The budgeted maximum coverage problem
Information Processing Letters
Mining the network value of customers
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Maximizing the spread of influence through a social network
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Multicasting in delay tolerant networks: semantic models and routing algorithms
Proceedings of the 2005 ACM SIGCOMM workshop on Delay-tolerant networking
Analysis and implications of student contact patterns derived from campus schedules
Proceedings of the 12th annual international conference on Mobile computing and networking
Study of a bus-based disruption-tolerant network: mobility modeling and impact on routing
Proceedings of the 13th annual ACM international conference on Mobile computing and networking
Opportunistic spatial gossip over mobile social networks
Proceedings of the first workshop on Online social networks
Gossiping (via mobile?) in social networks
Proceedings of the fifth international workshop on Foundations of mobile computing
Predict and relay: an efficient routing in disruption-tolerant networks
Proceedings of the tenth ACM international symposium on Mobile ad hoc networking and computing
Multicasting in delay tolerant networks: a social network perspective
Proceedings of the tenth ACM international symposium on Mobile ad hoc networking and computing
Mobile Data Offloading through Opportunistic Communications and Social Participation
IEEE Transactions on Mobile Computing
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Information propagation in delay tolerant networks (DTN) is difficult due to the lack of continues connectivity. Most of previous work put their focus on the information propagation in static network. In this work, we examine two closely related problems on information propagation in predicable DTN. In particular, we assume that during a certain time period, the interacting process among nodes is known a priori or can be predicted. The first problem is to select a set of initial source nodes, subject to budget constraint, in order to maximize the total weight of nodes that receive the information at the final stage. This problem is well-known influence maximization problem which has been extensively studied for static networks. The second problem we want to study is minimum cost initial set problem, in this problem, we aim to select a set of source nodes with minimum cost such that all the other nodes can receive the information with high probability. We conduct extensive experiments using $10,000$ users from real contact trace.