Traffic modeling and performance analysis for IPTV systems

Date

2008-08-11T17:49:08Z

Authors

Wan, Fengdan

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Abstract

Internet protocol TV (IPTV) is predicted to be the key technology winner in the future. It has, however, stringent quality of service (QoS) requirements. When IPTV traffic shares the network resources with other traffic like data and voice, how to ensure their QoS and efficiently utilize the network resources is a key and challenging issue. In this thesis, Class based queueing (CBQ) is suggested to deploy at the bottleneck router to allow heterogeneous traffic share network resources fairly and efficiently. Then, we propose a two-level Markovian video traffic model and develop a fluid flow based analytical framework to quantify the performance of IPTV systems and derive the admission regions to ensure the QoS of IPTV traffic. The proposed two-level Markovian traffic model exploits both the temporal and spatial complexity of video traffic. The model can easily be incorporated to network simulators. The fidelity of the proposed video model and the effectiveness of the analytical framework are verified by network simulations driven by real video traces. Given the traffic model, a fluid flow based analytical framework is developed to study the queueing behaviors of IPTV traffic in wired, single-hop and multi-hop wireless networks. The analytical results provide insights in how traffic characteristics and network parameters affect the network performance. To ensure the QoS of heterogeneous traffic, admission regions of a wired or wireless bottleneck, with or without CBQ are obtained. The simulation and analytical results both illustrate that time-varying wireless link accommodates much less IPTV connections than the wired link with fixed data rate. The variations of both the incoming traffic arrival rate and the outgoing service rate affect the network performance and admission region. Therefore, it is recommended to deploy proper traffic shaping and resource management schemes in order to support IPTV traffic more efficiently.

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Keywords

IPTV, fluid, modeling, analysis

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