Toward region- and action-aware second life clients: A parameterized second life traffic model

Virtual worlds, such as Second Life, are computer-simulated spaces divided into multiple regions, in which each user controls an avatar to perform actions (such as run and fly) in order to interact with other users. Second Life incurs diverse traffic patterns in different regions and with different actions. Hence, we propose region- and action-aware Second Life clients, which adapt to and take advantages of the diverse traffic patterns for user-specified optimization criterion, such as high visual quality, low energy consumption, and short response time. To achieve this, we develop a parameterized traffic model to predict Second Life traffic patterns. We systematically derive the traffic model parameters using public Second Life traces [1], and we validate the model accuracy using another set of real network traces. To the best of our knowledge, region- and action-aware virtual world clients have never been considered in the literature. In addition, the proposed parameterized traffic model is of interest in its own right to various parties, including: (i) virtual world developers, (ii) researchers, and (iii) Internet Service Providers (ISPs).