On-line Video Traffic Smoothing for
IP Networks with Variable Delay

 Abstract

The technique of on-line video traffic smoothing is a significant method to improve the network BW utilization and reduce the burstiness characteristic of live video data. An efficient traffic smoothing scheme should not only consider the characteristics of video coding, but also consider the QoS capacity of IP network and the limitation of server and client buffer space. Regarding the methods of delivering video data used by current video coding standards, a constant transmission rate and a fixed network delay are assumed whether the Hypothetical Reference Decoder (HRD) in H.263 or the video buffering verifier in MPEG is considered. These assumptions are quite rigid and unrealistic due to the variety of current network environments, especially for live on-line video applications.

Therefore, this paper proposes an Integrated On-line traffic Smoothing (IOS) system that consists of the Long-Span Prediction (LSP) scheme, the Smart Hopping (SH) approach, the Middle Tracking (MT) method, and the Dynamic Bound Adjustment with network Delay Tracking (DBA-DT) strategy. Compared with traditional schemes, the proposed IOS can provide more efficient smoothing performances with low variance of transmission rates and low peak rate requirement. More importantly, IOS provide the robust capability against the dynamic network delay. Simulation results reveal that IOS can effectively reduce the number of negotiations with network up to 80% and low the frame loss rate  up to 20%