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arXiv · 1103.5678

Converging an Overlay Network to a Gradient Topology

Håkan Terelius·Guodong Shi·Jim Dowling·Amir Payberah·Ather Gattami·Karl Henrik Johansson
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Abstract

In this paper, we investigate the topology convergence problem for the gossip-based Gradient overlay network. In an overlay network where each node has a local utility value, a Gradient overlay network is characterized by the properties that each node has a set of neighbors with the same utility value (a similar view) and a set of neighbors containing higher utility values (gradient neighbor set), such that paths of increasing utilities emerge in the network topology. The Gradient overlay network is built using gossiping and a preference function that samples from nodes using a uniform random peer sampling service. We analyze it using tools from matrix analysis, and we prove both the necessary and sufficient conditions for convergence to a complete gradient structure, as well as estimating the convergence time and providing bounds on worst-case convergence time. Finally, we show in simulations the potential of the Gradient overlay, by building a more efficient live-streaming peer-to-peer (P2P) system than one built using uniform random peer sampling.

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Håkan Terelius, Guodong Shi, Jim Dowling, Amir Payberah, Ather Gattami, Karl Henrik Johansson. 2011-03-29. Converging an Overlay Network to a Gradient Topology. https://doi.org/10.1109/cdc.2011.6161194

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