Energy-Efficient Joint Caching and Transcoding for HTTP Adaptive Streaming in 5G Networks with Mobile Edge Computing

Abstract

With the HTTP adaptive video streaming (HAS) transmission over mobile networks being widely concerned and the new promising technique of mobile edge computing (MEC) emerging, the problem of HAS transmission in MEC-based 5G networks has been widely studied. However, most of them focus on the issues of network resource utilization and the quality of experience (QoE) promotion, while the problem of energy efficiency is largely ignored. In this paper, different from previous works, by taking the caching and transcoding into consideration, we propose a joint caching and transcoding schedule strategy for HAS delivery in MEC-enhanced 5G network to realize the energy efficiency. We formulate the problem of energy efficient joint caching and transcoding as an integer linear programming problem to minimize the system energy consumption. Then to make the NP-hard problem tractable, we introduce a heuristic scheme based on simulated annealing algorithm to iteratively provide the global optimum solution. Finally, simulation results are illustrated to show that our proposed strategy presents an excellent performance and provides practical significance to choose proper ways of responding users' content requests according to different hit modes.