On Democracy in Peer-to-Peer systems

The information flow inside a P2P network is highly dependent on the network structure. In order to ease the diffusion of relevant data toward interested peers, many P2P protocols gather similar nodes by putting them in direct contact. With this approach the similarity between nodes is computed in a point-to-point fashion: each peer individually identifies the nodes that share similar interests with it. This leads to the creation of a sort of "private" communities, limited to each peer neighbors list. This "private" knowledge do not allow to identify the features needed to discover and characterize the correlations that collect similar peers in broader groups. In order to let these correlations to emerge, the collective knowledge of peers must be exploited. One common problem to overcome in order to avoid the "private" vision of the network, is related to how distributively determine the representation of a community and how nodes may decide to belong to it. We propose to use a gossip-like approach in order to let peers elect and identify leaders of interest communities. Once leaders are elected, their profiles are used as community representatives. Peers decide to adhere to a community or another by choosing the most similar representative they know about

Hybrid Dissemination: Adding Determinism to Probabilistic Multicasting in Large-Scale P2P Systems

Abstract. Epidemic protocols have demonstrated remarkable scalability and robustness in disseminating information on internet-scale, dynamic P2P systems. However, popular instances of such protocols suffer from a number of significant drawbacks, such as increased message overhead in push-based systems, or low dissemination speed in pull-based ones. In this paper we study push-based epidemic dissemination algorithms, in terms of hit ratio, communication overhead, dissemination speed, and resilience to failures and node churn. We devise a hybrid push-based dissemination algorithm, combining probabilistic with deterministic properties, which limits message overhead to an order of magnitude lower than that of the purely probabilistic dissemination model, while retaining strong probabilistic guarantees for complete dissemination of messages. Our extensive experimentation shows that our proposed algorithm outperforms that model both in static and dynamic network scenarios, as well as in the face of large-scale catastrophic failures. Moreover, the proposed algorithm distributes the dissemination load uniformly on all participating nodes. Keywords: Epidemic/Gossip protocols, Information Dissemination, Peer-to-Peer

Localizzazione di comunita per similarita su reti peer to peer basate su DHT

La tesi presenta la definizione e l'implementazione di un sistema per la ricerca per similarità di profili di comunità su reti di tipo DHT. Il sistema è caratterizzato dall'utilizzo di funzioni LSH basate su min-wise independent permutations per l'indicizzazione dei profili memorizzati sulla DHT allo scopo di abbattere il consumo di banda e spazio di memorizzazione

Proactive Gossip-Based Management of Semantic Overlay Networks

Much research on content-based P2P searching for file-sharing applications has focused on exploiting semantic relations between peers to facilitate searching. Current methods suggest reactive ways to manage semantic relations: they rely on the usage of the underlying search mechanism, and infer semantic relationships based on the queries placed and the corresponding replies received. In this paper we follow a different approach, proposing a proactive method to build a semantic overlay. Our method is based on an epidemic protocol that clusters peers with similar content. Peer clustering is done in a completely implicit way, that is, without requiring the user to specify preferences or to characterize the content of files being shared. In our approach, each node maintains a small list of semantically optimal peers. Our simulation studies show that such a list is highly effective when searching files. The construction of this list through gossiping is efficient and robust, even in the presence of changes in the network. Copyright © 2007 John Wiley & Sons, Ltd