Traffic prediction and QoS transmission of real-time live VBR videos in WLANs

As the demand for broadband multimedia wireless services is increasing, improving quality of service (QoS) of the widely deployed IEEE 802.11 wireless LANs (WLANs) has become crucial. To support the QoS required by a wide range of applications, the IEEE 802.11 working group has defined a new standard - the IEEE 802.11e. Substantial studies have been performed on traffic scheduling for variable bit rate (VBR) video transport over 802.11e WLANs. However, within those studies, relatively little attention has been devoted to the QoS transmission of real-time live VBR videos. In this paper, we present a novel traffic scheduling algorithm for IEEE 802.11e that aims at achieving high channel utilization while still guaranteeing QoS requirements for real-time live VBR videos. The novel characteristic of this algorithm, compared to published literatures, is that it predicts the bandwidth requirements for future traffic using a novel traffic predictor designed to provide simple yet accurate online prediction. Analyses using real life MPEG video traces indicate that the proposed traffic predictor significantly outperforms previously published technique with respect to the prediction error. The proposed traffic predictor can also be used independently to estimate any MPEG traffic. The performance of the proposed traffic scheduling algorithm is also investigated by comparing several existing scheduling algorithms. Simulation results demonstrate that the proposed traffic scheduling algorithm surpasses other mechanisms in terms of channel utilization, buffer usage, video quality and packet loss rate.