Group-Based Reduction Schemes for Streaming Applications

Some peer-to-peer streaming systemsmake use of linear codes to reduce the rate of the data uploaded by peers with limited upload capabilities. Such "data reduction" techniques are based on a vector-space approach and produce the data to be uploaded bymeans of linear combinations of the content data in a suitable finite field. In this paper, we propose a more general approach based on group theory. The new approach, while including the vector space approach as a special case, allows to design schemes that cannot be modeled as linear codes. We analyze the properties of the schemes based on the new approach, showing also how a group-based scheme can be used to prevent stream poisoning and how a group-based scheme can be converted into a secret-sharing scheme. Examples of group-based schemes that cannot be described in the vector-space framework are also shown.