With the technology advances in multimedia compression and Internet, multimedia applications delivered over Internet are dramatically boosted. Currently, real-time streaming without waiting for complete downloads is the trend of video delivery. However, it is very difficult to allocate resources effectively due to the bursty nature of video traffic. The impact of variable available bandwidth and network delay, which results from a best-effort network such as today’s Internet, may degrade the received video quality drastically. Besides, these multimedia streaming applications generally utilize the UDP protocol that does not provide the congestion control. This may lead to congestion collapse and starvation of TCP traffic in the Internet. Therefore, this thesis proposes an end-to-end adaptive video streaming system by integrating the TCP-Friendly Rate Control (TFRC) with the video traffic smoothing algorithm. The proposed framework can adaptively adjust the smoothing transmission schedule to ensure the smooth delivery quality for different real-time and pre-stored video streams with low quality degradation. The adaptation is based on the current network condition, the available resources and the characteristics of video traffic. Simulation results show that, when the average available bandwidth is close to the video target encoding rate, the proposed system can effectively reduce the total packet loss rate of online video streaming from 5.67% to 0.91% compared with traditional TFRC solution.