Ianire Taboada

Web QoE Evaluation in Multi-agent Networks: Validation of ITU-T G.1030

Users requirements have become a key factor for any Quality of Service (QoS) management model to succeed. The advent and rise of new broadband services and network architectures (Triple-Play-Services, NGN…) depends on the ability of providers to achieve users expectations in these scenarios. For that reason, the overall end users perception (Quality of Experience – QoE) must be audited, on a regular basis, to address changing users needs. This paper presents a general system developed to evaluate QoE on IP networks. The system architecture is designed to be capable of emulating multi agent networks and dynamically changing conditions. In addition, the results of a Web browsing QoE experiment, laid out within this emulation system, are described. The experiment was conducted on the basis of ITU-T Recommendation G.1030, and aimed to update the perceptual model, provided in this Recommendation, to today’s user requirements and technical improvements.

Improving content delivery efficiency through multi-layer mobile edge adaptation

This article presents a novel architecture for optimizing HTTP-based multimedia delivery in multi-user mobile networks. This proposal combines the usual client-driven dynamic adaptation scheme DASH-3GPP with network-assisted adaptation capabilities, in order to maximize the overall quality of experience. The foundation of this combined adaptation scheme is based on two state of the art technologies. On one hand, adaptive HTTP streaming with multi-layer encoding allows efficient media delivery and improves the experienced media quality in highly dynamic channels. Additionally, it makes it possible to implement network-level adaptations for better coping with multi-user scenarios. On the other hand, mobile edge computing facilitates the deployment of mobile services close to the user. This approach brings new possibilities in modern and future mobile networks, such as close to zero delays and awareness of the radio status. The proposal in this article introduces a novel element, called the mobile edge-DASH adaptation function, which combines all these advantages to support efficient media delivery in mobile multi-user scenarios. Furthermore, we evaluate the performance enhancements of this content-aware and user context-aware scheme through simulations of a mobile multimedia scenario.

QoE-aware optimization of multimedia flow scheduling

This paper deals with the subjective quality maximization problem when scheduling multimedia traffic flows in a shared channel. In order to quantify such user satisfaction a utility function dependent on flow transfer delay is used. In this context, we formulate the Quality of Experience aware resource allocation optimization problem as a Markov Decision Process. This model is analytically unsolvable in general, and as an approximate solution we develop a simple and tractable index rule based on Gittins approach, originally aimed just at minimizing mean flow delay. As concluded from simulation results, when evaluating subjective quality performance this novel index rule proposal outperforms the most relevant existing scheduling disciplines.

Impact of end devices on subjective video quality assessment for QCIF video sequences

The aim of this paper is to assess the impact of devices on Quality of Experience (QoE) of the user. As the types of video content viewed over handheld devices increases e.g. streaming video, it is important to evaluate the impact of the end device on video quality assessment. In this paper subjective tests were conducted with QCIF (176×144) videos over two devices — Personal Computer (PC) and mobile handset with 90 test conditions. The dataset was generated with a combination of parameters associated with the access network (block error rates and mean burst lengths), H.264 codec related parameter (sender bitrates) and content types. Subjects favoured PC test over handset test in almost all test scenarios. These studies should help in context-aware services in deciding the appropriate encoding parameters based on type of device being used to receive content.

Opportunistic scheduling of flows with general size distribution in wireless time-varying channels

In this paper we study how to design an opportunistic scheduler when flow sizes have a general service time distribution with the objective of minimizing the expected holding cost. We allow the channel condition to have two states which in particular covers the important special case of ON/OFF channels. We formulate the problem as a multi-armed restless bandit problem, a particular class of Markov decision processes. Since an exact solution is out of reach, we characterize in closed-form the Whittle index, which allows us to define a heuristic scheduling rule for the problem. We then particularize the index to the important subclass of distributions with a decreasing hazard rate. We finally evaluate the performance of the proposed Whittle-index based scheduler by simulation of a wireless network. The numerical results show that the performance of the proposed scheduler is very satisfactory.

