Privacy-aware Robust Proactive Content Caching using Edge Service Providers

In this paper, we propose a novel proactive content caching problem in which a set of contending edge service providers (ESPs) in a given region offer their storage and link capacities to the content provider (CP). The privacy of each contending ESP is preserved in the proposed caching problem. Each ESP independently determines the amount of storage and link capacity it can offer to the CP based on the local forecast of the content requests and its local edge resources. Unlike existing works, an ESP’s decision making problem is modeled as a robust mixed integer problem due to the uncertain storage capacity. Based on the offers made by the ESPs and its own prediction of the content requests, the CP determines the optimal content placement decisions while reserving the storage and link capacities under the ESPs in order to serve its clients at different bit rates. The CP also finds the optimal allocation of predicted requests across the ESPs. The decisions of the CP are found using a separate mixed integer problem which minimizes the payments given by the CP to the ESPs for their service. We show the impact of the robust parameter on the content placement decisions. We also perform sensitivity analysis of the CP’s decisions.