Evaluating the Use of QoS for Video Delivery in Vehicular Networks

In a near future, video transmission capabilities in intelligent vehicular networks will be essential for deploying high-demanded multimedia services for drivers and passengers. Applications and services like video on demand, iTV, context-aware video commercials, touristic information, driving assis-tance, multimedia e-call, etc., will be part of the common multimedia service-set of future transportation systems. However, wireless vehicular networks introduce several constraints that may seriously impact on the final quality of the video content delivery process. Factors like the shared-medium communication model, the limited bandwidth, the unconstrained delays, the signal propagation issues, and the node mobility, will be the ones that will degrade video delivery performance, so it will be a hard task to guarantee the minimum quality of service required by video applications. In this work, we will study how these factors impact on the received video quality by using a detailed simulation model of a urban vehicular network scenario. We will apply different techniques to reduce the video quality degradation produced by the transmission impairments like (a) Intra-refresh video coding modes, (b) frame partitioning (tiles/slices), and (c) quality of service at the Medium Access Control (MAC) level. So, we will learn how these techniques are able to fight against the network impairments produced by the hostile environment typically found in vehicular network scenarios. The experiments were carried out with a simulation environment based on the OMNeT++, Veins and SUMO simulators. Results show that the combination of the proposed techniques significantly improves the robustness of video transmission in vehicular networks, paving the way, with a wise collaboration with other techniques, to achieve a robust video delivery system that supports multimedia applications in future intelligent transportation systems

A Simulation Tool for Evaluating Video Streaming Architectures in Vehicular Network Scenarios

An integrated simulation tool called Video Delivery Simulation Framework over Vehicular Networks (VDSF-VN) is presented. This framework is intended to allow users to conduct experiments related to video transmission in vehicular networks by means of simulation. Research on this topic requires the use of many independent tools, such as traffic and network simulators, intermediate frameworks, video encoders and decoders, converters, platform-dependent scripting languages, data visualisation packages and spreadsheets, and some other tasks are performed manually. The lack of tools necessary to carry out all these tasks in an integrated and efficient way formed the motivation for the development of the VDSF-VN framework. It is managed via two user-friendly applications, GatcomSUMO and GatcomVideo, which allow all the necessary tasks to be accomplished. The first is primarily used to build the network scenario and set up the traffic flows, whereas the second involves the delivery process of the whole video, encoding/decoding video, running simulations, and processing all the experimental results to automatically provide the requested figures, tables and reports. This multiplatform framework is intended to fill the existing gap in this field, and has been successfully used in several experimental tests of vehicular network

Design and implementation of an efficient hardware integer motion estimator for an HEVC video encoder

High-Efficiency Video Coding (HEVC) was developed to improve its predecessor standard, H264/AVC, by doubling its compression efficiency. As in previous standards, Motion Estimation (ME) is one of the encoder critical blocks to achieve significant compression gains. However, it demands an overwhelming complexity cost to accurately remove video temporal redundancy, especially when encoding very high-resolution video sequences. To reduce the overall video encoding time, we propose the implementation of the HEVC ME block in hardware. The proposed architecture is based on (a) a new memory scan order, and (b) a new adder tree structure, which supports asymmetric partitioning modes in a fast and efficient way. The proposed system has been designed in VHDL (VHSIC Hardware Description Language), synthesized and implemented by means of the Xilinx FPGA, Virtex-7 XC7VX550T-3FFG1158. Our design achieves encoding frame rates up to 116 and 30 fps at 2 and 4K video formats, respectively

Simulation Framework for Evaluating Video Delivery Services over Vehicular Networks

Vehicular Ad-hoc Networks contribute to the Intelligent Transportation Systems by providing a set of services related to traffic, mobility, safe driving, and infotainment applications. One of the most challenging applications is video delivery, since it has to deal with several hurdles typically found in wireless communications, like high node mobility, bandwidth limitations and high loss rates. In this work, we propose an integrated simulation framework that will provide a multilayer view of a particular video delivery session with a bunch of simulation results at physical (i.e., collisions), MAC (i.e., packet delay), application (i.e.,%of lost frames), and user levels (i.e., perceptual video quality). With this tool, we can analyze the performance of video streaming over vehicular networks with a high level of detail, giving us the keys to better understand and, as a consequence, improve video delivery services

On the use of deep learning and parallelism techniques to signifcantly reduce the HEVC intra‑coding time

It is well-known that each new video coding standard signifcantly increases in computational complexity with respect to previous standards, and this is particularly true for the HEVC and VVC video coding standards. The development of techniques for reducing the required complexity without afecting the rate/distortion (R/D) performance is therefore always a topic of intense research interest. In this paper, we propose a combination of two powerful techniques, deep learning and parallel computing, to signifcantly reduce the complexity of the HEVC encoding engine. Our experimental results show that a combination of deep learning to reduce the CTU partitioning complexity with parallel strategies based on frame partitioning is able to achieve speedups of up to 26× when 16 threads are used. The R/D penalty in terms of the BD-BR metric depends on the video content, the compression rate and the number of OpenMP threads, and was consistently between 0.35 and 10% for the video sequence test set used in our experiment

