Moustafa M. Nasralla

A downlink scheduling approach for balancing QoS in LTE wireless networks

In this paper, we propose a strategy for resource allocation for different traffic classes at the Medium Access Control (MAC) layer of wireless systems based on Orthogonal Frequency Division Multiple Access (OFDMA), such as the recent Long-Term Evolution (LTE) wireless standard. In order to achieve inter-class fairness, we propose a modification of the Virtual Token Modified Largest Weighted Delay First (VT-M-LWDF) and Modified Largest Weighted Delay First (M-LWDF) rules. Through simulation, we show that the proposed scheduler introduces remarkable multi-objective improvement of the Quality of Service (QoS) performance parameters, i.e., Packet Loss Rate (PLR), average throughput, fairness index and system spectral efficiency, among different classes of traffic such as video, VoIP and best-effort.

3-D robotic tele-surgery and training over next generation wireless networks

The latest advances on robotic surgery enable the performance of many surgical procedures by utilizing minimally invasive techniques. In particular, recent 3-D endoscopes have improved the performance of minimally invasive surgical procedures. Based on these advances, performing or visualizing in real-time surgical procedures at a distance can be envisaged. In this paper, we present a performance evaluation of 3-D robotic tele-surgery and training over next generation wireless networks, namely wireless networks based on the long term evolution (LTE) 3GPP standard. Different scheduling strategies are compared and results are analyzed in term of the resulting quality of experience (QoE) for the surgeon.

Subjective and objective evaluation and packet loss modeling for 3D video transmission over LTE networks

The recent Long-Term Evolution (LTE) standard, thanks to the provision of high data rates, will enable bandwidth demanding multimedia applications like Three Dimensional (3D) video streams over wireless. In this paper, we study the transmission of 3D video sequences over LTE networks by modeling an LTE wireless network, which uses the best performing downlink packet scheduling strategy (Modified Largest Weighted Delay First (M-LWDF)) for delay sensitive applications, through the well-known Gilbert-Elliot Channel Model (GE). Also, we perform subjective and objective quality evaluation of the received 3D video sequences. The perceived video sequences are impaired with six packet loss rates produced by the corresponding LTE network. The three major contributions of the paper are: 1) GE parameters that represent real statistics of an LTE network 2) a subjective study on 3D video transmission over an LTE system modeled as a GE channel for different levels of impairments and 3) the provision of a publicly available database with 3D video sequences affected by packet losses distributed according to a GE model and associated Mean Opinion Score (MOS) values, to enable researchers to test their video quality evaluation algorithms.

Bandwidth scalability and efficient 2D and 3D video transmission over LTE networks

The recent Long-Term Evolution (LTE) standard, thanks to the provision of high data rates, will enable future immersive and interactive multimedia applications over wireless. In this paper, we study the performance of 2D and 3D video transmission over LTE networks. The LTE standard bandwidth ranges are considered in order to explore the impact of the LTE bandwidth scalability on the transmission of 2D and 3D video traffic to the end users. This dependency is investigated through the packet loss ratio (PLR) and average throughput as user-oriented metrics, and the cell spectral efficiency as a system-oriented metric. Furthermore, a PLR-based Admission Control (AC) strategy is introduced in the system for which the achieved trade-off between the system resource utilization and the quality level provided to the different users is investigated. The simulation results provide guidelines for combining bandwidth scalability and admission control strategies in LTE networks in order to achieve high system resource utilization and video quality for the LTE users.

A methodology to evaluate the effect of video compression on the performance of analytics systems

The Image Library for Intelligent Detection Systems (i-LIDS) provides benchmark surveillance datasets for analytics systems. This paper proposes a methodology to investigate the effect of compression and frame-rate reduction, and to recommend an appropriate suite of degraded datasets for public release. The library consists of six scenarios, including Sterile Zone (SZ) and Parked Vehicle (PV), which are investigated using two different compression algorithms (H.264 and JPEG) and a number of detection systems. PV has higher spatio-temporal complexity than the SZ. Compression performance is dependent on scene content hence PV will require larger bit-streams in comparison with SZ, for any given distortion rate. The study includes both industry standard algorithms (for transmission) and CCTV recorders (for storage). CCTV recorders generally use proprietary formats, which may significantly affect the visual information. Encoding standards such as H.264 and JPEG use the Discrete Cosine Transform (DCT) technique, which introduces blocking artefacts. The H.264 compression algorithm follows a hybrid predictive coding approach to achieve high compression gains, exploiting both spatial and temporal redundancy. The highly predictive approach of H.264 may introduce more artefacts resulting in a greater effect on the performance of analytics systems than JPEG. The paper describes the two main components of the proposed methodology to measure the effect of degradation on analytics performance. Firstly, the standard tests, using the ‘f-measure’ to evaluate the performance on a range of degraded video sets. Secondly, the characterisation of the datasets, using quantification of scene features, defined using image processing techniques. This characterization permits an analysis of the points of failure introduced by the video degradation.

