Social relationships are a natural basis on which humans make trust decisions. Online Social Networks (OSNs) are increasingly often used to let users base trust decisions on the existence and the strength of social relationships. While most OSNs allow users to discover the length of the social path to other users, they do so in a centralized way, thus requiring them to rely on the service provider and reveal their interest in each other. This paper presents Social PaL, a system supporting the privacy-preserving discovery of arbitrary-length social paths between any two social network users. We overcome the bootstrapping problem encountered in all related prior work, demonstrating that Social PaL allows its users to find all paths of length two and to discover a significant fraction of longer paths, even when only a small fraction of OSN users is in the Social PaL system - e.g., discovering 70 of all paths with only 40 of the users. We implement Social PaL using a scalable server-side architecture and a modular Android client library, allowing developers to seamlessly integrate it into their apps.
@cite_14 present a routing protocol (called SimBet) for DTN networks based on social network data. Their protocol attempts to identify a routing bridge node based on the concept of centrality and transitivity of social networks. @cite_31 design another DTN routing protocol (called Social Selfishness Aware Routing) which takes into account user's social selfishness and willingness to forward data only to nodes with sufficiently strong social ties. Other work @cite_24 @cite_48 @cite_27 also propose adjusting message forwarding based on some social metrics.
@cite_14 @cite_48 @cite_24 @cite_27 @cite_31
2017478515 2078129565 2082674813 2155528675
In the past few years, more and more researchers have paid close attention to the emerging field of delay tolerant networks (DTNs), in which network often partitions and end-to-end paths do not exist nearly all the time. To cope with these challenges, most routing protocols employ the "store-carry-forward" strategy to transmit messages. However, the difficulty of this strategy is how to choose the best relay node and determine the best time to forward messages. Fortunately, social relations among nodes can be used to address these problems. In this paper, we present a comprehensive survey of recent social-aware routing protocols, which offer an insight into how to utilize social relationships to design efficient and applicable routing algorithms in DTNs. First, we review the major practical applications of DTNs. Then, we focus on understanding social ties between nodes and investigating some design-related issues of social-based routing approaches, e.g., the ways to obtain social relations among nodes, the metrics and approaches to identify the characteristics of social ties, the strategies to optimize social-aware routing protocols, and the suitable mobility traces to evaluate these protocols. We also create a taxonomy for social-aware routing protocols according to the sources of social relations. Finally, we outline several open issues and research challenges. Delay-tolerant network architectures exploit mobile devices carried by users to enable new networked applications. Efficiently routing information through these DTNs faces new challenges such as mobility and the dynamic nature of the network. Previous work has looked at using encountered nodes to build a social network for routing. In this work we construct routing tables from users' self-reported social networks. Initial experiments indicate that this significantly reduces the delivery cost of transmitting messages through a DTN. Message delivery in sparse Mobile Ad hoc Networks (MANETs) is difficult due to the fact that the network graph is rarely (if ever) connected. A key challenge is to find a route that can provide good delivery performance and low end-to-end delay in a disconnected network graph where nodes may move freely. This paper presents a multidisciplinary solution based on the consideration of the so-called small world dynamics which have been proposed for economy and social studies and have recently revealed to be a successful approach to be exploited for characterising information propagation in wireless networks. To this purpose, some bridge nodes are identified based on their centrality characteristics, i.e., on their capability to broker information exchange among otherwise disconnected nodes. Due to the complexity of the centrality metrics in populated networks the concept of ego networks is exploited where nodes are not required to exchange information about the entire network topology, but only locally available information is considered. Then SimBet Routing is proposed which exploits the exchange of pre-estimated "betweenness' centrality metrics and locally determined social "similarity' to the destination node. We present simulations using real trace data to demonstrate that SimBet Routing results in delivery performance close to Epidemic Routing but with significantly reduced overhead. Additionally, we show that SimBet Routing outperforms PRoPHET Routing, particularly when the sending and receiving nodes have low connectivity. The routing performance of delay tolerant networks (DTN) is highly correlated with the distribution of inter-contact times (ICT), the time period between two successive contacts of the same two mobile nodes. As humans are often carriers of mobile communication devices, studying the patterns of human mobility is an essential tool to understand the performance of DTN protocols. From measurement studies of human contact behaviors, we find that their distributions closely resemble a form of power-law distributions called truncated Pareto. Human walk traces has a dichotomy distribution pattern of ICT; it has a power-law tendency up to some time, and decays exponentially after that time. Truncated Pareto distributions offer a simple yet cohesive mathematical model to express this dichotomy in the measured data. Using the residual and relaxation time theory [17] [4], we apply truncated Pareto distributions to quantify the performance of opportunistic routing in DTN. We further show that Truncated Levy walk (TLW) mobility model [22] commonly used in biology to describe the foraging patterns of animals [25], provide the same truncated power-law ICT distributions as observed from the empirical data, especially when mobility is confined within a finite area. This result confirms our recent finding that human walks contain similar statistical characteristics as Levy walks [22].