Second life in-world action traffic modeling

Abstract

Massive multiplayer online games (MMOGs) are increasingly popular because they can provide entertainment, numerous opportunities for socialization, and the ability for end users to earn money. Cornerstone to MMOGs is the underlying network traffic between MMOG clients and servers; understanding this traffic is important for application developers trying to improve game performance and for ISPs trying to provide a better quality of service for their customers. In this paper we present fine-grained approaches at modeling SL client-server traffic. Our approaches differ from existing modeling work as they focus on the analysis of specific in-world actions, on the decomposition of the collected samples in subsets of packets with the same size, and on modeling the dependencies between packets in the sample. We compare our different approaches between them and with the original collected sample using the Kolmogorov-Smirnov (KS) test statistic on packet size and inter-arrival time. We observed over one order of magnitude improvement of our models in the KS statistic for packet size and three time improvement for packet inter-arrival time compared to a bivariate 2-component Gaussian mixture model.