Joint optimization of caching and transport in proactive edge cloud

Our goal in this paper is to devise a strategy for finding the optimal trade-off between the transport and caching energy costs associated to the delivery of contents in information networks. The proposed strategy is proactive with respect to the users' requests, as contents are pre-fetched depending on the distribution of their (estimated) popularity. In particular, we propose a k-center dominating set strategy to find the optimal clustering and then locate the best places to store/replicate the most popular contents. Then we develop a dynamic energy-efficient, strategy that jointly optimizes caching and delivery costs within each cluster. Although the formulated problem is a binary problem, we will show as it can be solved for moderate size networks by using efficient solvers. The performance gain reached through the proposed proactive strategy are then assessed by numerical results.