Before revision:  We start our analysis from a linear cache network: we propose a utility maximization problem where the objective is to maximize the sum of utilities and a cost minimization problem where the objective is to minimize the content transmission cost across the network . These frameworks enable us to design online algorithms for cache management, for which we prove achieving optimal performance. Informed by the results of our analysis, we formulate a non-convex optimization problem for a general cache network. We show that the duality gap is zero, hence we can develop a distributed iterative primal-dual algorithm for content management in the network. Numerical evaluations show that our algorithm significant outperforms path replication with traditional caching algorithms over some network topologies .
After revision:  We start our analysis from a linear cache network: we propose a utility maximization problem where the objective is to maximize the overall network utility. Our TTL-based optimization model provides theoretical answers to how long each content must be cached, and where it should be placed in the edge network. Extensive evaluations show that our algorithm significant outperforms path replication with traditional caching algorithms over some network topologies .