H264 data partitioned video streaming

Motivated by the increasing demand and challenges of video streaming in this thesis, we investigate methods by which the quality of the video can be improved. We utilise overlay networks that have been created by implemented relay nodes to produce path diversity, and show through analytical and simulation models for which environments path diversity can improve the packet loss probability. We take the simulation and analytical models further by implementing a real overlay network on top of Planetlab, and show that when the network conditions remain constant the video quality received by the client can be improved. In addition, we show that in the environments where path diversity improves the video quality forward error correction can be used to further enhance the quality. We then investigate the effect of IEEE 802.11e Wireless LAN standard with quality of service enabled on the video quality received by a wireless client. We find that assigning all the video to a single class outperforms a cross class assignment scheme proposed by other researchers. The issue of virtual contention at the access point is also examined. We increase the intelligence of our relay nodes and enable them to cache video, in order to maximise the usefulness of these caches. For this purpose, we introduce a measure, called the PSNR profit, and present an optimal caching method for achieving the maximum PSNR profit at the relay nodes where partitioned video contents are stored and provide an enhanced quality for the client. We also show that the optimised cache the degradation in the video quality received by the client becomes more graceful than the non-optimised system when the network experiences packet loss or is congested.

A quality driven framework for adaptive video streaming in mobile wireless networks

The concern over the quality of delivering video streaming services in mobile wireless networks is addressed in this work. A framework that enhances the Quality of Experience (QoE) of end users through a quality driven resource allocation scheme is proposed. To play a key role, an objective no-reference quality metric, Pause Intensity (PI), is adopted to derive a resource allocation algorithm for video streaming. The framework is examined in the context of 3GPP Long Term Evolution (LTE) systems. The requirements and structure of the proposed PI-based framework are discussed, and results are compared with existing scheduling methods on fairness, efficiency and correlation (between the required and allocated data rates). Furthermore, it is shown that the proposed framework can produce a trade-off between the three parameters through the QoE-aware resource allocation process.

Quality-driven resource utilization methods for video streaming in wireless communication networks

This research is focused on the optimisation of resource utilisation in wireless mobile networks with the consideration of the users’ experienced quality of video streaming services. The study specifically considers the new generation of mobile communication networks, i.e. 4G-LTE, as the main research context. The background study provides an overview of the main properties of the relevant technologies investigated. These include video streaming protocols and networks, video service quality assessment methods, the infrastructure and related functionalities of LTE, and resource allocation algorithms in mobile communication systems. A mathematical model based on an objective and no-reference quality assessment metric for video streaming, namely Pause Intensity, is developed in this work for the evaluation of the continuity of streaming services. The analytical model is verified by extensive simulation and subjective testing on the joint impairment effects of the pause duration and pause frequency. Various types of the video contents and different levels of the impairments have been used in the process of validation tests. It has been shown that Pause Intensity is closely correlated with the subjective quality measurement in terms of the Mean Opinion Score and this correlation property is content independent. Based on the Pause Intensity metric, an optimised resource allocation approach is proposed for the given user requirements, communication system specifications and network performances. This approach concerns both system efficiency and fairness when establishing appropriate resource allocation algorithms, together with the consideration of the correlation between the required and allocated data rates per user. Pause Intensity plays a key role here, representing the required level of Quality of Experience (QoE) to ensure the best balance between system efficiency and fairness. The 3GPP Long Term Evolution (LTE) system is used as the main application environment where the proposed research framework is examined and the results are compared with existing scheduling methods on the achievable fairness, efficiency and correlation. Adaptive video streaming technologies are also investigated and combined with our initiatives on determining the distribution of QoE performance across the network. The resulting scheduling process is controlled through the prioritization of users by considering their perceived quality for the services received. Meanwhile, a trade-off between fairness and efficiency is maintained through an online adjustment of the scheduler’s parameters. Furthermore, Pause Intensity is applied to act as a regulator to realise the rate adaptation function during the end user’s playback of the adaptive streaming service. The adaptive rates under various channel conditions and the shape of the QoE distribution amongst the users for different scheduling policies have been demonstrated in the context of LTE. Finally, the work for interworking between mobile communication system at the macro-cell level and the different deployments of WiFi technologies throughout the macro-cell is presented. A QoEdriven approach is proposed to analyse the offloading mechanism of the user’s data (e.g. video traffic) while the new rate distribution algorithm reshapes the network capacity across the macrocell. The scheduling policy derived is used to regulate the performance of the resource allocation across the fair-efficient spectrum. The associated offloading mechanism can properly control the number of the users within the coverages of the macro-cell base station and each of the WiFi access points involved. The performance of the non-seamless and user-controlled mobile traffic offloading (through the mobile WiFi devices) has been evaluated and compared with that of the standard operator-controlled WiFi hotspots.

Model and performance of a no-reference quality assessment metric for video streaming

Video streaming via Transmission Control Protocol (TCP) networks has become a popular and highly demanded service, but its quality assessment in both objective and subjective terms has not been properly addressed. In this paper, based on statistical analysis a full analytic model of a no-reference objective metric, namely pause intensity (PI), for video quality assessment is presented. The model characterizes the video playout buffer behavior in connection with the network performance (throughput) and the video playout rate. This allows for instant quality measurement and control without requiring a reference video. PI specifically addresses the need for assessing the quality issue in terms of the continuity in the playout of TCP streaming videos, which cannot be properly measured by other objective metrics such as peak signal-to-noise-ratio, structural similarity, and buffer underrun or pause frequency. The performance of the analytical model is rigidly verified by simulation results and subjective tests using a range of video clips. It is demonstrated that PI is closely correlated with viewers' opinion scores regardless of the vastly different composition of individual elements, such as pause duration and pause frequency which jointly constitute this new quality metric. It is also shown that the correlation performance of PI is consistent and content independent. © 2013 IEEE.

