1,721,061 research outputs found
Moving Multimedia Simulations into the Cloud: a Cost-Effective Solution
Get PDFResearchers often demand bursts of computing power to quickly obtain the results of certain simulation activities. Multimedia communication simulations usually belong to such category. They may require several days on a generic PC to test a comprehensive set of conditions depending on the complexity of the scenario. This paper proposes to use a cloud computing framework to accelerate these simulations and, consequently, research activities, while at the same time reducing the overall costs. A practical simulation example is shown, representative of a typical simulation of H.264/AVC video communications over a wireless channel. This work shows that, by means of a commercial cloud computing provider, the gains of the proposed technique compared to more traditional solutions using dedicated computers can be significant in terms of speed and cost reductio
Rate-Distortion Optimized Low-Delay 3D Video Communications
No full textThis paper focuses on the rate-distortion optimization of low-delay 3D video communications based on the latest H.264/MVC video coding standard. The first part of the work proposes a new low-complexity model for distortion estimation suitable for low-delay stereoscopic video communication scenarios such as 3D videoconferencing. The distortion introduced by the loss of a given frame is investigated and a model is designed in order to accurately estimate the impact that the loss of each frame would have on future frames. The model is then employed in a rate-distortion optimized framework for video communications over a generic QoS-enabled network. Simulations results show consistent performance gains, up to 1.7 dB PSNR, with respect to a traditional a priori technique based on frame dependency information only. Moreover, the performance is shown to be consistently close to the one of the prescient technique that has perfect knowledge of the distortion characteristics of future frames
Application-Aware Optimization of Packet Scheduling for Video Communications over Intervehicle Ad Hoc Networks
No full textSensor-Based Real-Time Adaptation of 3D Video Encoding Quality for Remote Control Applications
Get PDFThe availability of stereoscopic mobile devices, such as mobile phones, on the consumer market allows to attempt the development of low-cost remote control systems that can provide a real-time 3D video feedback. In this work we show how implement such a communication system by considering the stringent latency constraints of the remote control scenario. To reduce the impact of this issue, we observe that part of the latency is due to the limited processing power of the mobile device that cannot sustain video transmission at high quality with low latency. Thus, we propose to dynamically change the latency-quality trade-off at the transmitter to optimize the quality of experience as perceived by the operator of the remote control system, by taking into account, in real-time, the dynamics of the control operations. In more details, low-cost accelerometer and gyroscopic sensors are employed to decide in real-time how much latency has to be privileged over quality and vice versa, by selectively reducing the quality of one of the views in favor of a reduced overall latency. Comparisons with a non-adaptive higher-quality but also higher-latency system show that the operators prefer the adaptive system despite the video quality is slightly reduced in dynamic control conditions
A cost-effective cloud computing framework for accelerating multimedia communication simulations
Get PDFMultimedia communication research and development often requires computationally intensive simulations in order to develop and investigate the performance of new optimization algorithms. Depending on the simulations, they may require even a few days to test an adequate set of conditions due to the complexity of the algorithms. The traditional approach to speed up this type of relatively small simulations, which require several develop-simulate-reconfigure cycles, is indeed to run them in parallel on a few computers and leaving them idle when developing the technique for the next simulation cycle. This work proposes a new cost-effective framework based on cloud computing for accelerating the development process, in which resources are obtained on demand and paid only for their actual usage. Issues are addressed both analytically and practically running actual test cases, i.e., simulations of video communications on a packet lossy network, using a commercial cloud computing service. A software framework has also been developed to simplify the management of the virtual machines in the cloud. Results show that it is economically convenient to use the considered cloud computing service, especially in terms of reduced development time and costs, with respect to a solution using dedicated computers, when the development time is longer than one hour. If more development time is needed between simulations, the economic advantage progressively reduces as the computational complexity of the simulation increases
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No full textDiscovering users with similar internet access performance through cluster analysis
Get PDFUsers typically subscribe to an Internet access service on the basis of a specific download speed, but the actual service may differ. Several projects are active collecting internet access performance measurements on a large scale at the end user location. However, less attention has been devoted to analyzing such data and to inform users on the received services. This paper presents MiND, a cluster-based methodology to analyze the characteristics of periodic Internet measurements collected at the end user location. MiND allows to discover (i) groups of users with a similar Internet access behavior and (ii) the (few) users with somehow anomalous service. User measurements over time have been modeled through histograms and then analyzed through a new two-level clustering strategy. MiND has been evaluated on real data collected by Neubot, an open source tool, voluntary installed by users, that periodically collects Internet measurements. Experimental results show that the majority of users can be grouped into homogeneous and cohesive clusters according to the Internet access service that they receive in practice, while a few users receiving anomalous services are correctly identified as outliers. Both users and ISPs can benefit from such information: users can constantly monitor the ISP offered service, whereas ISPs can quickly identify anomalous behaviors in their offered services and act accordingly
Opinion Score Distribution Prediction via AI-Based Observers in Media Quality Assessment
Get PDFTraining a Deep Neural Network (DNN) to predict an individual's opinion score regarding the quality of multimedia content is a recent research direction. This type of DNN is called Artificial Intelligence-based Observer (AIO). By generating individual opinion scores, AIOs enable the prediction of the Opinion Score Distribution (OSD) for a given multimedia content. Multimedia image quality assessment literature lacks contributions that thoroughly assess the ability of AIOs to predict the OSD. In this paper a new set of AIOs is trained and shown to predict the OSD more accurately than state-of-the-art methods
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