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.
Other approaches cluster users on the basis of similarity between their semantics profile. Approaches of this kind of systems includes GridVine @cite_11 , the semantic overlay networks @cite_22 and p2pDating @cite_6 . They build a semantic P2P overlay infrastructure that relies on a logical layer storing data.
@cite_22 @cite_6 @cite_11
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This paper addresses the problem of building scalable semantic overlay networks. Our approach follows the principle of data independence by separating a logical layer, the semantic overlay for managing and mapping data and metadata schemas, from a physical layer consisting of a structured peer-to-peer overlay network for efficient routing of messages. The physical layer is used to implement various functions at the logical layer, including attribute-based search, schema management and schema mapping management. The separation of a physical from a logical layer allows us to process logical operations in the semantic overlay using different physical execution strategies. In particular we identify iterative and recursive strategies for the traversal of semantic overlay networks as two important alternatives. At the logical layer we support semantic interoperability through schema inheritance and Semantic Gossiping. Thus our system provides a complete solution to the implementation of semantic overlay networks supporting both scalability and interoperability. Online social networking has quickly become one of the most common Internet activities. As social networks evolve, they encourage users to share more information, requiring the users, in turn, to place more trust into social networks. In centralized systems, this means trusting a third-party commercial entity, like Facebook or MySpace. Peer-to-peer (P2P) systems can enable the creation of online social networks extending trust to friends only. In this paper, we present a novel approach to constructing completely decentralized social networks through P2P overlays, OverSoc. Our approach relies on a common directory overlay, which facilitates friend discovery and bootstraps connectivity to individualized profile overlays. Each user has their own individual profile overlay managed transparently using a public key infrastructure (PKI). We define necessary interfaces for constructing the system and describe some examples of user interactions with the system. The widespread use of peer-to-peer (P2P) systems has made multimedia content sharing more efficient. Users in a P2P network can query and download objects based on their preference for specific types of multimedia content. However, most P2P systems only construct the overlay architecture according to physical network constraints and do not take user preferences into account. In this paper, we investigate a social-based overlay that can cluster peers that have similar preferences. To construct a semantic social-based overlay, we model a quantifiable measure of similarity between peers so that those with a higher degree of similarity can be connected by shorter paths. Hence, peers can locate objects of interest from their overlay neighbors, i.e., peers who have common interests. In addition, we propose an overlay adaptation algorithm that allows the overlay to adapt to P2P churn and preference changes in a distributed manner. We use simulations and a real database called Audioscrobbler, which tracks users' listening habits, to evaluate the proposed social-based overlay. The results show that social-based overlay adaptation enables users to locate content of interest with a higher success ratio and with less message overhead.