Saving Energy in Mobile Devices for On-Demand Multimedia Streaming -- A Cross-Layer Approach

This paper proposes a novel energy-efficient multimedia delivery system called EStreamer. First, we study the relationship between buffer size at the client, burst-shaped TCP-based multimedia traffic, and energy consumption of wireless network interfaces in smartphones. Based on the study, we design and implement EStreamer for constant bit rate and rate-adaptive streaming. EStreamer can improve battery lifetime by 3x, 1.5x and 2x while streaming over Wi-Fi, 3G and 4G respectively.Comment: Accepted in ACM Transactions on Multimedia Computing, Communications and Applications (ACM TOMCCAP), November 201

Service Migration from Cloud to Multi-tier Fog Nodes for Multimedia Dissemination with QoE Support.

A wide range of multimedia services is expected to be offered for mobile users via various wireless access networks. Even the integration of Cloud Computing in such networks does not support an adequate Quality of Experience (QoE) in areas with high demands for multimedia contents. Fog computing has been conceptualized to facilitate the deployment of new services that cloud computing cannot provide, particularly those demanding QoE guarantees. These services are provided using fog nodes located at the network edge, which is capable of virtualizing their functions/applications. Service migration from the cloud to fog nodes can be actuated by request patterns and the timing issues. To the best of our knowledge, existing works on fog computing focus on architecture and fog node deployment issues. In this article, we describe the operational impacts and benefits associated with service migration from the cloud to multi-tier fog computing for video distribution with QoE support. Besides that, we perform the evaluation of such service migration of video services. Finally, we present potential research challenges and trends

DyPS: Dynamic Processor Switching for Energy-Aware Video Decoding on Multi-core SoCs

In addition to General Purpose Processors (GPP), Multicore SoCs equipping modern mobile devices contain specialized Digital Signal Processor designed with the aim to provide better performance and low energy consumption properties. However, the experimental measurements we have achieved revealed that system overhead, in case of DSP video decoding, causes drastic performances drop and energy efficiency as compared to the GPP decoding. This paper describes DyPS, a new approach for energy-aware processor switching (GPP or DSP) according to the video quality . We show the pertinence of our solution in the context of adaptive video decoding and describe an implementation on an embedded Linux operating system with the help of the GStreamer framework. A simple case study showed that DyPS achieves 30% energy saving while sustaining the decoding performanc

Design and evaluation of a DASH-compliant second screen video player for live events in mobile scenarios

The huge diffusion of mobile devices is rapidly changing the way multimedia content is consumed. Mobile devices are often used as a second screen, providing complementary information on the content shown on the primary screen, as different camera angles in case of a sport event. The introduction of multiple camera angles poses many challenges with respect to guaranteeing a high Quality of Experience to the end user, especially when the live aspect, different devices and highly variable network conditions typical of mobile environments come into play. Due to the ability of HTTP Adaptive Streaming (HAS) protocols to dynamically adapt to bandwidth fluctuations, they are especially suited for the delivery of multimedia content in mobile environments. In HAS, each video is temporally segmented and stored in different quality levels. Rate adaptation heuristics, deployed at the video player, allow the most appropriate quality level to be dynamically requested, based on the current network conditions. Recently, a standardized solution has been proposed by the MPEG consortium, called Dynamic Adaptive Streaming over HTTP (DASH). We present in this paper a DASH-compliant iOS video player designed to support research on rate adaptation heuristics for live second screen scenarios in mobile environments. The video player allows to monitor the battery consumption and CPU usage of the mobile device and to provide this information to the heuristic. Live and Video-on-Demand streaming scenarios and real-time multi-video switching are supported as well. Quantitative results based on real 3G traces are reported on how the developed prototype has been used to benchmark two existing heuristics and to analyse the main aspects affecting battery lifetime in mobile video streaming