Energy measurements for mobile cooperative video streaming

Abstract

Abstract-In a classical mobile video streaming architecture, the server is responsible for processing each request from the mobile clients even if those requests are for the same content in the same geographical area. This tends to be resource exhaustive in terms of complexity, radio resources, and energy consumption especially when delivering high bit rate multimedia content. In this paper, we exploit cooperation between network technologies to reduce the load placed on a given multimedia server and reduce the overall energy drain of mobile devices. We consider a set of mobile devices that wish to receive a common video content from a designated video server. The mobile devices organize themselves into multiple Bluetooth piconets. The master in each piconet receives an H.264 encoded video content from the server via an IEEE 802.11 WLAN access point and relays it to its slave mobile devices using standard Bluetooth connections. A prototypical implementation of the proposed model in an experimental testbed is used to perform energy and video quality measurements in real conditions. Results demonstrate notable energy consumption gains while maintaining video quality in various scenarios.

A proactive scalable approach for reliable cluster formation in wireless networks with D2D offloading

“…The devices are equipped with multiple wireless interfaces supporting long range (LR) connectivity to the APs and short range (SR) connectivity to other device over direct D2D links (e.g., WiFi-Direct, LTE-Direct, or Bluetooth). It is worth noting here that such setup may lead to notable energy savings since communications within the cluster take place over short range connections that are more energy efficient than long range links [9], [31], [32]. Moreover, we assume centralized intelligence in the network side to facilitate D2D cooperation whereby the devices are divided into clusters with one device per cluster selected as a cluster head.…”

“…Cooperation among devices has been shown to be highly effective in enhancing the performance of infrastructure-based wireless networks for a wide range of use cases; devices in the context of this work can be sensor nodes in an Internet of Things (IoT) network, mobile users in a cellular or WiFi network, or cars in a vehicular ad hoc network (VANET) [1], [2], [3], [4], [5]. Facilitating mobile-tomobile, sensor-to-sensor or car-to-car (all denoted as deviceto-device (D2D) in the sequel) cooperation can lead to traffic offloading, throughput enhancement, energy consumption savings, coverage extension, and/or cost reduction, e.g., see [6], [7], [8], [9] and the references therein.…”

An Energy-Aware Framework for Reliable and Secure End-to-End Ubiquitous Data Communications

“…The overall energy drained by the transmission layer, is hence given by the sum of fixed and variable energy consumptions of all its network interfaces, subject to the current network load. Some reference values about the transmission-related power consumption of mobile terminals, have been presented in [52], [54], [55], [56] for cellular, Wi-Fi and Bluetooth technologies. An excerpt of these data, is reported, for the sake of completeness, in Table IV.…”

Social‐Aware Device‐to‐Device Offloading Based on Experimental Mobility and Content Similarity Models

“…Data sharing over device-to-device (D2D) links has been shown to provide a multitude of performance gains in terms of throughput and spectral efficiency enhancement [4][5][6], energy consumption reduction [7][8][9][10], and end user cost savings and incentives [11][12][13]. However, reliable and efficient D2D data sharing in practice hinges on several factors that include content availability, users' proximity and ability to connect to each other, users' mobility patterns, and contact intervals [14], in addition to other aspects such as cooperation incentives and trust establishment [15,16].…”