A novel traffic rate measurement algorithm for quality of experience-aware video admission control

With the inevitable dominance of video traffic on the Internet, providing perceptually good video quality is becoming a challenging task. This is partly due to the bursty nature of video traffic, changing network conditions and limitations of network transport protocols. This growth of video traffic has made Quality of Experience (QoE) of the end user the focus of the research community. In contrast, Internet service providers are concerned about maximizing revenue by accepting as many sessions as possible, as long as customers remain satisfied. However, there is still no entirely satisfactory admission algorithm for flows with variable rate. The trade-off between the number of sessions and perceived QoE can be optimized by exploiting the bursty nature of video traffic. This paper proposes a novel algorithm to determine the upper limit of the aggregate video rate that can exceed the available bandwidth without degrading the QoE of accepted video sessions. A parameter Beta that defines the exceedable limit is defined. The proposed algorithm results in accepting more sessions without compromising the QoE of on-going video sessions. Thus it contributes to the optimization of the QoE-Session trade-off in support of the expected growth of video traffic on the Internet

Cross-layer optimisation of quality of experience for video traffic

Realtime video traffic is currently the dominant network traffic and is set to increase in volume for the foreseeable future. As this traffic is bursty, providing perceptually good video quality is a challenging task. Bursty traffic refers to inconsistency of the video traffic level. It is at high level sometimes while is at low level at some other times. Many video traffic measurement algorithms have been proposed for measurement-based admission control. Despite all of this effort, there is no entirely satisfactory admission algorithm for variable rate flows. Furthermore, video frames are subjected to loss and delay which cause quality degradation when sent without reacting to network congestion. The perceived Quality of Experience (QoE)-number of sessions trade-off can be optimised by exploiting the bursty nature of video traffic. This study introduces a cross-layer QoE-aware optimisation architecture for video traffic. QoE is a measure of the user's perception of the quality of a network service. The architecture addresses the problem of QoE degradation in a bottleneck network. It proposes that video sources at the application layer adapt their rate to the network environment by dynamically controlling their transmitted bit rate. Whereas the edge of the network protects the quality of active video sessions by controlling the acceptance of new sessions through a QoE-aware admission control. In particular, it seeks the most efficient way of accepting new video sessions and adapts sending rates to free up resources for more sessions whilst maintaining the QoE of the current sessions. As a pathway to the objective, the performance of the video flows that react to the network load by adapting the sending rate was investigated. Although dynamic rate adaptation enhances the video quality, accepting more sessions than a link can accommodate will degrade the QoE. The video's instantaneous aggregate rate was compared to the average aggregate rate which is a calculated rate over a measurement time window. It was found that there is no substantial difference between the two rates except for a small number of video flows, long measurement window, or fast moving contents (such as sport), in which the average is smaller than the instantaneous rate. These scenarios do not always represent the reality. The finding discussed above was the main motivation for proposing a novel video traffic measurement algorithm that is QoE-aware. The algorithm finds the upper limit of the video total rate that can exceed a specific link capacity without the QoE degradation of ongoing video sessions. When implemented in a QoE-aware admission control, the algorithm managed to maintain the QoE for a higher number of video session compared to the calculated rate-based admission controls such as the Internet Engineering Task Force (IETF) standard Pre-Congestion Notification (PCN)-based admission control. Subjective tests were conducted to involve human subjects in rating of the quality of videos delivered with the proposed measurement algorithm. Mechanisms proposed for optimising the QoE of video traffic were surveyed in detail in this dissertation and the challenges of achieving this objective were discussed. Finally, the current rate adaptation capability of video applications was combined with the proposed QoE-aware admission control in a QoE-aware cross-layer architecture. The performance of the proposed architecture was evaluated against the architecture in which video applications perform rate adaptation without being managed by the admission control component. The results showed that our architecture optimises the mean Mean Opinion Score (MOS) and number of successful decoded video sessions without compromising the delay. The algorithms proposed in this study were implemented and evaluated using Network Simulator-version 2 (NS-2), MATLAB, Evalvid and Evalvid-RA. These software tools were selected based on their use in similar studies and availability at the university. Data obtained from the simulations was analysed with analysis of variance (ANOVA) and the Cumulative Distribution Functions (CDF) for the performance metrics were calculated. The proposed architecture will contribute to the preparation for the massive growth of video traffic. The mathematical models of the proposed algorithms contribute to the research community

Joint in-network video rate adaptation and measurement-based admission control: algorithm design and evaluation

