Ms. Maya Haridasan Profile

Maya Haridasan

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Proceedings Article | 28 January 2008 Paper

Enforcing fairness in a live-streaming system

Maya Haridasan, Ingrid Jansch-Porto, Robbert van Renesse

Proceedings Volume 6818, 68180E (2008) https://doi.org/10.1117/12.775127

KEYWORDS: Statistical analysis, Data modeling, Computing systems, Computer simulations, Receivers, Systems modeling, System identification, Computer science, Information science, Video

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We describe a practical auditing approach designed to encourage fairness in peer-to-peer streaming. Auditing is employed to ensure that correct nodes are able to receive streams even in the presence of nodes that do not upload enough data (opportunistic nodes), and scales well when compared to previous solutions that rely on tit-for-tat style of data exchange. Auditing involves two roles: local and global. Untrusted local auditors run on all nodes in the system, and are responsible for collecting and maintaining accountable information regarding data sent and received by each node. Meanwhile, one or more trusted global auditors periodically sample the state of participating nodes, estimate whether the streaming quality is satisfactory, and decide whether any actions are required. We demonstrate through simulation that our approach can successfully detect and react to the presence of opportunistic nodes in streaming sessions. Furthermore, it incurs low network and computational overheads, which remain fixed as the system scales.

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