Pause intensity:a no-reference quality assessment metric for video streaming in TCP networks

In this paper a full analytic model for pause intensity (PI), a no-reference metric for video quality assessment, is presented. The model is built upon the video play out buffer behavior at the client side and also encompasses the characteristics of a TCP network. Video streaming via TCP produces impairments in play continuity, which are not typically reflected in current objective metrics such as PSNR and SSIM. Recently the buffer under run frequency/probability has been used to characterize the buffer behavior and as a measurement for performance optimization. But we show, using subjective testing, that under run frequency cannot reflect the viewers' quality of experience for TCP based streaming. We also demonstrate that PI is a comprehensive metric made up of a combination of phenomena observed in the play out buffer. The analytical model in this work is verified with simulations carried out on ns-2, showing that the two results are closely matched. The effectiveness of the PI metric has also been proved by subjective testing on a range of video clips, where PI values exhibit a good correlation with the viewers' opinion scores. © 2012 IEEE.

Ensuring QoE in contemporary mobile networks for video content distribution

A framework that aims to best utilize the mobile network resources for video applications is presented in this paper. The main contribution of the work proposed is the QoE-driven optimization method that can maintain a desired trade-off between fairness and efficiency in allocating resources in terms of data rates to video streaming users in LTE networks. This method is concerned with the control of the user satisfaction level from the service continuity's point of view and applies appropriate QoE metrics (Pause Intensity and variations) to determine the scheduling strategies in combination with the mechanisms used for adaptive video streaming such as 3GP/MPEG-DASH. The superiority of the proposed algorithms are demonstrated, showing how the resources of a mobile network can be optimally utilized by using quantifiable QoE measurements. This approach can also find the best match between demand and supply in the process of network resource distribution.

Adaptive resource allocation for QoE-aware mobile communication networks

A real-time adaptive resource allocation algorithm considering the end user's Quality of Experience (QoE) in the context of video streaming service is presented in this work. An objective no-reference quality metric, namely Pause Intensity (PI), is used to control the priority of resource allocation to users during the scheduling process. An online adjustment has been introduced to adaptively set the scheduler's parameter and maintain a desired trade-off between fairness and efficiency. The correlation between the data rates (i.e. video code rates) demanded by users and the data rates allocated by the scheduler is taken into account as well. The final allocated rates are determined based on the channel status, the distribution of PI values among users, and the scheduling policy adopted. Furthermore, since the user's capability varies as the environment conditions change, the rate adaptation mechanism for video streaming is considered and its interaction with the scheduling process under the same PI metric is studied. The feasibility of implementing this algorithm is examined and the result is compared with the most commonly existing scheduling methods.

Long-term drivers of broadband traffic in next-generation networks

This paper is concerned with long-term (20+ years) forecasting of broadband traffic in next-generation networks. Such long-term approach requires going beyond extrapolations of past traffic data while facing high uncertainty in predicting the future developments and facing the fact that, in 20 years, the current network technologies and architectures will be obsolete. Thus, "order of magnitude" upper bounds of upstream and downstream traffic are deemed to be good enough to facilitate such long-term forecasting. These bounds can be obtained by evaluating the limits of human sighting and assuming that these limits will be achieved by future services or, alternatively, by considering the contents transferred by bandwidth-demanding applications such as those using embedded interactive 3D video streaming. The traffic upper bounds are a good indication of the peak values and, subsequently, also of the future network capacity demands. Furthermore, the main drivers of traffic growth including multimedia as well as non-multimedia applications are identified. New disruptive applications and services are explored that can make good use of the large bandwidth provided by next-generation networks. The results can be used to identify monetization opportunities of future services and to map potential revenues for network operators. © 2014 The Author(s).

A quality driven adaptation scheme for DASH streaming

In this work we present a quality driven approach to DASH (Dynamic Adaptive Streaming over HTTP) for segment selection in varying network conditions. Current adaption algorithms focus largely on regulating data rates using network layer parameters by selecting the level of quality on offer that can eliminate buffer underrun without considering picture fidelity. In reality, viewers may accept a level of buffer underrun in order to achieve an improved level of picture fidelity. In this case, the conventional DASH algorithms can cause extreme degradation of the picture fidelity when attempting to eliminate buffer underrun with scarce bandwidth availability. Our work is concerned with a quality-aware rate adaption scheme that maximizes the client's quality of experience in terms of both continuity and fidelity (picture quality). Results show that the scheme proposed can maintain a high level of quality for streaming services, especially at low packet loss rates. It is also shown that by eliminating buffer underrun completely, the PSNR that reflects the picture quality of the video is greatly reduced. Our scheme offers the offset between continuity-based quality and resolution-based quality, which can be used to set threshold values for the level of quality desired by clients with different quality requirements. © 2013 IEEE.

Effective video content distribution by combining TCP with adaptive FEC coding

This paper will look at the benefits and limitations of content distribution using Forward Error Correction (FEC) in conjunction with the Transmission Control Protocol (TCP). FEC can be used to reduce the number of retransmissions which would usually result from a lost packet. The requirement for TCP to deal with any losses is then greatly reduced. There are however side-effects to using FEC as a countermeasure to packet loss: an additional requirement for bandwidth. When applications such as real-time video conferencing are needed, delay must be kept to a minimum, and retransmissions are certainly not desirable. A balance, therefore, between additional bandwidth and delay due to retransmissions must be struck. Our results show that the throughput of data can be significantly improved when packet loss occurs using a combination of FEC and TCP, compared to relying solely on TCP for retransmissions. Furthermore, a case study applies the result to demonstrate the achievable improvements in the quality of streaming video perceived by end users.