A Decomposition Framework for Optimal Edge-Cache Leasing

International audienceCaching popular content at the wireless edge promises performance benefits as well as business perspectives. In this work we study the following arrangement: a Mobile Network Operator (MNO) pre-installs memory on its wireless equipment, sets a price, and invites a unique Content Provider (CP) to invest. The CP leases memory space and places its content; the MNO then associates network users to stations, aiming for offloading CP traffic or not. We formulate an optimization problem, which maximizes offloading with minimum leasing costs for the CP. This is an NP-hard mixed-integer non-linear optimization problem. We present an iterative exact solution using Generalized Benders decomposition into a content-related Master problem and a user-association Slave problem. Master is integer linear. Slave is convex for various association policies, including (1) join-the-closest-cache, and (2) cache-aware association. For Slave, we introduce a distributed exact solution, named Generalized Bucket-filling. Extensive simulations illustrate the performance benefits under different association policies. The solution helps to determine the optimal leasing price for the MNO, and the optimal investment budget for the CP. As a general conclusion, both actors profit when the MNO association supports CP decisions