The important new revenue opportunities that multimedia services offer to network and service providers come with important management challenges. For providers, it is important to control the video quality that is offered and perceived by the user, typically known as the quality of experience (QoE). Both admission control and scalable video coding techniques can control the QoE by blocking connections or adapting the video rate but influence each other's performance. In this article, we propose an in-network video rate adaptation mechanism that enables a provider to define a policy on how the video rate adaptation should be performed to maximize the provider's objective (e.g., a maximization of revenue or QoE). We discuss the need for a close interaction of the video rate adaptation algorithm with a measurement based admission control system, allowing to effectively orchestrate both algorithms and timely switch from video rate adaptation to the blocking of connections. We propose two different rate adaptation decision algorithms that calculate which videos need to be adapted: an optimal one in terms of the provider's policy and a heuristic based on the utility of each connection. Through an extensive performance evaluation, we show the impact of both algorithms on the rate adaptation, network utilisation and the stability of the video rate adaptation. We show that both algorithms outperform other configurations with at least 10 %. Moreover, we show that the proposed heuristic is about 500 times faster than the optimal algorithm and experiences only a performance drop of approximately 2 %, given the investigated video delivery scenario

Cross-layer design of multi-hop wireless networks

MULTI -hop wireless networks are usually defined as a collection of nodes equipped with radio transmitters, which not only have the capability to communicate each other in a multi-hop fashion, but also to route each others’ data packets. The distributed nature of such networks makes them suitable for a variety of applications where there are no assumed reliable central entities, or controllers, and may significantly improve the scalability issues of conventional single-hop wireless networks. This Ph.D. dissertation mainly investigates two aspects of the research issues related to the efficient multi-hop wireless networks design, namely: (a) network protocols and (b) network management, both in cross-layer design paradigms to ensure the notion of service quality, such as quality of service (QoS) in wireless mesh networks (WMNs) for backhaul applications and quality of information (QoI) in wireless sensor networks (WSNs) for sensing tasks. Throughout the presentation of this Ph.D. dissertation, different network settings are used as illustrative examples, however the proposed algorithms, methodologies, protocols, and models are not restricted in the considered networks, but rather have wide applicability. First, this dissertation proposes a cross-layer design framework integrating a distributed proportional-fair scheduler and a QoS routing algorithm, while using WMNs as an illustrative example. The proposed approach has significant performance gain compared with other network protocols. Second, this dissertation proposes a generic admission control methodology for any packet network, wired and wireless, by modeling the network as a black box, and using a generic mathematical 0. Abstract 3 function and Taylor expansion to capture the admission impact. Third, this dissertation further enhances the previous designs by proposing a negotiation process, to bridge the applications’ service quality demands and the resource management, while using WSNs as an illustrative example. This approach allows the negotiation among different service classes and WSN resource allocations to reach the optimal operational status. Finally, the guarantees of the service quality are extended to the environment of multiple, disconnected, mobile subnetworks, where the question of how to maintain communications using dynamically controlled, unmanned data ferries is investigated

Advanced solutions for quality-oriented multimedia broadcasting

Multimedia content is increasingly being delivered via different types of networks to viewers in a variety of locations and contexts using a variety of devices. The ubiquitous nature of multimedia services comes at a cost, however. The successful delivery of multimedia services will require overcoming numerous technological challenges many of which have a direct effect on the quality of the multimedia experience. For example, due to dynamically changing requirements and networking conditions, the delivery of multimedia content has traditionally adopted a best effort approach. However, this approach has often led to the end-user perceived quality of multimedia-based services being negatively affected. Yet the quality of multimedia content is a vital issue for the continued acceptance and proliferation of these services. Indeed, end-users are becoming increasingly quality-aware in their expectations of multimedia experience and demand an ever-widening spectrum of rich multimedia-based services. As a consequence, there is a continuous and extensive research effort, by both industry and academia, to find solutions for improving the quality of multimedia content delivered to the users; as well, international standards bodies, such as the International Telecommunication Union (ITU), are renewing their effort on the standardization of multimedia technologies. There are very different directions in which research has attempted to find solutions in order to improve the quality of the rich media content delivered over various network types. It is in this context that this special issue on broadcast multimedia quality of the IEEE Transactions on Broadcasting illustrates some of these avenues and presents some of the most significant research results obtained by various teams of researchers from many countries. This special issue provides an example, albeit inevitably limited, of the richness and breath of the current research on multimedia broadcasting services. The research i- - ssues addressed in this special issue include, among others, factors that influence user perceived quality, encoding-related quality assessment and control, transmission and coverage-based solutions and objective quality measurements

Final report on the evaluation of RRM/CRRM algorithms

Deliverable public del projecte EVERESTThis deliverable provides a definition and a complete evaluation of the RRM/CRRM algorithms selected in D11 and D15, and evolved and refined on an iterative process. The evaluation will be carried out by means of simulations using the simulators provided at D07, and D14.Preprin