1,721,000 research outputs found
Timber: An SDN-based Emulation Platform for Experimental Research on Video Streaming
Full text linkIn this paper, we present an open source Software-Defined Networking (SDN) based emulation platform called Timber . We aim to provide the research community with an experimental tool for the design and evaluation of the new Quality of Experience (QoE) management and monitoring procedures for video streaming. To this aim, the main functionalities of Timber include: i) an SDN application for taking QoE-aware management decisions; ii) an SDN controller to monitor the network’s QoS (Quality of Service) and implement network management actions, such as network slicing and Multiprotocol Label Switching (MPLS) based prioritization operations; iii) a complete video streaming application including a multimedia server and a DASH-based client video player; iv) a user-end probe at the client video player to monitor QoE-related video application parameters, which are stored in a database that can be accessed by the SDN application; v) data analysis tools, which enable easy data visualization of measured QoS and QoE metrics as well as execution of statistical analysis of experimental results. In this article, we introduce and describe the main characteristics and functionalities of Timber as well as the implementation details. Finally, we provide experimental results of a video streaming scenario to demonstrate the capability of Timber to implement and test QoE-aware management approaches
QoE-centric service delivery: A collaborative approach among OTTs and ISPs
No full textThe provisioning of the quality to end users is a major objective for the successful deployment of multimedia services over the Internet. It is more and more evident from past research and service deployments that such an objective often requires a collaboration among the different parties that are involved in the delivery of the service. This paper specifically focuses on the cooperation between the Over-The-Top (OTTs) and the Internet Service Providers (ISPs) and proposes a novel service delivery approach that is purely driven by the Quality of Experience (QoE) provided to the final common users. Initially, we identify the need of the collaboration among the OTTs and the ISPs where we not only highlight some of the enterprise level motivations (revenue generation) but also the technical aspects which require collaboration. Later, we provide a reference architecture with the required modules and vertical interfaces for the interaction among the OTTs and the ISPs. Then, we provide a collaboration model where we focus on the modeling of the revenue, whose maximization drives the collaboration. The revenue is considered to be dependent on the user churn, which in turn is affected by the QoE and is modeled using the Sigmoid function. We illustrate simulation results based on our proposed collaboration approach which highlight how the proposed strategy increases the revenue generation and QoE for the OTTs and the ISPs hence providing a ground for ISP to join the loop of revenue generation between OTTs and users
Timber: An SDN based emulation platform for QoE Management Experimental Research
No full textIn this paper, we present an open source Software-Defined Networking (SDN) based emulation platform called Timber. It is aimed at providing the research community with a tool for experimenting new Quality of Experience (QoE) management procedures and tools in multimedia service delivery. Timber is developed on the top of Mininet SDN emulator and Ryu SDN controller, which provides the major functionalities of the traffic engineering abstractions in SDN environment. Moreover, the platform provides an actual complete video streaming application including the implementation of the server side and client side probes for QoE measurements which have functionalities to store the quality measurements into the cloud database accessible to the SDN controller application. In this paper, we first discuss the general architecture and framework of Timber. Secondly, we provide the implementation details and major functionalities of the platform. Thirdly, we provide experimental results to highlight the major functionalities of Timber by 4 different scenarios which include traffic shaping through DiffServ and dynamic resource allocation by queuing strategies
Quality of Experience in the Metaverse: An Initial Analysis on Quality Dimensions and Assessment
Full text linkThe Metaverse provides a novel experience to the user, by opening the doors to social-based multiuser environments merging physical reality with digital virtuality. In this paper, we present an initial analysis of the Quality of Experience (QoE) in the Metaverse. We first consider traditional influence factors (human, system, and context). Then, we introduce the social and economic dimensions of the Metaverse as additional factors to
be considered for QoE assessment. Finally, we discuss what QoE assessment methods can be more suitable for Metaverse applications, with a particular focus on implicit assessment methods (e.g., physiological, human cognitive, affective behaviour)
Controlling Media Player with Hands: A Transformer Approach and a Quality of Experience Assessment
Full text linkIn this article, we propose a Hand Gesture Recognition (HGR) system based on a novel deep transformer (DT) neural network for media player control. The extracted hand skeleton features are processed by separate transformers for each finger in isolation to better identify the finger characteristics to drive the following
classification. The achieved HGR accuracy (0.853) outperforms state-of-the-art HGR approaches when tested on the popular NVIDIA dataset. Moreover, we conducted a subjective assessment involving 30 people to evaluate the Quality of Experience (QoE) provided by the proposed DT-HGR for controlling a media player application compared with two traditional input devices, i.e., mouse and keyboard. The assessment participants were asked to evaluate objective (accuracy) and subjective (physical fatigue, usability, pragmatic quality, and hedonic quality) measurements. We found that (i) the accuracy of DT-HGR is very high (91.67%), only slightly lower than that of traditional alternative interaction modalities; and that (ii) the perceived quality for DT-HGR in terms of satisfaction, comfort, and interactivity is very high, with an average Mean Opinion Score (MOS) value as high as 4.4, whereas the alternative approaches did not reach 3.8, which encourages a more pervasive adoption of the natural gesture interaction
