PROJECT TITLE :

Hybrid Content Caching in 5G Wireless Networks: Cloud Versus Edge Caching - 2018

ABSTRACT:

Most existing content caching styles need accurate estimation of content popularity, which will be challenging in the dynamic mobile network atmosphere. Moreover, emerging hierarchical network design enables us to boost the content caching performance by opportunistically exploiting both cloud-centric and edge-centric caching. During this Project, we tend to propose a hybrid content caching design that does not need the information of content popularity. Specifically, our design optimizes the content caching locations, that will be original content servers, central cloud units (CUs) and base stations (BSs) where the design objective is to support as high average requested content knowledge rates as potential subject to the finite service latency. We have a tendency to fulfill this style by employing the Lyapunov optimization approach to tackle an NP-onerous caching control drawback with the tight coupling between CU caching and BS caching control selections. Toward this finish, we tend to propose algorithms in 3 specific caching eventualities by exploiting the submodularity property of the sum-weight objective function and the hierarchical caching structure. Moreover, we tend to prove the proposed algorithms can achieve finite content service delay for all arrival rates at intervals the constant fraction of capability region using Lyapunov optimization technique. Furthermore, we tend to propose practical and heuristic CU/BS caching algorithms to handle a general caching situation by inheriting the look rationale of the aforementioned performance-guaranteed algorithms. Trace-driven simulation demonstrates that our proposed hybrid CU/BS caching algorithms outperform the final popularity primarily based caching algorithm and also the freelance caching algorithm in terms of average finish-to-finish service latency and backhaul/fronthaul load reduction ratios.