Implementation of 4kUHD HEVC-content transmission

The Internet of things (IoT) has received a great deal of attention in recent years, and is still being approached with a wide range of views. At the same time, video data now accounts for over half of the internet traffic. With the current availability of beyond high definition, it is worth understanding the performance effects, especially for real-time applications. High Efficiency Video Coding (HEVC) aims to provide reduction in bandwidth utilisation while maintaining perceived video quality in comparison with its predecessor codecs. Its adoption aims to provide for areas such as television broadcast, multimedia streaming/storage, and mobile communications with significant improvements. Although there have been attempts at HEVC streaming, the literature/implementations offered do not take into consideration changes in the HEVC specifications. Beyond this point, it seems little research exists on real-time HEVC coded content live streaming. Our contribution fills this current gap in enabling compliant and real-time networked HEVC visual applications. This is done implementing a technique for real-time HEVC encapsulation in MPEG-2 Transmission Stream (MPEG-2 TS) and HTTP Live Streaming (HLS), thereby removing the need for multi-platform clients to receive and decode HEVC streams. It is taken further by evaluating the transmission of 4k UHDTV HEVC-coded content in a typical wireless environment using both computers and mobile devices, while considering well-known factors such as obstruction, interference and other unseen factors that affect the network performance and video quality. Our results suggest that 4kUHD can be streamed at 13.5 Mb/s, and can be delivered to multiple devices without loss in perceived quality

Prediction of Quality of Experience for Video Streaming Using Raw QoS Parameters

Along with the rapid growth in consumer adoption of modern portable devices, video streaming is expected to dominate a large share of the global Internet traffic in the near future. Today user experience is becoming a reliable indicator for video service providers and telecommunication operators to convey overall end-to-end system functioning. Towards this, there is a profound need for an efficient Quality of Experience (QoE) monitoring and prediction. QoE is a subjective metric, which deals with user perception and can vary due to the user expectation and context. However, available QoE measurement techniques that adopt a full reference method are impractical in real-time transmission since they require the original video sequence to be available at the receiver’s end. QoE prediction, however, requires a firm understanding of those Quality of Service (QoS) factors that are the most influential on QoE. The main aim of this thesis work is the development of novel and efficient models for video quality prediction in a non-intrusive way and to demonstrate their application in QoE-enabled optimisation schemes for video delivery. In this thesis, the correlation between QoS and QoE is utilized to objectively estimate the QoE. For this, both objective and subjective methods were used to create datasets that represent the correlation between QoS parameters and measured QoE. Firstly, the impact of selected QoS parameters from both encoding and network levels on video QoE is investigated. The obtained QoS/QoE correlation is backed by thorough statistical analysis. Secondly, the development of two novel hybrid non-reference models for predicting video quality using fuzzy logic inference systems (FIS) as a learning-based technique. Finally, attention was move onto demonstrating two applications of the developed FIS prediction model to show how QoE is used to optimise video delivery

Packet loss visibility across SD, HD, 3D, and UHD video streams

The trend towards video streaming with increased spatial resolutions and dimensions, SD, HD, 3D, and 4kUHD, even for portable devices has important implications for displayed video quality. There is an interplay between packetization, packet loss visibility, choice of codec, and viewing conditions, which implies that prior studies at lower resolutions may not be as relevant. This paper presents two sets of experiments, the one at a Variable BitRate (VBR) and the other at a Constant BitRate (CBR), which highlight different aspects of the interpretation. The latter experiments also compare and contrast encoding with either an H.264 or an High Efficiency Video Coding (HEVC) codec, with all results recorded as objective Mean Opinion Score (MOS). The video quality assessments will be of interest to those considering: the bitrates and expected quality in error-prone environments; or, in fact, whether to use a reliable transport protocol to prevent all errors, at a cost in jitter and latency, rather than tolerate low levels of packet errors

IEEE 802.11ac wireless delivery of 4kUHD video: The impact of packet loss

This paper examines the 4kUHD video quality from streaming over an IEEE 802.11ac wireless channel, given measured levels of packet loss. Findings suggest that there is a strong content dependency to loss impact upon video quality but that, for short-range transmission, the quality is acceptable, making 4kUHD feasible on head-mounted displays

