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Mobile networks are becoming increasingly popular in enterprise environments as a means for distributing information to a large community of highly dynamic users. In comparison to traditional wired networks, mobile networks are distinguished by a potentially much higher variability in users demand due to user mobility. Most previous content distribution techniques assume a static user demand distribution and, thus, may not perform well in mobile networks. This paper proposes and analyzes a mobile dynamic content distribution network model, which takes demand variations into account to decide whether to replicate a content and whether to remove previously created replicas in order to minimize total network traffic. We develop two solutions to our model: an offline optimal solution, which provides an ideal lower bound on the total traffic, and a practical heuristic online algorithm, which uses demand forecasting to make replication decisions. We provide a thorough evaluation of our solutions, comparing them against ACDN, the only previous dynamic content placement algorithm targeting bandwidth minimization that we are aware of. Our results show that our online algorithm significantly outperforms ACDN, reducing total network traffic by up to 85% in a number of experiments covering a large system design space.