Video Transmission Framework Research Articles

Optimized Visual Internet of Things for Video Streaming Enhancement in 5G Sensor Network Devices.

The global expansion of the Visual Internet of Things (VIoT)'s deployment with multiple devices and sensor interconnections has been widespread. Frame collusion and buffering delays are the primary artifacts in the broad area of VIoT networking applications due to significant packet loss and network congestion. Numerous studies have been carried out on the impact of packet loss on Quality of Experience (QoE) for a wide range of applications. In this paper, a lossy video transmission framework for the VIoT considering the KNN classifier merged with the H.265 protocols. The performance of the proposed framework was assessed while considering the congestion of encrypted static images transmitted to the wireless sensor networks. The performance analysis of the proposed KNN-H.265 protocol is compared with the existing traditional H.265 and H.264 protocols. The analysis suggests that the traditional H.264 and H.265 protocols cause video conversation packet drops. The performance of the proposed protocol is estimated with the parameters of frame number, delay, throughput, packet loss ratio, and Peak Signal to Noise Ratio (PSNR) on MATLAB 2018a simulation software. The proposed model gives 4% and 6% better PSNR values than the existing two methods and better throughput.

A Quality-of-Experience-Aware Framework for Versatile Video Coding-Based Video Transmission

Multimedia applications have expanded and resulted in huge demands for high resolution videos in order to enhance the end user Quality of Experience (QoE). Therefore, QoE becomes a critical factor that is often addressed in design considerations of Consumer Electronics (CE) devices. Furthermore, error prone transmission conditions can influence the QoE, potentially degrading the end-user multimedia experience. Although video coding standards such as Versatile Video Coding (VVC) take potential mitigation measures to improve the bandwidth reductions, it fails to address other significant network Quality of Service (QoS) parameters that impact transmission based QoE such as transmission delay and Packet Loss Rate (PLR) in the encoding processes. In response, this paper first derives a relationship between QoE that addresses the network QoS parameters and VVC dependent parameters. Subsequently, the derived QoE model is used with the VVC encoding process to adaptively optimize Lagrange parameters as well as the quantization parameter. Extensive experiments report significant improvements to VVC Test Model (VTM) 7.0, achieving superior QoE gains over the state-of-the-art research and up to 3.41% over the anchor implementations.

EdgeSaver: Edge-Assisted Energy-Aware Mobile Video Streaming for User Retention Enhancement

Video streaming service is one of the most important IoT applications/services at the mobile end. To provide better services and earn more customers, the mobile video service providers have paid considerable attention to enhance end users&#x2019; Quality of Experience (QoE) in video streaming. As an important aspect of the mobile device, however, the battery power and its impacts on the mobile services were seldom concerned. According to our survey over 2000&#x002B; mobile users, the low battery power of mobile phones could cause the user to give up watching videos. To quantify the relationship between the battery power and user&#x2019;s video abandoning probability (VAP), we first extract the VAP model from the collected survey data, leveraging a reversed accumulative histogram approach. Then, referring to the quantified VAP model, we present <i>EdgeSaver</i>, an edge-assisted video transmission framework, which aims at maintaining a sustainable overall user retention rate for the service providers by reducing the power consumption of video playback at the mobile ends. Particularly, as the core component of <i>EdgeSaver</i>, a low-power video scheduler is designed to strategically select user groups, such that the most profitable outcome can be achieved under the constraints of limited edge resources. With extensive experiments using a real-world data set, we demonstrate that <i>EdgeSaver</i> can help the mobile video service provider improve the user retention rate by up to 30&#x0025; and increase the average user viewing time by 20&#x0025;.

Design of Robust Video Transmission System by Using Efficient Forward Error Correction Scheme

The advent of modern digital technologies has made multimedia communication systems one of the most demanding technologies of the time. The use of available bandwidth for efficient and errorless multimedia communication is the key challenge for the wireless communication research community. However, a wireless network has the disadvantage of being prone to random channel noise and data contamination. This paper proposes a robust video transmission framework by using an efficient forward error correction technique. In this work, the experimental performance of widely used forward error correction codes i.e., Convolution codes, LDPC codes, Turbo codes, and Concatenated codes, are compared based on their capability to compensate the channel noise and distortion. An efficient encoding scheme is devised for the transmission of YUV encoded frames by using the selected FEC codes in a noisy channel environment. The retrieved video is analysed by using the Peak Signal-to-Noise ratio and bit error rate as performance metrics. The results and cross comparison shows that concatenated codes have a handsome improvement in avoiding channel contamination and distortion.

