Video traffic is bursty in nature and has different network requirements compared to other types of traffic (e.g. voice, data) in terms of bandwidth, delay, jitter, and loss etc. So it becomes important to manage video traffic on a WLAN carefully to achieve acceptable levels of Quality of Service (QoS). The unique contribution of this work is that it presents experimental and simulation studies of the performance of real video content streamed over WLAN networks. Under various test scenarios the performance of the WLAN network in terms of delay, loss, throughput etc. is analysed in the presence of background traffic. The effects of different types of server configurations and access contention between stations are also investigated for IEEE 802.11b and IEEE 802.11e networks. This work specifically considers the IPB fame based nature of MPEG- 4 encoded video. A novel QoS aware MPEG-4 video delivery algorithm is proposed and evaluated using a computer model written in the C programming language. The model exploits two mechanisms namely frame retransmission (ReTx) and GOP truncation (GOPT). The ReTx mechanism effectively increases the QoS by minimising the transmission losses at the expense of an increased buffer overflow probability. The GOPT mechanism reduces the probability of buffer overflow at the expense of a reduced QoS. The QoS aware MPEG-4 video delivery algorithm aims to achieve an optimal trade off between these two mechanisms in order to eliminate buffer overflow and minimise transmission losses. The algorithm aims to replace uncontrolled packet loss due to buffer overflow, MAC collisions, and transmission errors by a controlled prioritized packet loss scheme that permits a graceful degradation in MPEG-4 video quality streamed over IEEE 802.11b networks. This ensures the realisation of the most favourable network conditions for the delivery of MPEG-4 video frames on WLANs. Through extensive simulations it has been shown to provide a significant improvement in the QoS performance for video streaming applications for both uplink and downlink network scenarios in the presence of background traffic
