Characterizing user mobility in second life
Proceedings of the first workshop on Online social networks
Textures in Second Life: Measurement and Analysis
ICPADS '08 Proceedings of the 2008 14th IEEE International Conference on Parallel and Distributed Systems
Traffic analysis of avatars in Second Life
Proceedings of the 18th International Workshop on Network and Operating Systems Support for Digital Audio and Video
CoNEXT '08 Proceedings of the 2008 ACM CoNEXT Conference
Avatar mobility in user-created networked virtual worlds: measurements, analysis, and implications
Multimedia Tools and Applications
Energy consumption in mobile phones: a measurement study and implications for network applications
Proceedings of the 9th ACM SIGCOMM conference on Internet measurement conference
Second life in-world action traffic modeling
Proceedings of the 20th international workshop on Network and operating systems support for digital audio and video
Network traces of virtual worlds: measurements and applications
MMSys '11 Proceedings of the second annual ACM conference on Multimedia systems
Toward region- and action-aware second life clients: A parameterized second life traffic model
ICME '11 Proceedings of the 2011 IEEE International Conference on Multimedia and Expo
Research note: Source models of network game traffic
Computer Communications
On Optimizing MMVEs in Network-Aware Clouds
Proceedings of International Workshop on Massively Multiuser Virtual Environments
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We propose region- and action-aware virtual world clients. To develop such clients, we present a parameterized network traffic model, based on a large collection of Second Life traces gathered by us. Our methodology is also applicable to virtual worlds other than Second Life. With the traffic model, various optimization criteria can be adopted, including visual quality, response time, and energy consumption. We use energy consumption as the show case, and demonstrate via trace-driven simulations that, compared to two existing schemes, a mobile client can save up to 36% and 41% communication energy by selectively turning on its WiFi network interface.