E³DOAS: Balancing QoE and Energy-Saving for Multi-Device Adaptation in Future Mobile Wireless Video Delivery

Abstract

Abstract-Smart devices (e.g. smartphones, tablets, smarthome devices, etc.) have become important companions to most people in their daily activities, and are very much used for multimedia content exchange (i.e. video sharing, real-time/nonreal-time multimedia streaming), contributing to the exponential increase in mobile traffic over the current wireless networks. While the next generation mobile networks will provide higher capacity than the current 4G systems, the network operators will face important challenges associated with the outstanding increase of both video traffic and user expectations in terms of their levels of perceived quality or Quality of Experience (QoE). Furthermore, the heterogeneity of mobile devices (e.g. screen resolution, battery life, hardware performance) also impacts severely the end-user QoE. In this context, this paper proposes an Evolved QoE-aware Energy-saving Device-Oriented Adaptive Scheme (E 3 DOAS ) for mobile multimedia delivery over future wireless networks. E 3 DOAS makes use of a coalition gamebased rate allocation strategy within the multi-device heterogeneous environment, and optimizes the trade-off between the end-user perceived quality of the multimedia delivery and the mobile device energy-saving. Testing has involved a prototype of E 3 DOAS , a crowd-sourcing-based QoE assessment method to model non-reference perceptual video quality, and an energy measurement testbed introduced to collect power consumption parameters of the mobile devices. Simulation-based performance evaluation showed how E 3 DOAS outperformed other state of the art multimedia adaptive solutions in terms of energy saving, endto-end Quality of Service (QoS) metrics and end-user perceived quality.

Seamless Multimedia Delivery Within a Heterogeneous Wireless Networks Environment: Are We There Yet?

“…Many studies [123], [124], [125], [126], [127], [128] have tried to understand the energy consumption pattern of different mobile devices under various conditions such as different radio access technologies, dynamic network conditions, time, mobility and applications and tried to model it mathematically. In case of multimedia-based streaming applications more energy will be consumed for de/encoding, data processing and displaying making the display screen, CPU and network interface the three major components to be the most significant energy consumers within a mobile device [123].…”

“…Considering the heterogeneity of mobile devices (e.g., screen resolution, battery life, hardware performance) Zou et al [127] proposes a mobile devices classification based on the characteristics of 4914 devices, as listed in Table VIII. For each device class, the authors make use of the utility theory A comprehensive study on the impact of the Wi-Fi networkrelated parameters (e.g., network load and signal quality level) on the power consumption of an Android mobile device in the context of video delivery is presented in [128].…”

Power Modeling for Video Streaming Applications on Mobile Devices

“…Furthermore, we take into account two different video codecs (HEVC and H.264/AVC) and find empirically that the codec only has a marginal influence on the overall power consumption. Hence, we combine (8) and (10), neglect the codec, and obtain…”

A Fuzzy Logic System for Vertical Handover and Maximizing Battery Lifetime in Heterogeneous Wireless Multimedia Networks

“…The concept of Quality of Experience (QoE) is becoming a key factor because it can measure the degree of quality of a multimedia service through the perception of the user. In other words, the satisfaction of the user can be measured through required conditions based on social psychology, cognitive science, and engineering science [3].…”