Adaptive network traffic management for multi user virtual environments
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Multi User Virtual Environments (MUVE) are a new class of Internet application with a significant user base. This thesis adds to our understanding of how MUVE network traffic fits into the mix of Internet traffic, and how this relates to the application's needs. MUVEs differ from established Internet traffic types in their requirements from the network. They differ from traditional data traffic in that they have soft real-time constraints, from game traffic in that their bandwidth requirements are higher, and from audio and video streaming traffic in that their data streams can be decomposed into elements that require different qualities of service. This work shows how real-time adaptive measurement based congestion control can be applied to MUVE streams so that they can be made more responsive to changes in network conditions than other real-time traffic and existing MUVE clients. It is shown that a combination of adaptive congestion control and differential Quality of Service (QoS) can increase the range of conditions under which MUVEs both get sufficient bandwidth and are Transport Control Protocol (TCP) fair. The design, implementation and evaluation of an adaptive traffic management system is described. The system has been implemented in a modified client, which allows the MUVE to be made TCP fair without changing the server.
Thesis, PhD Doctor of Philosophy
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