Diagnóstico de Poluição de Conteúdo em Redes P2P
para Transmissões de Mídia Contínua ao Vivo

Emanuel A. Schimidt, Roverli P. Ziwich, Elias P. Duarte Jr., Ingrid Jansch-Pôrto
Proc. of the 17th Brazilian Symposium on Multimedia and the Web --
XVII Simpósio Brasileiro de Sistemas Multimídia e Web (WEBMEDIA'2011),
ISSN 2175-9642, pp. 221-228,
Florianópolis, SC, Brazil, Oct, 2011.  [pdf]


Content pollution is one of the challenges for deploying live streaming with P2P networks in the Internet. As the peers themselves are responsible to retransmit data, there is no trivial solution to this problem. This work presents a new strategy to detect content pollution that employs comparison-based diagnosis to identify modifications on the data stream. A peer compares selected chunks with those of its neighbors. Based on the comparison results, peers that transmitted polluted content are identified. The proposed solution was implemented using Fireflies, a scalable and intrusion-tolerant overlay network. Experimental results show that the strategy represents a feasible solution to detect content pollution and adds a low overhead in terms of network bandwidth.


A poluição de conteúdo é um dos desafios do uso de redes P2P para a transmissão de mídia contínua ao vivo. Como os próprios peers são responsáveis pela retransmissão dos dados, este não é um problema de solução trivial. Este trabalho apresenta uma nova solução para a detecção de poluição que utiliza o diagnóstico baseado em comparações para identificar alterações no conteúdo dos dados transmitidos. Cada peer do sistema executa comparações sobre determinados chunks de seus vizinhos. Com base no resultado das comparações, é possível detectar se há poluição de conteúdo e quem são os peers poluídos. A solução proposta foi implementada no Fireflies, um protocolo escalável para redes overlay tolerante a intrusões. Resultados experimentais mostram que esta estratégia é uma solução viável para a detecção de alterações de conteúdo e que a solução apresenta baixa sobrecarga no tráfego da rede.


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