91 research outputs found

    vSkyConf: Cloud-assisted Multi-party Mobile Video Conferencing

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    As an important application in the busy world today, mobile video conferencing facilitates virtual face-to-face communication with friends, families and colleagues, via their mobile devices on the move. However, how to provision high-quality, multi-party video conferencing experiences over mobile devices is still an open challenge. The fundamental reason behind is the lack of computation and communication capacities on the mobile devices, to scale to large conferencing sessions. In this paper, we present vSkyConf, a cloud-assisted mobile video conferencing system to fundamentally improve the quality and scale of multi-party mobile video conferencing. By novelly employing a surrogate virtual machine in the cloud for each mobile user, we allow fully scalable communication among the conference participants via their surrogates, rather than directly. The surrogates exchange conferencing streams among each other, transcode the streams to the most appropriate bit rates, and buffer the streams for the most efficient delivery to the mobile recipients. A fully decentralized, optimal algorithm is designed to decide the best paths of streams and the most suitable surrogates for video transcoding along the paths, such that the limited bandwidth is fully utilized to deliver streams of the highest possible quality to the mobile recipients. We also carefully tailor a buffering mechanism on each surrogate to cooperate with optimal stream distribution. We have implemented vSkyConf based on Amazon EC2 and verified the excellent performance of our design, as compared to the widely adopted unicast solutions.Comment: 10 page

    A survey of application-level multicast group communication and a proposal for intelligent reflectors

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    The article proposes the state of the art in techniques and models designed to solve issues in application-layer IP multicast. Specifically, the issue of group communication for distributing video flows using reflectors to participants at a videoconference is considered. A proposed solution is introduced, involving an algorithm capable of dynamically discovering the appropriate reflector to meet a given client’s needs. Simulations results show the efficiency of using reflectors in this type of application.5th IFIP International Conference on Network Control & Engineering for QoS, Security and MobilityRed de Universidades con Carreras en Informática (RedUNCI

    DecVi: Adaptive Video Conferencing on Open Peer-to-Peer Networks

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    Video conferencing has become the preferred way of interacting virtually. Current video conferencing applications, like Zoom, Teams or WebEx, are centralized, cloud-based platforms whose performance crucially depends on the proximity of clients to their data centers. Clients from low-income countries are particularly affected as most data centers from major cloud providers are located in economically advanced nations. Centralized conferencing applications also suffer from occasional outages and are embattled by serious privacy violation allegations. In recent years, decentralized video conferencing applications built over p2p networks and incentivized through blockchain are becoming popular. A key characteristic of these networks is their openness: anyone can host a media server on the network and gain reward for providing service. Strong economic incentives combined with lower entry barrier to join the network, makes increasing server coverage to even remote regions of the world. These reasons, however, also lead to a security problem: a server may obfuscate its true location in order to gain an unfair business advantage. In this paper, we consider the problem of multicast tree construction for video conferencing sessions in open p2p conferencing applications. We propose DecVi, a decentralized multicast tree construction protocol that adaptively discovers efficient tree structures based on an exploration-exploitation framework. DecVi is motivated by the combinatorial multi-armed bandit problem and uses a succinct learning model to compute effective actions. Despite operating in a multi-agent setting with each server having only limited knowledge of the global network and without cooperation among servers, experimentally we show DecVi achieves similar quality-of-experience compared to a centralized globally optimal algorithm while achieving higher reliability and flexibility

    Distributed adaptation decision-taking framework and Scalable Video Coding tunneling for edge and in-network media adaptation

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    Optimal Control of Distributed Computing Networks with Mixed-Cast Traffic Flows

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    Distributed computing networks, tasked with both packet transmission and processing, require the joint optimization of communication and computation resources. We develop a dynamic control policy that determines both routes and processing locations for packets upon their arrival at a distributed computing network. The proposed policy, referred to as Universal Computing Network Control (UCNC), guarantees that packets i) are processed by a specified chain of service functions, ii) follow cycle-free routes between consecutive functions, and iii) are delivered to their corresponding set of destinations via proper packet duplications. UCNC is shown to be throughput-optimal for any mix of unicast and multicast traffic, and is the first throughput-optimal policy for non-unicast traffic in distributed computing networks with both communication and computation constraints. Moreover, simulation results suggest that UCNC yields substantially lower average packet delay compared with existing control policies for unicast traffic