Secure Video Transmission Framework for Battery-Powered Video Devices

Selective video encryption schemes for battery-powered video devices have been proposed to prevent illegal acquisition of recorded video during transmission. However, the transmission security of conventional schemes is lower than the fully encrypted transmission schemes because a substantial part of the recorded video remains unencrypted including significant metadata for decoding recorded video. In order to address this limitation, we propose a secure video transmission framework that selectively encrypts video metadata and frames on a per packet basis with a consideration of currently available computing power and transmission distance. Evaluation on a testbed demonstrates that the proposed framework provides enhanced video transmission security with less than half of the battery power consumption required by the fully encrypted transmission scheme.

Efficient security framework for reliable wireless 3D video transmission

Efficient security framework for reliable wireless 3D video transmission

LensCast: Robust Wireless Video Transmission Over MmWave MIMO With Lens Antenna Array

In this paper, we present LensCast, a novel cross-layer video transmission framework for wireless networks, which seamlessly integrates millimeter wave (mmWave) lens multiple-input multiple-output (MIMO) with robust video transmission. LensCast is designed to exploit the video content diversity at the application layer, together with the spatial path diversity of lens antenna array at the physical layer, to achieve graceful video transmission performance under varying channel conditions. In LensCast, a transmission distortion minimization problem is formulated with the consideration of video chunk scheduling, path matching and power allocation, which is an intractable mixed integer non-linear programming (MINLP) problem. The solution of this MINLP problem is converted into resource allocation (i.e., joint path matching and power allocation) plus chunk scheduling. First, resource allocation is investigated with given chunk scheduling results. By analyzing the optimality of the resource allocation problem, a winner-takes-all assignment is obtained to guide resource allocation. After that, a greedy water-filling algorithm is proposed as a near-optimal solution. Second, we propose a low-complexity chunk scheduling algorithm to schedule chunks for each transmission. Simulation results demonstrate that the proposed LensCast achieves an improved performance in terms of both peak signal-to-noise ratio and visual quality comparing with reference schemes.

Development of a real-time framework for farm monitoring using drone technology

This work developed a cost-effective framework for agriculturists to regularly monitor their crops against intruding rodents and other security concerns using modern drone technology through configuration and deployment of an autonomous UAV which also functions as a remotely piloted vehicle. This was done by configuring a quadcopter capable of causing a disturbance when a rodent is observed through an inbuilt alarm system whose sound is amplified to be loud enough to cause the animals to leave the farm area. A framework for real-time image and live video transmission from the farm to a designated remote base station was developed. This was achieved through programming codes that configured the drone to operate an intelligent alarm and object tracking systems which enables a live feed from the UAV using Arduino IDE and Mission Planner for autonomous flight control. The requisite algorithms were developed using the framework of tracking, learning and detection (TLD) in the OpenCV software. The drone movement is equally controlled remotely over a Wi-Fi network using an ESP8266 Wi-Fi module for redirection and controlling of the drone movement to monitor specific locations.

Toward Convergence of AI and IoT for Energy-Efficient Communication in Smart Homes

The convergence of artificial intelligence (AI) and the Internet of Things (IoT) promotes energy-efficient communication in smart homes. Quality-of-Service (QoS) optimization during video streaming through wireless micro medical devices (WMMDs) in smart healthcare homes is the main purpose of this research. This article contributes in four distinct ways. First, to propose a novel lazy video transmission algorithm (LVTA). Second, a novel video transmission rate control algorithm (VTRCA) is proposed. Third, a novel cloud-based video transmission framework is developed. Fourth, the relationship between buffer size and performance indicators, i.e., peak-to-mean ratio (PMR), energy (i.e., encoding and transmission), and standard deviation, is investigated while comparing LVTA, VTRCA, and baseline approaches. The experimental results demonstrate that the reduction in encoding (32% and 35.4%) and transmission (37% and 39%) energy drains, PMR (5 and 4), and standard deviation (3 and 4 dB) for VTRCA and LVTA, respectively, is greater than that obtained by baseline during video streaming through WMMD.