Analysis of the quality of remote working experience: a speech-based approach
Full text linkThe current pandemic situation has led to an extraordinary increase in remote working activities all over the world. In this paper, we conducted a research study with the aim to investigate the Quality of Remote Working Experience (QRWE) of workers when conducting remote working activities and to analyse its correlation with implicit emotion responses estimated from the speech of video-calls or discussions with people in the same room. We implemented a system that captures the audio when the worker is talking and extracts and stores several speech features. A subjective assessment has been conducted, using this tool, which involved 12 people that were asked to provide feedback on the QRWE and assess their sentiment polarity during their daily remote working hours. ANOVA results suggest that speech features may be potentially observed to infer the QRWE and the sentiment polarity of the speaker. Indeed, we have also found that the perceived QRWE and polarity are strongly related
Quality of Experience in the Multimedia Internet of Things: Definition and practical use-cases
No full textIn this paper, a first approach for evaluating the
Quality of Experience (QoE) for IoT (Internet of Things)
applications is presented. Firstly, a layered IoT architecture is
analysed to understand which QoE influence factors have to be
considered in relevant application scenarios. Secondly, we
introduce the concept of Multimedia IoT (MIoT) and define a
layered QoE model aimed at evaluating and combining the
contributions of each influence factor to estimate the overall QoE
in MIoT applications. Finally, we present a vehicular MIoT
application that has been used to conduct subjective quality
assessments to verify the performance of the proposed approach
QoE-aware Service Delivery: A Joint-Venture Approach for Content and Network Providers
No full textThe objective of this work is the investigation of a possible collaboration between Over-The-Top (OTTs) service providers and Internet Service Providers (ISPs), which is centered around the Quality of Experience (QoE). Initially, we define a reference architecture with the required modules and interfaces for the interaction between the two providers. Then, we focus on the modeling of the revenue, whose maximization drives the collaboration. It is considered as depending on the user churn, which in turn is affected by the QoE and is modeled using the Sigmoid function. We illustrate simulation results based on our proposed collaboration approach which highlights how the proposed strategy increases the revenue generation and QoE for both players hence providing a ground for ISP to join the loop of revenue generation between OTT and users
Implementation of a Magnetometer based Vehicle Detection System for Smart Parking applications
No full textThe time lost looking for a free parking spot in a city impacts negatively not only on the mood of the drivers but also on the environment in terms of air quality and fuel consumption. The vehicle detection can be considered as the most important task in Smart Parking systems as it allows to automatically monitor the occupancy state of the parking spots in a city. In this paper, we implement and test a vehicle detection system based on a magnetometer sensor, which is part of a complete Smart Parking system under development at the University of Cagliari. After a preliminary analysis conducted to test the performance of the magnetometer, we conducted two specific experiments to investigate the suitability of the magnetometer as the mean to detect the presence of a vehicle in the parking spots. The first experiment, involving 15 different vehicles, has
demonstrated that the magnetometer can be used to reliably detect the presence of a vehicle in a parking spot if it is placed under the front or rear axle of the vehicle. From the second experiment it resulted that, when considering 3 adjacent parking spots and only one magnetometer placed in the central spot, it is not possible to reliably detect the vehicles parked on the adjacent spots. Therefore, one magnetometer for each considered parking spot is needed
Analysis of Application-layer Data to Estimate the QoE of WebRTC-based Audiovisual Conversations
No full textSuccessful deployment of Web-based Real-Time Communication (WebRTC) applications needs appropriate Quality of Experience (QoE)-aware service management to assure acceptability from the user's perspective. To this aim, monitoring of application-level data was found to provide relevant insights to estimate the user's QoE. In this paper, we investigate the relationship between WebRTC session parameters (collected with the webrtc-internals tool) and the users' QoE (in terms of the Mean Opinion Score (MOS)) through in-depth statistical analysis aimed at identifying the most suitable parameters for QoE estimation. In this regard, we based on statistical metrics, Pearson Correlation Coefficient (PCC), and Analysis of Variance (ANOVA). Then, we trained three machine learning regression algorithms (Regression tree, Extreme Gradient Boosting (XGBoost), and Multi-Layer Perceptron (MLP)) using the identified parameters as the input data and the MOS as the output to be predicted. Experimental results show that the statistical analysis based on the PCC identified the optimal set of WebRTC session parameters for estimating the end user's QoE. With this optimal set of features, the MLP achieved the greatest QoE estimation performance in terms of R2 (0.852) and Root Mean Square Error (RMSE) (0.282), outperforming state-of-the-art results
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