An efficient modeling and dimensioning approach for integrated streaming and elastic traffic

Recent studies show that both data traffic and real-time traffic grow very fast in wired and wireless networks. To provide better performance guarantee, these applications need efficient network modeling and planning. In this paper, the problem where the total bandwidth of a link is shared by streaming traffic (real time traffic such as voice or video etc.) and elastic traffic (such as data) is studied. Integrating streaming traffic and elastic traffic presents a unique dimensioning problem. This paper considers dimensioning a link to satisfy both quality of service (QoS) requirements for streaming traffic, such as loss probability, and elastic traffic, such as mean waiting (delay) time. The Erlang loss model is applied to streaming traffic and a bursty traffic model is applied to the elastic traffic. Efficient dimensioning algorithms based on classical Markovian models and time-scale decomposition are then proposed. Numerical results show that the proposed methods have good accuracy.