Hierarchical-Caching Based Statistical QoS Provisioning Over 5G Multimedia Big-Data Mobile Wireless Networks

As one of essential techniques to support the multimedia transmissions over the fifth generation (5G) mobile wireless networks, the statistical quality of service (QoS) provisioning has been proved to be effective in statistically guaranteeing time sensitive video transmission over time-varying wireless channels. But, how to efficiently design and implement statistical QoS provisioning enabled wireless network remains as the open challenging problem. To overcome these challenges, in this paper we propose the hierarchical-caching architecture to efficiently implement the statistical QoS guarantees in 5G wireless networks, which cooperatively caches the popular multimedia data contents at different wireless network caching tiers, efficiently trading the widely available storage resources for precious wireless bandwidth resources. However, the hierarchical caching scheme imposes the multi-hop wireless link statistical delay-bounded QoS provisioning problem when the requested multimedia data contents are fetched across tiers. In particular, we develop two hierarchical caching schemes to adaptively cache the delay bounded multimedia data contents: (1) caching in mobile users, which yields the single-hop wireless transmission and (2) caching in routers, which yields the tandem two-hop wireless transmission. To maximize the average effective capacity when cached data contents dynamically switch between these two schemes, we apply the Markov chain model to derive the optimal departure rates for data contents leaving cacheable mobile users and routers, respectively. Using these two departure rates, we develop the optimal caching schemes in terms of the probability distribution of how long to cache the data contents and the probability of where to cache the data contents. Finally, we evaluate and validate these two optimized caching schemes through numerical analyses.