    Efficient HEVC-based video adaptation using transcoding

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    In a video transmission system, it is important to take into account the great diversity of the network/end-user constraints. On the one hand, video content is typically streamed over a network that is characterized by different bandwidth capacities. In many cases, the bandwidth is insufficient to transfer the video at its original quality. On the other hand, a single video is often played by multiple devices like PCs, laptops, and cell phones. Obviously, a single video would not satisfy their different constraints. These diversities of the network and devices capacity lead to the need for video adaptation techniques, e.g., a reduction of the bit rate or spatial resolution. Video transcoding, which modifies a property of the video without the change of the coding format, has been well-known as an efficient adaptation solution. However, this approach comes along with a high computational complexity, resulting in huge energy consumption in the network and possibly network latency. This presentation provides several optimization strategies for the transcoding process of HEVC (the latest High Efficiency Video Coding standard) video streams. First, the computational complexity of a bit rate transcoder (transrater) is reduced. We proposed several techniques to speed-up the encoder of a transrater, notably a machine-learning-based approach and a novel coding-mode evaluation strategy have been proposed. Moreover, the motion estimation process of the encoder has been optimized with the use of decision theory and the proposed fast search patterns. Second, the issues and challenges of a spatial transcoder have been solved by using machine-learning algorithms. Thanks to their great performance, the proposed techniques are expected to significantly help HEVC gain popularity in a wide range of modern multimedia applications

    A survey of application-level multicast group communication and a proposal for intelligent reflectors

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    The article proposes the state of the art in techniques and models designed to solve issues in application-layer IP multicast. Specifically, the issue of group communication for distributing video flows using reflectors to participants at a videoconference is considered. A proposed solution is introduced, involving an algorithm capable of dynamically discovering the appropriate reflector to meet a given client’s needs. Simulations results show the efficiency of using reflectors in this type of application.5th IFIP International Conference on Network Control & Engineering for QoS, Security and MobilityRed de Universidades con Carreras en Informática (RedUNCI

    Distributed Rate Allocation in Switch-Based Multiparty Videoconferencing System

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    Multiparty videoconferences, or more generally multiparty video calls, are gaining a lot of popularity as they offer a rich communication experience. These applications have, however, large requirements in terms of both network and computational resources and have to deal with sets of heterogenous clients. The multiparty videoconferencing systems are usually either based on expensive central nodes, called Multipoint Control Units (MCU), with transcoding capabilities, or on a peer-to-peer architecture where users cooperate to distribute more efficiently the different video streams. Whereas the first class of systems requires an expensive central hardware, the second one depends completely on the redistribution capacity of the users, which sometimes might neither provide sufficient bandwidth nor be reliable enough. In this work we propose an alternative solution where we use a central node to distribute the video streams, but at the same time we maintain the hardware complexity and the computational requirements of this node as low as possible, e.g. it has no video decoding capabilities. We formulate the rate allocation problem as an optimization problem that aims at maximizing the Quality of Service (QoS) of the videoconference. We propose two different distributed algorithms for solving the optimization problem: the first algorithm is able to find an approximate solution of the problem in a one-shot execution, whereas the second algorithm, based on Lagrangian relaxation, performs iterative updates of the optimization variables in order to gradually increase the value of the objective function. The two algorithms, though being disjointed, nicely complement each other. If executed in sequence, they allow to achieve both, a quick approximate rate reallocation in case of a sudden change of the system conditions, and a precise refinement of the variables which avoids problems caused by possible faulty approximate solutions. We have further implemented our solution in a network simulator where we show that our rate allocation algorithm is able to properly optimize users' QoS. We also illustrate the benefits of our solution in terms of network usage and overall utility when compared to a baseline heuristic method operating on the same system architecture

    Distributed rate allocation in switch-based multiparty videoconference

    Get PDF
    Multiparty videoconferences, or more generally multiparty video calls, are gaining a lot of popularity as they offer a rich communication experience. These applications have however, large requirements in terms of both network and computational resources and have to deal with sets of heterogenous clients. The multiparty videoconferencing systems can be grouped in two classes. They are based either on expensive central nodes, called multipoint control units (MCU), with transcoding capabilities, or, on a peer-to-peer strategy where users help each other to distribute the different video streams. Whereas the first one requires an expensive central hardware, the second one depends completely on the redistribution capacity of the users, which sometimes might neither provide sufficient bandwidth nor be reliable enough. In this work we propose an alternative solution where we use a central node to distribute the video streams but at the same time we maintain the hardware complexity and the computational requirements of this node as low as possible. The proposed solution uses a distributed algorithm to allocate the users' rates in a Quality of Service (QoS) aware manner. The allocation algorithm is also extremely fast and is able to quickly reallocate the rates in case the conditions change. We have further implemented our solution in a network simulator where we show that our rate allocation algorithm is able to properly optimize users' QoS and adapt to dynamic changes in the system. We also illustrate the benefits of our solution in terms network usage and average utility when compared to a baseline heuristic method operating on the same system architecture
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