Design and implementation of a novel secured and wide WebRTC signalling mechanism for multimedia over internet

A modern and free technology called web real-time communication (WebRTC) was enhanced to allow browser-to-browser multimedia communication without plugins. In contract, WebRTC has not categorised a specific signalling mechanism to set, establish and end communication between browsers. The primary target of this application is to produce and implement a novel WebRTC signalling mechanism for multimedia communication between different users over the Internet without plugins. Furthermore, it has been applied over different browsers, such as Explorer, Safari, Google Chrome, Firefox and Opera without any downloading or fees. This application designed using JavaScript language under ASP.net and C# language. Moreover, to prevent irrelevant users from accessing or attacking the session, user-id for initiating and joining the course using encryption technique was done. This system has been employed in real implementation among various users; therefore, an evaluation of bandwidth consumption, CPU, and quality of experience (QoE) was accomplished. The results show an original signalling mechanism which applied to different browsers, multiple users, and diverse networks such as Ethernet and Wireless. Besides, it sets session initiator, saves the communication efficient even if the initiator leaves, and communicating new participator with existing participants, etc. This studying focuses on the creation of a new signalling mechanism, the limitations of resources for WebRTC video conferencing

System Integration for Medical Data Dissemination and Multimedia Communication in the Implementation of Tele-ECG and Teleconsultation

One of the options to extend medical services coverage is deploying a telemedicine system, where medical personnel make use of ICT (Information and Communication Technology) to overcome distance and time constraints. The implementation of telemedicine systems in Indonesia faces challenges posed by the lack of ICT infrastructure availability, such as communication networks, data centres, and other computing resources. To deal with these challenges, a telemedicine innovation needs to produce a modular and flexible system that is adaptive to medical services needed and the available ICT infrastructure. This paper presents research and development of a telemedicine system prototype for tele-electrocardiography (tele-ECG) and teleconsultation. The contributions offered are integrating system from various open-source modules and the system operational feasibility based on its function and performance. The research is conducted on a testbed which represents various components involved in the telemedicine system operation. Experiments are carried out to assess the system functionality and observe whether tele-ECG and teleconsultation reach their expected performance. Experiment results show that the system works properly and recommend several multimedia communication modes to achieve the target quality based on the available network bandwidth

A Telerehabilitation System for the Selection, Evaluation and Remote Management of Therapies

Telerehabilitation systems that support physical therapy sessions anywhere can help save healthcare costs while also improving the quality of life of the users that need rehabilitation. The main contribution of this paper is to present, as a whole, all the features supported by the innovative Kinect-based Telerehabilitation System (KiReS). In addition to the functionalities provided by current systems, it handles two new ones that could be incorporated into them, in order to give a step forward towards a new generation of telerehabilitation systems. The knowledge extraction functionality handles knowledge about the physical therapy record of patients and treatment protocols described in an ontology, named TRHONT, to select the adequate exercises for the rehabilitation of patients. The teleimmersion functionality provides a convenient, effective and user-friendly experience when performing the telerehabilitation, through a two-way real-time multimedia communication. The ontology contains about 2300 classes and 100 properties, and the system allows a reliable transmission of Kinect video depth, audio and skeleton data, being able to adapt to various network conditions. Moreover, the system has been tested with patients who suffered from shoulder disorders or total hip replacement.This research was funded by the Spanish Ministry of Economy and Competitiveness grant number FEDER/TIN2016-78011-C4-2R

