Energy-Aware Caching Policy Design Under Heterogeneous Interests and Sharing Willingness

By exploiting the storage resources of end devices, local caching becomes a promising approach to reduce the latency and improve the throughput of content delivery. Considering battery constraints at end devices, this paper investigates energy-aware caching policy to minimize the power consumed in content delivery, taking into account the heterogeneity of interests and sharing willingness of different MSs. Specifically, MSs are divided into disjoint groups based on the preferences and sharing willingness, and each group customizes the caching policy accordingly. Both the non-coordinated and coordinated caching scenarios are considered. For the non-coordinated case, the problem is formulated as an optimization problem, which is proved to be concave and solved by Lagrange methods. For the coordinated caching case, a water-filling based iterative algorithm is proposed to get the optimal caching policies. Numerical results demonstrate that the designed caching policies can reduce the system energy consumption by around 10% - 20% comparing to the conventional ones without considering the heterogeneity of users.