EDASH: Energy-Aware QoE Optimization for Adaptive Video Delivery over LTE Networks

Dynamic adaptive streaming over HTTP (DASH) has emerged as a popular Internet video service, constituting a growing fraction of LTE network traffic today. We identify the root causes of DASH performance problems in bit-ate stability, energy consumption of User Equipment (UE) and efficiency of bandwidth utilization, from both the users' and network operators' perspectives. Unlike the existing researches that separately studied two important performance metrics in DASH, i.e., Quality of Experience (QoE) and UEs' energy consumption. We propose an energy-aware DASH delivery framework over LTE networks (EDASH), jointly optimizing the network throughput, users' QoE and UEs' energy efficiency. We formulate the bandwidth allocation problem as a nonlinear integer program, and design the EDASH Online Allocation algorithm (EOA). EOA assigns bandwidth based on channel conditions and buffer occupancy of UEs to achieve efficient video delivery among multiple users. Furthermore, we present the detailed design and implementation of EDASH using Apache HTTP server and Android smartphones. Both simulation and experiment results reveal that our scheme can improve the network throughput while striking a better balance between users' QoE and UEs' energy consumption.

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