mobile dynamic content distribution networks
Mobile networks are becoming increasingly popular as means for distributing inform tion to large number of users. In comparison to wired networks, mobile networks distinguished by potentially much higher variability in demand due to user mobility. Most previous content techniques ssume static client demand distribution and, thus, may not perform well in mobile networks.This paper proposes and analyzes Mobile Dynamic Content Distribution Network model, which takes demand variations into account to decide whether to replicate 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, which provides an ideal lower-bound on the total traffic, and practical heuristic online algorithm, which uses demand forecasting to make replication decisions. We provide 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 the ACDN one, reducing total network traffic by up to 85\% in a number of experiments covering large system design space.
mobile network online algorithm demand forecasting dynamic content placement cdn simulation