Title :
Performance Study of Large-Scale Video Streaming Services in Highly Heterogeneous Environment
Author :
Ho, K.-M. ; Poon, W.-F. ; Lo, K.T.
Author_Institution :
Hong Kong Polytech Univ., Kowloon
Abstract :
To support large-scale Video-on-Demand (VoD) services in a heterogeneous network environment, either a replication or layering approach can be deployed to adapt the client bandwidth requirements. With the aid of the broadcasting and caching techniques, it has been proved that the overall performance of the system can be enhanced. In this paper, we explore the impact on the broadcasting schemes coupled with proxy caching and develop an analytical model to evaluate the system performance in a highly heterogeneous network environment. We develop guidelines for resources allocation, transmission strategies as well as caching schemes under different system configurations. The model can assist system designers to study various design options as well as perform system dimensioning. Moreover, a systematic comparison between replication and layering is performed. From the results, it can be seen that the system performance of layering is better than that of replication when the environment is highly heterogeneous even if the layering overhead is higher than 25%. In addition, it is found that the system blocking probability can be further reduced by exploring the broadcast capability of the network if the proxy server cannot store all the popular videos.
Keywords :
Internet; broadcasting; cache storage; probability; resource allocation; video on demand; video streaming; broadcasting scheme; caching scheme; client bandwidth requirement; heterogeneous network environment; large-scale video streaming service; probability; resource allocation; transmission strategy; video-on-demand service; Analytical models; Bandwidth; Broadcasting; Couplings; Guidelines; Large-scale systems; Multimedia communication; Resource management; Streaming media; System performance; Broadcasting; distributed servers; layered video; media streaming; network performance model; video-on-demand;
Journal_Title :
Broadcasting, IEEE Transactions on
DOI :
10.1109/TBC.2007.908326