Implementation of 4kUHD HEVC-content transmission

The Internet of things (IoT) has received a great deal of attention in recent years, and is still being approached with a wide range of views. At the same time, video data now accounts for over half of the internet traffic. With the current availability of beyond high definition, it is worth understanding the performance effects, especially for real-time applications. High Efficiency Video Coding (HEVC) aims to provide reduction in bandwidth utilisation while maintaining perceived video quality in comparison with its predecessor codecs. Its adoption aims to provide for areas such as television broadcast, multimedia streaming/storage, and mobile communications with significant improvements. Although there have been attempts at HEVC streaming, the literature/implementations offered do not take into consideration changes in the HEVC specifications. Beyond this point, it seems little research exists on real-time HEVC coded content live streaming. Our contribution fills this current gap in enabling compliant and real-time networked HEVC visual applications. This is done implementing a technique for real-time HEVC encapsulation in MPEG-2 Transmission Stream (MPEG-2 TS) and HTTP Live Streaming (HLS), thereby removing the need for multi-platform clients to receive and decode HEVC streams. It is taken further by evaluating the transmission of 4k UHDTV HEVC-coded content in a typical wireless environment using both computers and mobile devices, while considering well-known factors such as obstruction, interference and other unseen factors that affect the network performance and video quality. Our results suggest that 4kUHD can be streamed at 13.5 Mb/s, and can be delivered to multiple devices without loss in perceived quality

Antimicrobial Activity of Royal Jelly

Royal jelly (RJ) is a unique secretion that is produced by the mandibular and hypopharyngeal glands of worker bees and used globally for its unique health benefits. It consists mainly of water, proteins, fatty acids, minerals, carbohydrates, vitamins, and other components. RJ as a raw and purified product has been evaluated for its bioactivity in in-vitro, animal and clinical studies and one of the most notable findings was its antimicrobial activity. Although there are many types of antibiotics that can inhibit the growth of pathogenic bacteria, antibiotic-resistant strains have emerged, leading to a search for alternative methods through the re-examination of past remedies. Certain components in RJ have shown antimicrobial effects against a wide range of microbes, including bacteria, viruses, yeast, and fungi. Trans-10- hydroxy-2-decenoic acid, Royalisin, and Jelleines are the main antimicrobial biaoctives obtained from RJ, and they have significant antibacterial potential. This review is on the antimicrobial effects of RJ and their potential use in medical and other applications

QoE-enabled transport optimisation scheme for real-time SVC video delivery

Video traffic today accounts for 50 percent of all traffic on the network and is set to reach the 70 percent mark in a few years. Bringing in large volumes of video traffic threatens to exceed the network's capacity. As a result, traffic congestion is becoming more frequent, degrading the Quality of Experience (QoE) for video consumers. In this paper, we present a QoE-enabled Transport Optimization Scheme (QETOS) for real-time scalable video stream. The proposed scheme is a crucial design choice that will optimise the video traffic by mapping video quality degradations (that are caused by network) to the QoE without penetrating the video packets. It takes the advantage of the Scalable Video Coding (SVC) partitions that can organize video into layers of different importance, facilitating rate adaptation of video streams. Our approach will help to minimize the side effects on user perceived quality

Optimising the delivery of Scalable H.264 Video stream by QoS/QoE correlation

We present a novel system that optimizes the video delivery by mapping network conditions (QoS) to the QoE without penetrating video packets. It takes the advantage of the Scalable Video Coding (SVC) that can organize video streams into different layers. Our approach helps to maximize the QoE with respect to capacity constraints

Resource Allocation Scheme Based on Online QoE Estimation of Mobile H.264 Video Streaming

Demand on multimedia content by consumers' handheld devices over wireless channels is on the increase. In view of the accelerated trend towards consumption of high quality video, power utilization by mobile devices is expected to excessively increase. This paper presents a power and bandwidth efficient resource allocation scheme considering the end user's Quality of Experience (QoE) in the context of mobile video streaming. QoE has become the prime performance criterion for media delivery technologies. The QoE is estimated by an objective online estimation model based on adaptive Fuzzy Inference Systems (FIS). We simulate a mobile video transmission through which we identify the correlation between receiver's signal-to-noise ratio and QoE. Compared to QoS-based techniques, the proposed QoE-based scheme enables to save up to 33.13% in power and grant up to 50% more data bits for transmission

Intelligent Botnet Detection Approach in Modern Applications

Innovative applications are employed to enhance human-style life. The Internet of Things (IoT) is recently utilized in designing these environments. Therefore, security and privacy are considered essential parts to deploy and successful intelligent environments. In addition, most of the protection systems of IoT are vulnerable to various types of attacks. Hence, intrusion detection systems (IDS) have become crucial requirements for any modern design. In this paper, a new detection system is proposed to secure sensitive information of IoT devices. However, it is heavily based on deep learning networks. The protection system can provide a secure environment for IoT. To prove the efficiency of the proposed approach, the system was tested by using two datasets; normal and fuzzification datasets. The accuracy rate in the case of the normal testing dataset was 99.30%, while was 99.42% for the fuzzification testing dataset. The experimental results of the proposed system reflect its robustness, reliability, and efficiency