Social applications mine user social graphs to improve performance in search, provide recommendations, allow resource sharing and increase data privacy. When such applications are implemented on a peer-to-peer (P2P) architecture, the social graph is distributed on the P2P system: the traversal of the social graph translates into a socially-informed routing in the peer-to-peer layer. In this work we introduce the model of a projection graph that is the result of decentralizing a social graph onto a peer-to-peer network. We focus on three social network metrics: degree, node betweenness and edge betweenness centrality and analytically formulate the relation between metrics in the social graph and in the projection graph. Through experimental evaluation on real networks, we demonstrate that when mapping user communities of sizes up to 50-150 users on each peer, the association between the properties of the social graph and the projection graph is high, and thus the properties of the (dynamic) projection graph can be inferred from the properties of the (slower changing) social graph. Furthermore, we demonstrate with two application scenarios on large-scale social networks the usability of the projection graph in designing social search applications and unstructured P2P overlays.
The management of social data in a P2P architecture has been addressed in systems such as PeerSoN @cite_1 , Vis- a -Vis @cite_13 , Safebook @cite_31 , LifeSocial.KOM @cite_0 and Prometheus @cite_43 . In some cases (PeerSoN, Vis- a -Vis, Safebook, LifeSocial.KOM), the information of a user is isolated from other users, and peers access them individually. Thus, the @math is fragmented into 1-hop neighborhoods, one for each user, and distributed across all peers, with potentially multiple fragments stored on the same peer. In contrast, in Prometheus @cite_43 , a peer can mine the collection of social data entrusted to it by a group of (possibly socially connected) users. In all these systems, regardless of the way peers are organized in the P2P architecture (e.g., in a structured or unstructured overlay), the @math model can be applied for studying and improving system and application routing.
@cite_1 @cite_0 @cite_43 @cite_31 @cite_13
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Recent Internet applications, such as online social networks and user-generated content sharing, produce an unprecedented amount of social information, which is further augmented by location or collocation data collected from mobile phones. Unfortunately, this wealth of social information is fragmented across many different proprietary applications. Combined, it could provide a more accurate representation of the social world, and it could enable a whole new set of socially-aware applications. We introduce Prometheus, a peer-to-peer service that collects and manages social information from multiple sources and implements a set of social inference functions while enforcing user-defined access control policies. Prometheus is socially-aware: it allows users to select peers that manage their social information based on social trust and exploits naturally-formed social groups for improved performance. We tested our Prometheus prototype on PlanetLab and built a mobile social application to test the performance of its social inference functions under realtime constraints. We showed that the social-based mapping of users onto peers improves the service response time and high service availability is achieved with low overhead. This paper investigates the data exchange problem among distributed independent sources. It is based on previous works of the authors [11, 12, 14] in which a declarative semantics for P2P systems has been presented and a mechanism to set different degrees of reliability for neighbor peers has been provided. The basic semantics for P2P systems defines the concept of Maximal Weak Models (in [11, 12, 14] these models have been called Preferred Weak Models. In this paper we rename them and use the term Preferred for the subclass of Weak Model defined here) that represent scenarios in which maximal sets of facts not violating integrity constraints are imported into the peers [11, 12]. Previous priority mechanism defined in [14] is rigid in the sense that the preference between conflicting sets of atoms that a peer can import only depends on the priorities associated to the source peers at design time. In this paper we present a different framework that allows to select among different scenarios looking at the properties of data provided by the peers. The framework presented here allows to model concepts like "in the case of conflicting information, it is preferable to import data from the neighbor peer that can provide the maximum number of tuples" or "in the case of conflicting information, it is preferable to import data from the neighbor peer such that the sum of the values of an attribute is minimum" without selecting a-priori preferred peers. To enforce this preference mechanism we enrich the previous P2P framework with aggregate functions and present significant examples showing the flexibility of the new framework. 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. The field of structured P2P systems has seen fast growth upon the introduction of Distributed Hash Tables (DHTs) in the early 2000s. The first proposals, including Chord, Pastry, Tapestry, were gradually improved to cope with scalability, locality and security issues. By utilizing the processing and bandwidth resources of end users, the P2P approach enables high performance of data distribution which is hard to achieve with traditional client-server architectures. The P2P computing community is also being actively utilized for software updates to the Internet, P2PSIP VoIP, video-on-demand, and distributed backups. The recent introduction of the identifier-locator split proposal for future Internet architectures poses another important application for DHTs, namely mapping between host permanent identity and changing IP address. The growing complexity and scale of modern P2P systems requires the introduction of hierarchy and intelligence in routing of requests. Structured Peer-to-Peer Systems covers fundamental issues in organization, optimization, and tradeoffs of present large-scale structured P2P systems, as well as, provides principles, analytical models, and simulation methods applicable in designing future systems. Part I presents the state-of-the-art of structured P2P systems, popular DHT topologies and protocols, and the design challenges for efficient P2P network topology organization, routing, scalability, and security. Part II shows that local strategies with limited knowledge per peer provide the highest scalability level subject to reasonable performance and security constraints. Although the strategies are local, their efficiency is due to elements of hierarchical organization, which appear in many DHT designs that traditionally are considered as flat ones. Part III describes methods to gradually enhance the local view limit when a peer is capable to operate with larger knowledge, still partial, about the entire system. These methods were formed in the evolution of hierarchical organization from flat DHT networks to hierarchical DHT architectures, look-ahead routing, and topology-aware ranking. Part IV highlights some known P2P-based experimental systems and commercial applications in the modern Internet. The discussion clarifies the importance of P2P technology for building present and future Internet systems.