Real-world traffic analysis and joint caching and scheduling for in-RAN caching networks

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This paper analyzes the traffic of a current LTE network in China and investigates the joint optimization of content object caching and scheduling for in-radio access network (RAN) caches. Cooperative caching has been well recognized as a way of unleashing the ultimate potential of in-RAN caches, yet its feasibility is still unexplored. Moreover, content object caching and scheduling are two key issues for cache deployment, which are usually jointly considered and resolved. However, they are triggered by different events with different time granularities. Therefore, on the basis of the real-world dataset, the feasibility of in-RAN cooperative caching is proved from aspects of network topology, traffic load difference among small base stations (SBSs) and correlation analysis of content objects requested at different SBSs. Then, it is verified that different time scales should be considered in making content object caching and scheduling decisions. To exploit in-RAN cooperative caching while meeting the time scale requirement in making caching and scheduling decisions, an optimization problem is constructed considering practical transmission constraints in wireless and backhaul. It is proved to be a quadratic assignment problem, and then, a joint caching, and wireless and backhaul scheduling algorithm is proposed based on Lagrangian relaxation and decomposition, and hastening branch and bound. The performance of the proposed algorithm is evaluated based on the real-world dataset. Results depict the relationship among the cache capacity, the number of SBSs, the connection probability of SBSs and the objective performance, and show that the proposed algorithm can achieve better performance, compared with the existing algorithms.