Optimal Erasure Protection Strategy for Scalably Compressed Data With Tree-Structured Dependencies

This paper is concerned with the transmission of scalably compressed data sources over lossy channels. Specifically, this paper is concerned with packet networks or, more generally, erasure channels. Previous work has generally assumed that the source elements form linear dependencies. The contribution of this paper is an unequal erasure protection algorithm which is able to take advantage of scalable data with more general dependency structures. In particular, the proposed scheme is adapted to data with tree-structured dependencies. The source elements are allocated to clusters of packets according to their dependency structure, subject to constraints on packet size and channel codeword length. Given a packet cluster arrangement, source elements are assigned optimal channel codes subject to a constraint on the total transmission length. Experimental results confirm the benefit associated with exploiting the actual dependency structure of the data.