Optimal and Scalable Distribution of Content Updates over a Mobile Social Network

We study the dissemination of dynamic content, such as news or traffic information, over a mobile social network. In this application, mobile users subscribe to a dynamic-content distribution service, offered by their service provider. To improve coverage and increase capacity, we assume that users share any content updates they receive with other users they meet. We make two contributions. First, we determine how the service provider can allocate its bandwidth optimally to make the content at users as "fresh" as possible. More precisely, we define a global fairness objective (namely, maximizing the aggregate utility over all users) and prove that the corresponding optimization problem can be solved by gradient descent. Second, we specify a condition under which the system is highly scalable: even if the total bandwidth dedicated by the service provider remains fixed, the expected content age at each user grows slowly (as log(n)) with the number of users n. To the best of our knowledge, our work is the first to address these two aspects (optimality and scalability) of the distribution of dynamic content over a mobile social network.