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Multi-graph regularization for efficient delivery of user generated content in online social networks

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1 Author(s)
Chakareski, J. ; Signal Process. Lab., Ecole Polytech. Fed. de Lausanne, Lausanne, Switzerland

We present a methodology for enhancing the delivery of user-generated content in online social networks. To this end, we first regularize the social graph via node capacity and link cost information associated with the underlying data network. We then design a technique for constructing the most efficient delivery tree over the regularized social graph. Finally, we derive an optimization algorithm for allocating the nodes' uplink capacities over the content distribution tree. Our system substantially outperforms the conventional method of flooding data over the social graph, over multiple criteria. In particular, a 100% reduction in terms of network cost and data delivery delay is registered.

Published in:

Acoustics, Speech and Signal Processing (ICASSP), 2011 IEEE International Conference on

Date of Conference:

22-27 May 2011