The addition of storage capacity in network nodes for the caching or replication of popular data objects results in reduced end-user delay, reduced network traffic, and improved scalability. The problem of allocating an available storage budget to the nodes of a hierarchical content distribution system is formulated; optimal algorithms, as well as fast/efficient heuristics, are developed for its solution. An innovative aspect of the presented approach is that it combines all relevant subproblems, concerning node locations, node sizes, and object placement, and solves them jointly in a single optimization step. The developed algorithms may be utilized in content distribution networks that employ either replication or caching/replacement. In addition to reducing the average fetch distance for the requested content, they also cater to load balancing and workload constraints on a given node. Strictly hierarchical, as well as hierarchical with peering, request routing models are considered.
Cache dimensioning problem is considered in REF , where Laoutaris et al. optimized the storage capacity allocation for content distribution networks under a limited total cache storage budget, so as to reduce average fetch distance for the request contents with consideration of load balancing and workload constraints on a given node.
On the optimization of storage capacity allocation for content distribution
Computer Networks
Computer Science