All the results predicted by the model are validated with experiments with real routers. We also investigated several factors that can affect the inherent variation as well as some potential applications of this study.