text: Epidemic protocols proved to be very efficient solutions for supporting dynamic and complex information diffusion in highly dis- tributed computing infrastructures, like P2P environments. They are useful bricks for building and maintaining virtual network topologies, in the form of overlay networks as well as to support pervasive diffusion of information when it is injected into the network. This paper proposes a simple architecture exploiting the features of epidemic approaches to foster a collaborative percolation of information between computing nodes belonging to the network aimed at building a system that groups similar users and spread useful information among them.
  @cite_12: Most current peer-to-peer (P2P) file-sharing systems treat their users as anonymous, unrelated entities, and completely disregard any social relationships between them. However, social phenomena such as friendship and the existence of communities of users with similar tastes or interests may well be exploited in such systems in order to increase their usability and performance. In this paper we present a novel social-based P2P file-sharing paradigm that exploits social phenomena by maintaining social networks and using these in content discovery, content recommendation, and downloading. Based on this paradigm's main concepts such as taste buddies and friends, we have designed and implemented the TRIBLER P2P file-sharing system as a set of extensions to BitTorrent. We present and discuss the design of TRIBLER, and we show evidence that TRIBLER enables fast content discovery and recommendation at a low additional overhead, and a significant improvement in download performance. Copyright © 2007 John Wiley & Sons, Ltd.
summary: They make use of heterogeneous but semantically related information sources whereas our approach does not rely on any kind of semantic interpretation. It, in principle, enables a broader exploitation of more heterogeneous data sources. Related with our proposal is Tribler @cite_12 , a P2P television recommender system. In contrast with our approach, neighbor lists can be directly filled in by the user herself using an interface. No topology or affinity property is considered. We propose a gossip system that construct and maintain in rest groups of dynamic users based on their past activities, without needing their direct intervention.