Abstract
The acronym P2PTV, which stands for Peer-to-Peer Television, refers to P2P applications that enable multimedia contents broadcasting through the Internet. These applications have become very popular due to their capability of delivering material with or without copyright protection to a large audience. In P2PTV applications, the start-up phase - from the moment the client joins an existing channel to the moment she can start viewing the content - is crucial. A long time before showing the first images of a video, can make a user switch to another channel or to an alternative P2P application. Later on, the same user behavior is expected in case of frozen images. In this paper, we consider the case of Sopcast, which is currently one of the most popular P2PTV applications. Sopcast recently modified its start-up algorithms. We uncover the details of the new strategy adopted by Sopcast and evaluate its performance as a function of the swarm size and the geographic source of the content.
Highlights
The key idea behind Peer-to-Peer (P2P) is scalability
Before delving into the details of the peer picking algorithm used by the Sopcast tracker, we investigate if the tracker follows a strategy to control the number of peers that are behind a firewall to compose an initial peer list (PL)
If the node does not reply to our legacy ping, but successfully replies to our application ping, the probability of that node being behind a firewall is high
Summary
The key idea behind Peer-to-Peer (P2P) is scalability. Unlike client/server architectures, the performance of P2P architectures increases as the number of users increases, since any peer (a host engaged in a P2P network) can act like both client and/or server. The main objective was to provide to a new arriving peer a list of peers that are presumably its nearest neighbors This strategy is a major shift in the protocol, which was previously relying on a random approach to pick the addresses in the list maintained by the central tracker. We rely on an experimental approach to uncover the impact of the change in the initial peer picking algorithm of Sopcast. The remainder of this paper is organized as follows: Section 2 presents the Sopcast architecture and analyzes key parts of its protocol. The start-up time of a TV channel plays a key role in the Quality of Experience (QoE) of users. We began by analyzing the network level latency between a peer and its neighbors, as this parameter directly impacts the time needed to begin watching a given channel. It is clear that the network latency between peers is a key metric to assess the Quality of Experience (QoE) of a user
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