Quality utility modelling for multimedia applications for Android mobile devices

With the advances in mobile technologies, smart mobile computing devices have become increasingly affordable and powerful, leading to a significant growth in both the number of advanced mobile users and their bandwidth demands. Moreover multimedia streaming to these high-end mobile devices has become widespread. However, multimedia applications are known to be resource-hungry and in order to cope with this explosion of data traffic, operators have started deploying different, overlapping radio access network technologies. One important challenge in such a heterogeneous wireless environment is to ensure an Always Best Experience to the mobile user, anywhere and anytime. This paper proposes the Quality Utility, a realistic mapping function of the received bandwidth to user satisfaction for multimedia streaming applications. The Quality Utility is mapped to a Google Nexus One Android Mobile device and validated through objective and subjective tests

An innovative machine learning-based scheduling solution for improving live UHD video streaming quality in highly dynamic network environments

The latest advances in terms of network technologies open up new opportunities for high-end applications, including using the next generation video streaming technologies. As mobile devices become more affordable and powerful, an increasing range of rich media applications could offer a highly realistic and immersive experience to mobile users. However, this comes at the cost of very stringent Quality of Service (QoS) requirements, putting significant pressure on the underlying networks. In order to accommodate these new rich media applications and overcome their associated challenges, this paper proposes an innovative Machine Learning-based scheduling solution which supports increased quality for live omnidirectional (360◦) video streaming. The proposed solution is deployed in a highly dy-namic Unmanned Aerial Vehicle (UAV)-based environment to support immersive live omnidirectional video streaming to mobile users. The effectiveness of the proposed method is demonstrated through simulations and compared against three state-of-the-art scheduling solutions, such as: Static Prioritization (SP), Required Activity Detection Scheduler (RADS) and Frame Level Scheduler (FLS). The results show that the proposed solution outperforms the other schemes involved in terms of PSNR, throughput and packet loss rate

A utility-based priority scheduling scheme for multimedia delivery over LTE networks

With the mobile networks migrating towards LTE-Advanced and all-IP networks, people expect to connect to the Internet anytime, anywhere and from any IP-connected device. Moreover, nowadays people tend to spend much of their time consuming multimedia content from various devices with heterogeneous characteristics (e.g., TV screen, laptop, tablet, smartphone, etc.). In order to support uninterrupted, continuous, and smooth video streaming with reduced delay, jitter, and packet loss to their customers, network operators must be able to differentiate between their offerings according to device characteristics, including screen resolution. This paper proposes a novel Utility-based Priority Scheduling (UPS) algorithm which considers device differentiation when supporting high quality delivery of multimedia services over LTE networks. The priority decision is based on device classification, mobile device energy consumption and multimedia stream tolerance to packet loss ratio. Simulation results demonstrate the benefits of the proposed priority-based scheduling algorithm in comparison with two classic approaches

On the impact of wireless network traffic location and access technology on the mobile device energy consumption

In the context of wireless user’s increasing demands for better device power and battery management, this paper investigates some factors that can impact the power consumption on the energy consumption of mobile devices. The focus is on two factors when performing multimedia streaming: the impact of the traffic location within a WLAN; and the impact of the radio access network technology (WLAN, HSDPA, UMTS). The energy measurement results show that by changing the quality level of the multimedia stream the energy can be greatly conserved while the user perceived quality level is still acceptable. Moreover, by using the cellular interface much more energy is consumed (up to 61%) than by using the WLAN interface

Power-friendly access network selection strategy for heterogeneous wireless multimedia networks

Apart from the number and types of applications available to users of diverse devices with various characteristics, a highly relevant issue in current and future wireless environment is the coexistence of multiple networks supported by various access technologies deployed by different operators. In this context, the aim is to keep the mobile users “always best connected” anywhere and anytime in such a multi-technology multi-application multi-terminal multi-user environment. Multimedia streaming to battery powered mobile devices has become widespread. However, the battery power capability has not kept up with the advances in other technologies and it is rapidly becoming a concern. Since multimedia applications are known to be high energy consumers and since the battery lifetime is an important factor for mobile users, this paper proposes a network selection algorithm which bases its decision on the estimated energy consumption. The proposed solution enables the multimedia stream to last longer while maintaining an acceptable user perceived quality by selecting the least power consuming network

Reputation-based network selection solution for improved video delivery quality in heterogeneous wireless network environments

The continuous innovations and advances in both high-end mobile devices and wireless communication technologies have increased the users demand and expectations for anywhere, anytime, any device high quality multimedia applications provisioning. Moreover, the heterogeneity of the wireless network environment offers the possibility to the mobile user to select between several available radio access network technologies. However, selecting the network that enables the best user perceived video quality is not trivial given that in general the network characteristics vary widely not only in time but also depending on the user location within each network. In this context, this paper proposes a user location-aware reputation-based network selection solution which aims at improving the video delivery in a heterogeneous wireless network environment by selecting the best value network. Network performance is regularly monitored and evaluated by the currently connected users in different areas of each individual network. Based on the existing network performance-related information and mobile user location and speed, the network that offers the best support for video delivery along the user’s path is selected as the target network and the handover is triggered. The simulation results show that the proposed solution improves the video delivery quality in comparison with the case when a classic network selection mechanism was employed

Performance of an adaptive multimedia mechanism in a wireless multi-user environment

With the increasing popularity of accessing multimedia services over different wireless networks, researchers have been trying to develop different adaptive multimedia mechanisms in order to mitigate the impact of fluctuating radio resources. This paper considers the case when multiple users stream video over the same IEEE 802.11b WLAN using a newly proposed Signal Strength-based Adaptive Multimedia Delivery Mechanism (SAMMy). SAMMy makes use of the IEEE 802.11k standard and uses estimated signal strength, location, and packet loss as part of its adaptive mechanism in order to increase user perceived quality for multimedia streaming applications in wireless networks. SAMMy is evaluated by modeling and simulations and compared with another adaptive multimedia delivery mechanism TFRC, in terms of aggregate throughput and fairness. The results show that the proposed signal strengthbased adaptive multimedia delivery scheme outperforms the other scheme in terms of both throughput and fairness when performing video streaming in WLAN