Performance Evaluation And Anomaly detection in Mobile BroadBand Across Europe

With the rapidly growing market for smartphones and user’s confidence for immediate access to high-quality multimedia content, the delivery of video over wireless networks has become a big challenge. It makes it challenging to accommodate end-users with flawless quality of service. The growth of the smartphone market goes hand in hand with the development of the Internet, in which current transport protocols are being re-evaluated to deal with traffic growth. QUIC and WebRTC are new and evolving standards. The latter is a unique and evolving standard explicitly developed to meet this demand and enable a high-quality experience for mobile users of real-time communication services. QUIC has been designed to reduce Web latency, integrate security features, and allow a highquality experience for mobile users. Thus, the need to evaluate the performance of these rising protocols in a non-systematic environment is essential to understand the behavior of the network and provide the end user with a better multimedia delivery service. Since most of the work in the research community is conducted in a controlled environment, we leverage the MONROE platform to investigate the performance of QUIC and WebRTC in real cellular networks using static and mobile nodes. During this Thesis, we conduct measurements ofWebRTC and QUIC while making their data-sets public to the interested experimenter. Building such data-sets is very welcomed with the research community, opening doors to applying data science to network data-sets. The development part of the experiments involves building Docker containers that act as QUIC and WebRTC clients. These containers are publicly available to be used candidly or within the MONROE platform. These key contributions span from Chapter 4 to Chapter 5 presented in Part II of the Thesis. We exploit data collection from MONROE to apply data science over network data-sets, which will help identify networking problems shifting the Thesis focus from performance evaluation to a data science problem. Indeed, the second part of the Thesis focuses on interpretable data science. Identifying network problems leveraging Machine Learning (ML) has gained much visibility in the past few years, resulting in dramatically improved cellular network services. However, critical tasks like troubleshooting cellular networks are still performed manually by experts who monitor the network around the clock. In this context, this Thesis contributes by proposing the use of simple interpretable ML algorithms, moving away from the current trend of high-accuracy ML algorithms (e.g., deep learning) that do not allow interpretation (and hence understanding) of their outcome. We prefer having lower accuracy since we consider it interesting (anomalous) the scenarios misclassified by the ML algorithms, and we do not want to miss them by overfitting. To this aim, we present CIAN (from Causality Inference of Anomalies in Networks), a practical and interpretable ML methodology, which we implement in the form of a software tool named TTrees (from Troubleshooting Trees) and compare it to a supervised counterpart, named STress (from Supervised Trees). Both methodologies require small volumes of data and are quick at training. Our experiments using real data from operational commercial mobile networks e.g., sampled with MONROE probes, show that STrees and CIAN can automatically identify and accurately classify network anomalies—e.g., cases for which a low network performance is not justified by operational conditions—training with just a few hundreds of data samples, hence enabling precise troubleshooting actions. Most importantly, our experiments show that a fully automated unsupervised approach is viable and efficient. In Part III of the Thesis which includes Chapter 6 and 7. In conclusion, in this Thesis, we go through a data-driven networking roller coaster, from performance evaluating upcoming network protocols in real mobile networks to building methodologies that help identify and classify the root cause of networking problems, emphasizing the fact that these methodologies are easy to implement and can be deployed in production environments.This work has been supported by IMDEA Networks InstitutePrograma de Doctorado en Multimedia y Comunicaciones por la Universidad Carlos III de Madrid y la Universidad Rey Juan CarlosPresidente: Matteo Sereno.- Secretario: Antonio de la Oliva Delgado.- Vocal: Raquel Barco Moren

Web-Based Networked Music Performances via WebRTC: A Low-Latency PCM Audio Solution

Nowadays, widely used videoconferencing software has been diffused even further by the social distancing measures adopted during the SARS-CoV-2 pandemic. However, none of the Web-based solutions currently available support high-fidelity stereo audio streaming, which is a fundamental prerequisite for networked music applications. This is mainly because of the fact that the WebRTC RTCPeerConnection standard or Web-based audio streaming do not handle uncompressed audio formats. To overcome that limitation, an implementation of 16-bit pulse code modulation (PCM) stereo audio transmission on top of the WebRTC RTCDataChannel, leveraging Web Audio and AudioWorklets, is discussed. Results obtained with multiple configurations, browsers, and operating systems showthat the proposed approach outperforms theWebRTC RTCPeerConnection standard in terms of audio quality and latency, which in the authors' best case to date has been reduced to only 40 ms between twoMacBooks on a local area network

Performance Analysis of WebRTC-based Video Streaming over Power Constrained Platforms

