Client Clustering and Joint Multistream FEC Rate Allocation in IPTV Systems

This paper addresses the problem of clustering heterogeneous clients in IPTV services over lossy networks. The delivery of the same stream to clients with different capabilities or access networks is surely suboptimal in terms of average quality for the population of receivers. Instead, we propose that the streaming servers deliver distinct multicast streams to different subsets of clients. We formulate an optimization problem where the receivers are clustered depending on the quality of their connection so that the average video quality in the IPTV system is maximized. Then we propose a novel algorithm for determining optimally the clusters, as well as the source and channel rate allocation in each of the clusters. Simulation results show that the proposed algorithm is able to maximize the average quality in the system when each of the servers transmits information to a distinct cluster. In particular, we show that the proposed solution outperforms baseline schemes that serve all clients with the same multicast stream, as it is commonly the case in practical systems.