Load Balancing Strategies for Slice-Based Parallel Versions of JEM Video Encoder

The proportion of video traffic on the internet is expected to reach 82% by 2022, mainly due to the increasing number of consumers and the emergence of new video formats with more demanding features (depth, resolution, multiview, 360, etc.). Efforts are therefore being made to constantly improve video compression standards to minimize the necessary bandwidth while retaining high video quality levels. In this context, the Joint Collaborative Team on Video Coding has been analyzing new video coding technologies to improve the compression efficiency with respect to the HEVC video coding standard. A software package known as the Joint Exploration Test Model has been proposed to implement and evaluate new video coding tools. In this work, we present parallel versions of the JEM encoder that are particularly suited for shared memory platforms, and can significantly reduce its huge computational complexity. The proposed parallel algorithms are shown to achieve high levels of parallel efficiency. In particular, in the All Intra coding mode, the best of our proposed parallel versions achieves an average efficiency value of 93.4%. They als

Analysis of the perceptual quality performance of different HEVC coding tools

Each new video encoding standard includes encoding techniques that aim to improve the performance and quality of the previous standards. During the development of these techniques, PSNR was used as the main distortion metric. However, the PSNR metric does not consider the subjectivity of the human visual system, so that the performance of some coding tools is questionable from the perceptual point of view. To further explore this point, we have developed a detailed study about the perceptual sensibility of different HEVC video coding tools. In order to perform this study, we used some popular objective quality assessment metrics to measure the perceptual response of every single coding tool. The conclusion of this work will help to determine the set of HEVC coding tools that provides, in general, the best perceptual response

Optimizing the Transmission of Multimedia Content over Vehicular Networks

The multi channel operation mechanism of the IEEE 1609.4 protocol, used in vehicular networks, may impact network performance if applications do not care about its details. Packets delivered from the application layer to the MAC layer during a Control Channel time slot have to wait to be transmitted until the following Service Channel time slot arrives. The accumulation of packets at the beginning of this time slot may introduce additional delays and higher collision rates when packets are transmitted. In this work we propose a method, which we call SkipCCH, that deals with this issue in order to make a better use of the wireless channel and, as a consequence, increase the overall network performance. With our proposal, streaming video in vehicular networks will provide better reconstructed quality at the receiver side under the same network conditions. Furthermore, this method has particularly proven its benefits when working with QoS techniques, not only by increasing the received video quality, but also because it avoids starvation of the lower priority traffic

Monitoring pest insect traps by means of low-power image sensor technologies

Monitoring pest insect populations is currently a key issue in agriculture and forestry protection. At the farm level, human operators typically must perform periodical surveys of the traps disseminated through the field. This is a labor-, time- and cost-consuming activity, in particular for large plantations or large forestry areas, so it would be of great advantage to have an affordable system capable of doing this task automatically in an accurate and a more efficient way. This paper proposes an autonomous monitoring system based on a low-cost image sensor that it is able to capture and send images of the trap contents to a remote control station with the periodicity demanded by the trapping application. Our autonomous monitoring system will be able to cover large areas with very low energy consumption. This issue would be the main key point in our study; since the operational live of the overall monitoring system should be extended to months of continuous operation without any kind of maintenance (i.e., battery replacement). The images delivered by image sensors would be time-stamped and processed in the control station to get the number of individuals found at each trap. All the information would be conveniently stored at the control station, and accessible via Internet by means of available network services at control station (WiFi, WiMax, 3G/4G, etc.). © 2012 by the authors; licensee MDPI, Basel, Switzerland.This work was partially funded by Ministry of Education and Science grants CTM2011-29691-C02-01, TIN2011-28435-C03-01 and TIN2011-27543-C03-03.López ., O.; Martinez Rach, MO.; Migallon ., H.; Pérez Malumbres, MJ.; Bonastre Pina, AM.; Serrano Martín, JJ. (2012). Monitoring pest insect traps by means of low-power image sensor technologies. Sensors. 12(11):15801-15819. doi:10.3390/s121115801S15801158191211Shelton, A. M., & Badenes-Perez, F. R. (2006). CONCEPTS AND APPLICATIONS OF TRAP CROPPING IN PEST MANAGEMENT. Annual Review of Entomology, 51(1), 285-308. doi:10.1146/annurev.ento.51.110104.150959Jiang, J.-A., Tseng, C.-L., Lu, F.-M., Yang, E.-C., Wu, Z.-S., Chen, C.-P., … Liao, C.-S. (2008). A GSM-based remote wireless automatic monitoring system for field information: A case study for ecological monitoring of the oriental fruit fly, Bactrocera dorsalis (Hendel). Computers and Electronics in Agriculture, 62(2), 243-259. doi:10.1016/j.compag.2008.01.005http://www.memsic.comAl-Saqer. (2011). Red Palm Weevil (Rynchophorus Ferrugineous, Olivier) Recognition by Image Processing Techniques. American Journal of Agricultural and Biological Sciences, 6(3), 365-376. doi:10.3844/ajabssp.2011.365.376http://www.ti.com/lit/ds/symlink/cc1110f32.pdfhttp://www.comedia.com.hkOliver, J., & Perez Malumbres, M. (2008). On the Design of Fast Wavelet Transform Algorithms With Low Memory Requirements. IEEE Transactions on Circuits and Systems for Video Technology, 18(2), 237-248. doi:10.1109/tcsvt.2007.91396