End-to-end quality aware optimization for multimedia clouds

This article presents a novel, end-to-end, qualityaware optimization framework for multimedia clouds, where path selection mechanisms are exploited in conjunction with media optimization in order to support multimedia delivery in a quality-aware manner. As wireless data traffic worldwide is characterized by exponential growth, with the most prominent part being multimedia services, consumers get in the challenging position to compete for the limited wireless network resources. Cloud technologies and especially Software-Defined Networking is the perfect candidate technology in order to provide an elastic, dynamic provisioning of network resources that adapt to a highly changing environment, where application requirements and data volumes vary over time. This work combines the selection of the optimum path in the core network with quality-aware media adaptation based on the current conditions of the wireless access network. Thus the proposed framework achieves efficient network resources utilization in an end-to-end fashion

Resilience of Video Streaming Services to Network Impairments

When dealing with networks, performance management through conventional quality of service (QoS)-based methods becomes difficult and is often ineffective. In fact, quality emerges as an end-to-end factor, for it is particularly sensitive to the end-user perception of the overall service, i.e., the user's quality of experience (QoE). However, the two are not independent from each other and their relationship has to be studied through metrics that go beyond the typical network parameters. To better explore the value of assessing QoE alongside QoS in high-speed, lossy networks, this paper presents an experimental methodology to understand the relation between network QoS onto service QoE, with the aim to perform a combined network-service assessment. Using video streaming services as the test-case (given their extended usage nowadays), in this paper, we provide studies on three network-impaired video-sets with the aim to provide a comprehensive evaluation of the effects of networks on video quality. First, the ReTRIeVED video set provides the means to understand the most impairing effects on networks. Furthermore, it triggered the idea to create our own sets, specialized in the most impairing conditions for 2-D and 3-D: the LIMP Video Quality Database and the 3-D-HEVC-Net Video Quality Database. Our study and methodology are meant to provide service providers with the means to pinpoint the working boundaries of their video-sets in face of different network conditions. At the same time, network operators may use our findings to predict how network control policies affect the user's perception of the service

QoE Enhancement for Stereoscopic 3DVideo Quality Based on Depth and Color Transmission over IP Networks: A Review

In this review paper we focus on the enhancement of Quality of Experience (QoE) for stereoscopic 3D video based on depth information. We focus on stereoscopic video format because it takes less bandwidth than other format when 3D video is transmitted over an error channel but it is easily affected by the network parameters such as packets loss, delay and jitter. The packet loss on 3D video has more impact in the depth information than other 3D video factors such as comfort, motion, disparity and discomfort. The packet loss on depth information causes undesired effect on color and depth maps. Therefore, in order to minimize quality degradation, the application of frame loss concealment technique is preferred. This technique is expected to improve the QoE for end users. In this paper we will also review 3D video factors and their challenges, methods of measuring the QOE, algorithms used for packets loss recovery.

Single queue priority scheduler for video transmission in IEEE 802.11 networks

Includes bibliography.Mobile video transmission poses many challenges in standard wireless network like Wireless Local Area Network or IEEE 802.11. The challenges range from handover, delay, packet loss, jitter, fading and signal loss. Some studies have suggested an increase in network resources as a way to cater for the huge demands and reduce congestion in the network, while others suggest that optimizing the available resources might also reduce these challenges. In line with the optimization approach, this study proffers a solution to the video loss in IEEE 802.11 networks. It uses the Single-Queue Priority Scheduler to rearrange the video frames based on their importance. An MPEG frame (trace file) was rearranged by assigning weights to the video frames I, B and P. These frames were then prioritized and arranged in a single queue. A parameter to actively arrange the queue ( ) was deduced from three metrics- deadline, priority and cost. This value Sn was used to arrange the video trace or frames from the lowest to the highest. The arranged video trace or frames were injected into the queue and transmitted in that order. The results show that the implementation of Single-Queue Priority Scheduler algorithm improves the video transmission in Wireless Local Area Network. Without Single-Queue Priority Scheduler algorithm, the buffer overflow loss is 22.8% of the total load, but with SQPS algorithm, it is 8% of the total load. Without SQPS algorithm, the Packet Loss Ratio is about61%; but with the SQPS algorithm, the PLR reduces to 34%. Although, this scheduling algorithm produced better results with a reduction in packet loss, there were still some losses in the network