An opportunistic and non-anticipating size-aware scheduling proposal for mean holding cost minimization in time-varying channels

In this paper we study how to design a scheduling strategy aimed at minimizing the average holding cost for flows with general size distribution when the feasible transmission rate of each user varies randomly over time. We employ a Whittle-index-based approach in order to achieve an opportunistic and non-anticipating size-aware scheduling index rule proposal. When the flow size distribution belongs to the Decreasing Hazard Rate class, we propose the so-called Attained Service Potential Improvement index rule, which consists in giving priority to the flows with the highest ratio between the current attained-service-dependent completion probability and the expected potential improvement of this completion probability. We further analyze the performance of the proposed scheduler, concluding that it outperforms well-known opportunistic disciplines.

Radio-Aware Service-Level Scheduling to Minimize Downlink Traffic Delay Through Mobile Edge Computing

One of the most challenging problems in mobile broadband networks is how to assign the available radio resources among the different mobile users. Traditionally, research proposals are either specific to some type of traffic or deal with computationally intensive algorithms aimed at optimizing the delivery of general purpose traffic. Consequently, commercial networks do not incorporate these mechanisms due to the limited hardware resources at the mobile edge. Emerging 5G architectures introduce cloud computing principles to add flexible computational resources to Radio Access Networks. This paper makes use of the Mobile Edge Computing concepts to introduce a new element, denoted as Mobile Edge Scheduler, aimed at minimizing the mean delay of general traffic flows in the LTE downlink. This element runs close to the eNodeB element and implements a novel flow-aware and channel-aware scheduling policy in order to accommodate the transmissions to the available channel quality of end users.

Dealing with Energy-QoE Trade-Offs in Mobile Video

Scalable video coding allows an efficient provision of video services at different quality levels with different energy demands. According to the specific type of service and network scenario, end users and/or operators may decide to choose among different energy versus quality combinations. In order to deal with the resulting trade-off, in this paper we analyze the number of video layers that are worth to be received taking into account the energy constraints. A single-objective optimization is proposed based on dynamically selecting the number of layers, which is able to minimize the energy consumption with the constraint of a minimal quality threshold to be reached. However, this approach cannot reflect the fact that the same increment of energy consumption may result in different increments of visual quality. Thus, a multiobjective optimization is proposed and a utility function is defined in order to weight the energy consumption and the visual quality criteria. Finally, since the optimization solving mechanism is computationally expensive to be implemented in mobile devices, a heuristic algorithm is proposed. This way, significant energy consumption reduction will be achieved while keeping reasonable quality levels.

Size-based and channel-aware scheduling algorithm proposal for mean delay optimization in wireless networks

This paper deals with the analysis of the impact of different scheduling algorithms on flow level mean delay performance of elastic traffic in a single cell wireless downlink data channel paradigm. An enhanced size-based and channel-aware discipline is proposed, which is based on the sized-aware Gittins index approach applied to a time-varying channel context. In order to compare the proposed Opportunistic Gittins rule performance with well-known scheduling algorithms, several simulations have been performed for stochastically arriving flows with Pareto sizes under fading conditions, for different network loads and channel quality indicator reporting rates. As concluded, an approach that combines both flow size-awareness and channel-awareness is the best option, which guarantees a trade-off between minimizing uplink overhead due to channel quality reports and improving scheduling performance aimed at reducing overall flow mean delay.

Service provisioning and pricing methods in a multi-tenant cloud enabled RAN

The Cloud Enabled Small Cell (CESC) concept proposed in EU funded project SESAME has emerged as a promising solution to form a multi-tenant, multi-service architecture at the network edge according to 5G needs. It allows several operators/service providers to engage in a sharing model of both radio access capacity and Mobile Edge Computing (MEC) capabilities. From a business perspective, the shared ecosystem guarantees benefits such as easy system upgrades and CAPEX/OPEX reduction. However, depending on the adapted model which is reflected at Service Level Agreement (SLA) between involved stakeholders, cost and benefit of each party are subject to change. This paper is an effort to identify and analyse different radio and cloud models and pricing schemes for the joint provisioning of radio access capacity and MEC services in a multi-tenant Radio Access Network (RAN).