Content-aware packet scheduling strategy for medical ultrasound videos over LTE wireless networks

Abstract In parallel to the advancements in communication technologies, telemedicine research has continually adapted to develop various healthcare applications. The latest wireless technology Long-Term Evolution(LTE) is being increasingly deployed across developed countries and rapidly adopted by developing countries. In this paper, a content-aware packet scheduling approach for medical ultrasound videos is proposed. The contribution of this work is introducing a utility function based on the temporal complexity of the video frames. The utility function is used with four schedulers to prioritise the video packets based on their temporal complexity and type of frame (e.g. I frame). The results show that the utility function improves the packet delay performance obtained in our simulation when compared with content-unaware approach. Further, gain in average PSNR and SSIM are also observed in the received video quality. Research on content-aware packet scheduling for telemedicine applications over advanced wireless networks is limited and our work contributes towards addressing this research gap.

Network and user centric performance analysis of scheduling strategies for video streaming over LTE

Diverse scheduling strategies have been designed for video streaming traffic ranging from Quality of Service (QoS) aware scheduling rules to more complex video quality based scheduling strategies. In this work, we analyze and compare some of the well known scheduling rules for video streaming traffic. Our main goal is to compare and analyze different classes of scheduling strategies (QoS and video quality aware rules) in terms of network centric performance metrics as well as user centric metrics. QoS evaluation involves the evaluation of network performance parameters, e.g., packet loss rate, average system throughput and end-to-end packet delay. On the other hand, video quality evaluation involves the computation of objective and subjective video quality metrics. According to simulation results, the proxy based video quality aware scheduling strategy performs best in terms of number of satisfied users and should be used in an Long-Term Evolution (LTE) downlink to offer high quality video streaming services.

A hybrid quality evaluation approach based on fuzzy inference system for medical video streaming over small cell technology

Small cell technology is expected to be an integral part of future 5G networks in order to meet the increasingly high user demands for traffic volume, frequency efficiency, and energy and cost reductions. Small cell networks can play an important role in enhancing the Quality of Service (QoS) and Quality of Experience (QoE) in m-health applications, and in particular, in medical video streaming. In this paper, we propose a hybrid medical QoE prediction model based on a Fuzzy Inference System (FIS) that correlates the network QoS (NQoS) and application QoS (AQoS) parameters to the QoE. The model is tested on the transmission of medical ultrasound video over small cell technology. The results show that the predicted QoE scores of our proposed model have a high correlation with the subjective scores of medical experts.

3D Robotic Surgery and Training at a Distance

The usage of 3D images and video in medical surgery and training applications contributes in the provision of more natural viewing conditions and improved diagnosis and operation. This is enabled by the recent advances in 3D video capturing and display technologies, as well as advances in robotics and network technologies. The latest advances in robotic surgery enable the performance of many surgical procedures; in particular, recent 3D endoscopes have improved the performance of minimally invasive surgical procedures. Based on these advances, performing or visualizing in real-time surgical procedures at a distance can be envisaged. In this chapter, we present a review of 3D robotic surgery and tele-surgery applications and a performance evaluation of 3D robotic tele-surgery and training over wireless networks based on the long-term evolution (LTE) 3GPP standard. Different scheduling strategies are compared and results are analyzed in term of the resulting quality of experience for the surgeon.

Content-aware downlink scheduling for LTE wireless systems: A survey and performance comparison of key approaches

Abstract We present in this paper a comprehensive review and comparison of recent downlink scheduling approaches for video streaming traffic over the Orthogonal Frequency Division Multiple Access (OFDMA) based Long-Term Evolution (LTE) wireless technology. Focusing on content-aware downlink scheduling approaches, we provide an extensive literature review, a taxonomy for content-aware and content-unaware downlink schedulers, and tables that summarize the key approaches and common parameters among the schedulers. In addition, we analyze and compare via simulation the performance of some of the most relevant scheduling rules. Our main goal is to compare and analyze different classes of scheduling strategies in terms of network centric performance metrics as well as user centric metrics. Quality of Service (QoS) evaluation involves the evaluation of network performance parameters, e.g., packet loss rate, average system throughput and end-to-end packet delay. On the other hand, Quality of Experience (QoE) reflects the user’s experience and satisfaction in terms of Mean Opinion Score (MOS). According to simulation results, proxy based QoE aware scheduling strategies perform best in terms of number of satisfied users and should be used in an LTE downlink to offer high quality video streaming services.