Trace–Adaptive Fragmentation for Periodic Broadcast of VBR Video

Periodic broadcast schemes have been proposed as a scalable solution for the implementation of Video–on– Demand (VoD) systems. Efficient periodic broadcast schemes fragment each video into a number of segments assuming that the videos are encoded using Constant Bit Rate (CBR) coders. We focus instead on the more efficient and commonplace class of Variable Bit Rate (VBR) encoded videos. The claim made in this paper is that the significant bit rate variability of VBR video requires a different fragmentation approach for the construction of periodic broadcast schedules. Rigid fragmentation techniques do not consider the particular video traces and may result in traffic which exceeds the available broadcast link capacity and can lead to increased data losses. Remarkably, all known periodic broadcast schemes use rigid fragmentation techniques. We introduce a new fragmentation scheme, Trace–Adaptive Fragmentation (TAF), which derives improved broadcast schedules for VBR video. Essentially, increased processing time for an off–line optimization process is traded off for improved data loss performance while also satisfying a prescribed maximum playout latency. Numerical results show the benefits, feasibility and flexibility of the proposed scheme.