Astute Video Transmission for Geographically Dispersed Devices in Visual IoT Systems

Visual IoT (VIoT) is a promising IoT paradigm that visualizes sensing data from massive numbers of dispersed devices. A key objective in VIoT is to efficiently manage the devices to perform complex task-related visual data processing. Prior multimedia IoT systems have mainly focused on the delivery of captured video to remote servers, without considering the video tasks’ characteristics and the devices’ heterogeneous capabilities. In this work, we propose an astute video transmission framework for such a VIoT system composed of heterogeneous visual devices. First, we formulate the problem of joint video task allocation and heterogeneous device management by constructing a device hypergraph (DH) structure, which enables devices with different capabilities to perform complex video tasks cooperatively. Second, we model the video transmission within a VIoT system by applying fractal theory considering the NP-hardness of the optimization. In particular, we construct a comprehensive fractal submodular optimization framework through a DH and explore the inner submodular property to effectively leverage both video-task complexity and device heterogeneity. Third, we consider the geographically dispersed characteristic of massive numbers of VIoT devices and propose a multi-hop dispersed transmission mechanism for achieving globally cooperative optimality. The proposed architecture has been evaluated under diverse parameter settings. Numerical results are provided to validate the proposed algorithm in terms of delay, computational efficiency, and bandwidth utilization. Simulation results confirm the effectiveness and superiority of the proposed method.

A QoE-Based Framework for Video Streaming Over LTE-Unlicensed

To improve the system capacity and accommodate the ever-increasing demand for bandwidth by the network users, LTE service providers have turned their attention to the unlicensed industrial, scientific, and medical (ISM) spectrum; currently heavily utilized by the users of the IEEE 803.11 standards or WiFi. Unfortunately, such an approach, referred to as LTE-U, causes co-existence problems which necessitates the development of effective spectrum-sharing mechanisms to mitigate the interference with WiFi users. In this work, we propose a framework for video transmission over LTE-U to achieve harmonious coexistence with WiFi systems while taking into account the quality of experience (QoE) requirements of the user equipment (UE). In the proposed scheme, the channel allocation aims to enhance the peak signal-to-noise ratio (PSNR) and to reduce the end-to-end delay of video packets. We present analytical schemes for predicting PSNR and delay of the received video sequence based on video parameters transmitted by the video server and periodic feedback from the UE, which provides the signal-to-noise ratio (SNR) of the channel. In addition, the probability of causing interference to WiFi users is used to formulate the channel allocation problem as a multi-objective optimization problem. Taking into account the received video quality and the achieved inter-frame delay for both LTE-U and WiFi users, the simulation results show that the proposed scheme outperforms a reference model that employs a channel access mechanism but randomly assigns frames to the available channels.

An optimal bandwidth allocation algorithm for improving QoS in WiMAX

In the last few years, the term “quality of service” has become increasingly synonymous with digital cellular networks and has greatly influenced the way we manage network traffic. The IEEE 802.16 standard is a broadband wireless access system that enables high speed data transfer over large distances. It is one of the standards that meet the IMT-Advanced specifications. It also incorporates a quality of service framework to provide quality of service to both realtime and non-realtime multimedia applications. One of the critical contributions of a QoS framework is efficient scheduling of network traffic. This paper dilates on a two-level scheduling algorithm for base station uplink scheduler to provide quality of service to various classes of traffic. The proposed algorithm ensures efficient and fair multimedia transmission. We also deliberated on a video transmission framework based on the proposed algorithm. The performance of two-level scheduling algorithm has been extensively analyzed through simulations and the results have effectively established the efficacy of the proposed algorithm. The results reveal that the the proposed algorithm is able to fairly and efficiently schedule network traffic while ensuring quality of service for all classes of traffic.

Energy-efficient joint video encoding and transmission framework for WVSN

In this paper, we propose an energy-efficient joint video encoding and transmission framework for network lifetime extension, under an end-to-end video quality constraint in the Wireless Video Sensor Networks (WVSN). This framework integrates an energy-efficient and adaptive intra-only video encoding scheme based on the H.264/AVC standard, that outputs two service differentiated macroblocks categories, namely the Region Of Interest and the Background. Empirical models describing the physical behavior of the measured energies and distortions, during the video encoding and transmission phases, are derived. These models enable the video source node to dynamically adapt its video encoder’s configuration in order to meet the desired quality, while extending the network lifetime. An energy-efficient and reliable multipath multi-priority routing protocol is proposed to route the encoded streams to the sink, while considering the remaining energy, the congestion level as well as the packet loss rates of the intermediate nodes. Moreover, this protocol interacts with the application layer in order to bypass congestion situations and continuously feed it with current statistics. Through extensive numerical simulations, we demonstrate that the proposed framework does not only extend the video sensor lifetime by 54%, but it also performs significant end-to-end video quality enhancement of 35% in terms of Mean Squared Error (MSE) measurement.