This work analyses the use of the WebRTC framework on resource-constrained platforms. WebRTC is a consolidated solution for real-time video streaming, and it is an appealing solution in a wide range of application scenarios. We focus our attention on those in which power consumption, size and weight are of paramount importance because of size, weight and power requirements, such as the use case of unmanned aerial vehicles delivering real-time video streams overWebRTC to peers on the ground. The testbed described in this work shows that the power consumption can be reduced by changing WebRTC default settings while maintaining comparable video quality

Common Educational Teleoperation Platform for Robotics Utilizing Digital Twins

The erratic modern world introduces challenges to all sectors of societies and potentially introduces additional inequality. One possibility to decrease the educational inequality is to provide remote access to facilities that enable learning and training. A similar approach of remote resource usage can be utilized in resource-poor situations where the required equipment is available at other premises. The concept of Industry 5.0 (i5.0) focuses on a human-centric approach, enabling technologies to concentrate on human–machine interaction and emphasizing the importance of societal values. This paper introduces a novel robotics teleoperation platform supported by the i5.0. The platform reduces inequality and allows usage and learning of robotics remotely independently of time and location. The platform is based on digital twins with bi-directional data transmission between the physical and digital counterparts. The proposed system allows teleoperation, remote programming, and near real-time monitoring of controlled robots, robot time scheduling, and social interaction between users. The system design and implementation are described in detail, followed by experimental results

GRACE: Loss-Resilient Real-Time Video through Neural Codecs

In real-time video communication, retransmitting lost packets over high-latency networks is not viable due to strict latency requirements. To counter packet losses without retransmission, two primary strategies are employed -- encoder-based forward error correction (FEC) and decoder-based error concealment. The former encodes data with redundancy before transmission, yet determining the optimal redundancy level in advance proves challenging. The latter reconstructs video from partially received frames, but dividing a frame into independently coded partitions inherently compromises compression efficiency, and the lost information cannot be effectively recovered by the decoder without adapting the encoder. We present a loss-resilient real-time video system called GRACE, which preserves the user's quality of experience (QoE) across a wide range of packet losses through a new neural video codec. Central to GRACE's enhanced loss resilience is its joint training of the neural encoder and decoder under a spectrum of simulated packet losses. In lossless scenarios, GRACE achieves video quality on par with conventional codecs (e.g., H.265). As the loss rate escalates, GRACE exhibits a more graceful, less pronounced decline in quality, consistently outperforming other loss-resilient schemes. Through extensive evaluation on various videos and real network traces, we demonstrate that GRACE reduces undecodable frames by 95% and stall duration by 90% compared with FEC, while markedly boosting video quality over error concealment methods. In a user study with 240 crowdsourced participants and 960 subjective ratings, GRACE registers a 38% higher mean opinion score (MOS) than other baselines

Kires: a data-centric telerehabilitation system based on kinect

185 p.It is widely accepted that the worldwide demand for rehabilitation services. To meet these needs, there will have to be developed systems of telerehabilitation that will bring services to even the most remote locations, through Internet and related technologies.This thesis is addressing the area of remote health care delivery, in particular telerehabilitation. We present KiReS; a Kinect based telerehabilitation system which covers the needs of physiotherapists in the process of designing, managing and evaluating physiotherapy protocols and sessions and also covers the needs of the users providing them an intuitive and encouraging interface and giving useful feedback to enhance the rehabilitation process. As required for multi-disciplinary projects, physiotherapists were consulted and feedback from patients was incorporated at different development stages.KiReS aims to outcome limitations of other telerehabilitation systems and bring some novel features: 1) A friendly and helpful interaction with the system using Kinect and motivational interfaces based on avatars. 2) Provision of smart data that supports physiotherapists in the therapy design process by: assuring the maintenance of appropriate constraints and selecting for them a set of exercises that are recommended for the user. 3) Monitoring of rehabilitation sessions through an algorithm that evaluates online performed exercises and sets if they have been properly executed. 4) Extensibility, KiReS is designed to be loaded with a broad spectrum of exercises and protocols