A community‐based social P2P network for sharing human life digital memories

Social peer‐to‐peer (P2P) networks are usually designed by reflecting a user's interest/behavior for structuring the underlying network. Human interest is affected by various factors such as age, locality, and so on which changes after some time. The behavior when reflected in a network, results in peers moving within the network in order to connect the peer with peers of the same behavior/interest. Especially in community‐based schemes when a peer leaves a community the data that a peer was sharing will not be accessible in the same community anymore. It has an effect on the performance of the network due to the inaccessibility of data and the unavailability of connections, which affect network robustness. We address this issue by considering entities in data in the form of digital memories of a user and structuring network according to entity‐based communities. The simulation results for the proposed entity‐based community are demonstrated, which shows the effect on network performance during varying network size and traffic

Understanding community patterns in large attributed social networks

none3siThere is an inherent presence of communities in online social networks. These communities can be defined based on i) link structure or ii) the attributes of individuals. Attributes can indicate as interests in specific topics, like science-fiction books or romantic movies, or more in general their explicit affiliation to a group inside the network. In this paper, we analyze community structures as defined by how people are associated to third concepts like attributes. To understand the community patterns we analyze three large and one small social network datasets. Our analysis shows that, irrespective of the number of nodes for any particular interest in the network, at least 50% of the nodes are part of the same connected component in the graph induced by each interest. Another interesting result of our analysis is that the majority of sub-communities (50% or above) for any interest are separated by small hops (two to three) from each other.mixedSharma, Rajesh; Magnani, Matteo; Montesi, DaniloSharma, Rajesh; Magnani, Matteo; Montesi, Danil