A Practical Hybrid Digital-Analog Scheme for Wireless Video Transmission

We propose a hybrid digital-analog framework for wireless video transmission, which benefits from both the high distortion-power performance of digital systems and the graceful performance degradation of analog systems. The proposed framework models video frames as a parallel Gaussian source, which is separated into digital and analog parts through scalar quantization. It features entropy coding and channel coding in digital transmission and power scaling in analog transmission. The key challenge in this framework is how to allocate the constrained power and bandwidth resources between and among digital and analog components to achieve minimal distortion at the receiver. Given the worst-case channel signal-to-noise ratio, we are able to derive a closed-form expression of the overall distortion. However, minimizing it is a mixed-integer non-linear programming problem, which is generally non-deterministic polynomial-time hard. By making reasonable and justified simplifications, we approach the optimal solution through a practical scheme. Evaluations show that the proposed scheme outperforms the state-of-the-art analog scheme SoftCast by a large margin. The gain in received video peak signal-to-noise ratio is up to 5.0 dB for various types of videos.

Cloud-assisted secure video transmission and sharing framework for smart cities

With the innovations and increasing popularity of smart cities, video analytics (e.g., from social media, entertainment, surveillance, smart health monitoring, and crowd management) are used in a range of application domains to provide safety, security, and well-being for residents. As these video analytics are shared through highly interconnected devices, sensors, and other smart city stakeholders, security and integrity is a concern for secure video content. Without proper techniques to address the security threats of such transmission and sharing, it would be very difficult for a smart city government to provide safety and quality-of-life to its residents. To this end, this paper proposes a cloud-assisted framework for secure video transmission and sharing, where mobile clients have limited capabilities; however, users need to share videos seamlessly without sacrificing integrity and quality. In the proposed framework, once the video is captured by a smart phone, the key frames are detected. The key frames are detected by applying a genetic algorithm (GA). A discrete wavelet transform (DWT) based watermarking algorithm is used to insert the watermark into the key frames. A two layer protection mechanism based on error correcting codes is applied to the signature or identity of an individual to generate the watermark that is inserted into the video to protect it from any transmission loss, distortion or attacks. Watermarked video is then transmitted to the cloud. The watermark is also shared to a number of clouds in a space efficient and secret-robust way. To check the integrity of the video, the original user can at any time download the video, extract the watermark, and verify it. To test the quality of the watermarked video, imperceptibility analysis is carried out using PSNR and structural similarity index measure (SSIM). The experiment results demonstrate that the watermarking algorithm does not degrade the quality of the video.

ROI-Based Video Transmission in Heterogeneous Wireless Networks With Multi-Homed Terminals

We consider the problem of delivering region of interest (ROI)-coded mobile video streams using limited radio resources. Under the conditions of limited bandwidth and time-varying channel status, the goal is to optimize the transmission latency, while ensuring the quality of the ROI parts. Multi-homing support enables the terminals to establish multiple connections for transmission performance improvement. In this paper, we propose a novel framework for ROI-based video transmission in heterogeneous wireless networks with multi-homed terminals. The framework contains the modules of ROI detector and frame splitter, where macroblocks are categorized based on ROI detection and encapsulated into transforming units. It also includes a channel monitor that keeps track of the status of each communication path and sends feedback signals to the streaming controller for packet-scheduling control; a deep learning method is proposed for channel status prediction. To address the delivery problem, we propose a scheduling approach based on the formulated network model and the rate-distortion model. The scheduling method makes a tradeoff between the transmission delay and the distortion. It also guarantees that packets with ROI content are delivered on paths with sufficient bandwidths and low loss rates. Through comparisons with other scheduling methods, we find that the proposed scheme outperforms the other scheduling methods in terms of improving the quality (peak signal-to-noise ratio), balancing the end-to-end delay, and maintaining the playback fluency.

