Joint Cache Allocation With Incentive and User Association in Cloud Radio Access Networks Using Hierarchical Game

• Main Authors: Tra Huong Thi Le, Nguyen H. Tran, Phuong Luu Vo, Zhu Han, Mehdi Bennis, Choong Seon Hong
• Format: Article
• Language: English
• Published: IEEE 2019-01-01
• Series: IEEE Access
• Subjects: Cloud RAN; caching as a service; cache allocation; contract theory; asymmetric information; matching game
• Online Access: https://ieeexplore.ieee.org/document/8643046/

In this paper, we consider a cloud radio access network-based system consisting of one network operator (NO) and several content providers (CPs). The NO owns a cloud cache and provides caching as a service for CPs, who provide contents to users. While the NO wishes to motivate CPs to rent its cache and maximize its profit, CPs want to optimize the service performance for users and their renting utilities. Due to the time separation between cache allocation and user association problems, we model the interactions between the NO and CPs as a hierarchical game, i.e., a cache renting scheme between the NO and CPs in the cache allocation problem and the willingness of CPs in the user association problem. In the cache allocation problem, we propose a contract theory-based incentive mechanism in which the NO designs and offers an optimal contract to various types of CPs. We then formulate the user association problem as a many-to-many matching game with externalities. To solve this matching game, we propose a matching algorithm that converges to a two-sided exchange stable matching with low complexity. The simulation results demonstrate that this proposed approach is beneficial to the NO's profit and incentivize the CP to rent the cache with truthful private information. In addition, the system performance of the proposed approach in terms of the total data rate-delay tradeoff outperforms than the benchmarks.