Green and friendly media transmission algorithms for wireless body sensor networks

Video transmission is considered as a quite significant step towards health monitoring of the emergency patients during any critical incident. However, the energy hungry video transmission and slow progress in battery technologies have become a major and serious problem for the evolution of video technology in WBSNs. Therefore, the need arose to conduct research on sustainable, “Green”, i.e., energy-efficient and “Friendly”, i.e., battery-friendly technologies to cater the need of upcoming mobile and portable devices. The main challenge addressed in this research is how to increase the battery lifetime during on-demand Variable Bit Rate (VBR) video transmission from medical video server to base station in WBSNs. In order to overcome this problem, sustainable, Green and Friendly frame transmission algorithms are enunciated i.e. Lazy Algorithm (LA) and Battery-friendly Smoothing Algorithm (BSA) with analytical battery model. The proposed algorithms minimize transmission energy consumption, battery charge consumption and high current profile. These algorithms also prolongs the battery lifetime of those sensor nodes during video transmission. Experimental results demonstrates that BSA outperforms LA to minimize battery drain by improving its lifetime up to 19.8 %. However, the LA performs better than BSA in context of transmission energy saving up to 49.49 %. Furthermore, a video transmission framework of Remote Medical Education System (RMES) for elderly persons and infants is proposed to provide viable and sustainable battery solutions to serve the community.

Hybrid digital-analog video transmission in wireless multicast and multiple-input multiple-output system

Wireless video multicast has become one of the key technologies in wireless applications. But the main challenge of conventional wireless video multicast, i.e., the cliff effect, remains unsolved. To overcome the cliff effect, a hybrid digital-analog (HDA) video transmission framework based on SoftCast, which transmits the digital bitstream with the quantization residuals, is proposed. With an effective power allocation algorithm and appropriate parameter settings, the residual gains can be maximized; meanwhile, the digital bitstream can assure transmission of a basic video to the multicast receiver group. In the multiple-input multiple-output (MIMO) system, since nonuniform noise interference on different antennas can be regarded as the cliff effect problem, ParCast, which is a variation of SoftCast, is also applied to video transmission to solve it. The HDA scheme with corresponding power allocation algorithms is also applied to improve video performance. Simulations show that the proposed HDA scheme can overcome the cliff effect completely with the transmission of residuals. What is more, it outperforms the compared WSVC scheme by more than 2 dB when transmitting under the same bandwidth, and it can further improve performance by nearly 8 dB in MIMO when compared with the ParCast scheme.

Energy Efficient and QoS Aware Framework for Video Transmission over Wireless Sensor Networks

Wireless Multimedia Sensor Networks (WMSNs), is a network of sensors, which are limited in terms of memory, computing, bandwidth, and battery lifetime. Multimedia transmission over WSN requires certain QoS guarantees such as huge amount of bandwidth, strict delay and lower loss ratio that makes transmitting multimedia is a complicated task. However, adopting cross-layer approach in WMSNs improves quality of service of WSN under different environmental conditions. In this work, an energy efficient and QoS aware framework for transmitting multimedia content over WSN (EQWSN) is presented, where packet, queue and path scheduling were introduced. It adapts the application layer parameter of video encoder to current wireless channel state, and drops less important packets in case of network congestion according to packet type. Finally, the path scheduling differentiates packets types/priority and route them through different paths with different QoS considering network lifetime. Simulation results show that the new scheme EQWSN transmits video quality with QoS guarantees in addition to prolonging network lifetime.

SVCEval-RA: an evaluation framework for adaptive scalable video streaming

Multimedia content adaption strategies are becoming increasingly important for effective video streaming over the actual heterogeneous networks. Thus, evaluation frameworks for adaptive video play an important role in the designing and deploying process of adaptive multimedia streaming systems. This paper describes a novel simulation framework for rate-adaptive video transmission using the Scalable Video Coding standard (H.264/SVC). Our approach uses feedback information about the available bandwidth to allow the video source to select the most suitable combination of SVC layers for the transmission of a video sequence. The proposed solution has been integrated into the network simulator NS-2 in order to support realistic network simulations. To demonstrate the usefulness of the proposed solution we perform a simulation study where a video sequence was transmitted over a three network scenarios. The experimental results show that the Adaptive SVC scheme implemented in our framework provides an efficient alternative that helps to avoid an increase in the network congestion in resource-constrained networks. Improvements in video quality, in terms of PSNR (Peak Signal to Noise Ratio) and SSIM (Structural Similarity Index) are also obtained.