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Dr. Dr. Moustafa Nasralla
Prince Sultan University

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Research Keywords & Expertise

0 Multimedia Communications
0 IoT
0 Wireless Communication and Networks
0 5g
0 Wireless Sensors

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IoT
5g
Multimedia Communications

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Short Biography

Dr. Moustafa M. Nasralla is currently an Assistant Professor in the Communications and Networks Engineering Department at Prince Sultan University, Riyadh, Saudi Arabia. He received his Ph.D. and M.Sc. from the Faculty of Science, Engineering and Computing, Kingston University, London, UK. He received his B.Sc. degree in Electrical Engineering from Hashemite University, Jordan. He is a member of the Smart Systems Engineering Research Lab. His research interests include wireless networks, IoT, and multimedia commu­nications.

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Research article
Published: 30 May 2021 in Security and Communication Networks
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In ad hoc networks, the communication is usually made through multiple hops by establishing an environment of cooperation and coordination among self-operated nodes. Such nodes typically operate with a set of finite and scarce energy, processing, bandwidth, and storage resources. Due to the cooperative environment in such networks, nodes may consume additional resources by giving relaying services to other nodes. This aspect in such networks coined the situation of noncooperative behavior by some or all the nodes. Moreover, nodes sometimes do not cooperate with others due to their social likeness or their mobility. Noncooperative or selfish nodes can last for a longer time by preserving their resources for their own operations. However, such nodes can degrade the network's overall performance in terms of lower data gathering and information exchange rates, unbalanced work distribution, and higher end-to-end delays. This work surveys the main roots for motivating nodes to adapt selfish behavior and the solutions for handling such nodes. Different schemes are introduced to handle selfish nodes in wireless ad hoc networks. Various types of routing techniques have been introduced to target different types of ad hoc networks having support for keeping misbehaving or selfish nodes. The major solutions for such scenarios can be trust-, punishment-, and stimulation-based mechanisms. Some key protocols are simulated and analyzed for getting their performance metrics to compare their effectiveness.

ACS Style

Muhammad Altaf Khan; Moustafa M. Nasralla; Muhammad Muneer Umar; Zeeshan Iqbal; Ghani Ur Rehman; Muhammad Shahzad Sarfraz; Nikumani Choudhury. A Survey on the Noncooperative Environment in Smart Nodes-Based Ad Hoc Networks: Motivations and Solutions. Security and Communication Networks 2021, 2021, 1 -17.

AMA Style

Muhammad Altaf Khan, Moustafa M. Nasralla, Muhammad Muneer Umar, Zeeshan Iqbal, Ghani Ur Rehman, Muhammad Shahzad Sarfraz, Nikumani Choudhury. A Survey on the Noncooperative Environment in Smart Nodes-Based Ad Hoc Networks: Motivations and Solutions. Security and Communication Networks. 2021; 2021 ():1-17.

Chicago/Turabian Style

Muhammad Altaf Khan; Moustafa M. Nasralla; Muhammad Muneer Umar; Zeeshan Iqbal; Ghani Ur Rehman; Muhammad Shahzad Sarfraz; Nikumani Choudhury. 2021. "A Survey on the Noncooperative Environment in Smart Nodes-Based Ad Hoc Networks: Motivations and Solutions." Security and Communication Networks 2021, no. : 1-17.

Journal article
Published: 23 April 2021 in Sustainability
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To develop sustainable rehabilitation systems, these should consider common problems on IoT devices such as low battery, connection issues and hardware damages. These should be able to rapidly detect any kind of problem incorporating the capacity of warning users about failures without interrupting rehabilitation services. A novel methodology is presented to guide the design and development of sustainable rehabilitation systems focusing on communication and networking among IoT devices in rehabilitation systems with virtual smart cities by using time series analysis for identifying malfunctioning IoT devices. This work is illustrated in a realistic rehabilitation simulation scenario in a virtual smart city using machine learning on time series for identifying and anticipating failures for supporting sustainability.

ACS Style

Moustafa Nasralla. Sustainable Virtual Reality Patient Rehabilitation Systems with IoT Sensors Using Virtual Smart Cities. Sustainability 2021, 13, 4716 .

AMA Style

Moustafa Nasralla. Sustainable Virtual Reality Patient Rehabilitation Systems with IoT Sensors Using Virtual Smart Cities. Sustainability. 2021; 13 (9):4716.

Chicago/Turabian Style

Moustafa Nasralla. 2021. "Sustainable Virtual Reality Patient Rehabilitation Systems with IoT Sensors Using Virtual Smart Cities." Sustainability 13, no. 9: 4716.

Journal article
Published: 19 March 2021 in Electronics
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The literature on engineering education research highlights the relevance of evaluating course learning outcomes (CLOs). However, generic and reliable mechanisms for evaluating CLOs remain challenges. The purpose of this project was to accurately assess the efficacy of the learning and teaching techniques through analysing the CLOs’ performance by using an advanced analytical model (i.e., the Rasch model) in the context of engineering and business education. This model produced an association pattern between the students and the overall achieved CLO performance. The sample in this project comprised students who are enrolled in some nominated engineering and business courses over one academic year at Prince Sultan University, Saudi Arabia. This sample considered several types of assessment, such as direct assessments (e.g., quizzes, assignments, projects, and examination) and indirect assessments (e.g., surveys). The current research illustrates that the Rasch model for measurement can categorise grades according to course expectations and standards in a more accurate manner, thus differentiating students by their extent of educational knowledge. The results from this project will guide the educator to track and monitor the CLOs’ performance, which is identified in every course to estimate the students’ knowledge, skills, and competence levels, which will be collected from the predefined sample by the end of each semester. The Rasch measurement model’s proposed approach can adequately assess the learning outcomes.

ACS Style

Moustafa Nasralla; Basiem Al-Shattarat; Dhafer Almakhles; Abdelhakim Abdelhadi; Eman Abowardah. Futuristic Trends and Innovations for Examining the Performance of Course Learning Outcomes Using the Rasch Analytical Model. Electronics 2021, 10, 727 .

AMA Style

Moustafa Nasralla, Basiem Al-Shattarat, Dhafer Almakhles, Abdelhakim Abdelhadi, Eman Abowardah. Futuristic Trends and Innovations for Examining the Performance of Course Learning Outcomes Using the Rasch Analytical Model. Electronics. 2021; 10 (6):727.

Chicago/Turabian Style

Moustafa Nasralla; Basiem Al-Shattarat; Dhafer Almakhles; Abdelhakim Abdelhadi; Eman Abowardah. 2021. "Futuristic Trends and Innovations for Examining the Performance of Course Learning Outcomes Using the Rasch Analytical Model." Electronics 10, no. 6: 727.

Research article
Published: 17 March 2021 in Wireless Communications and Mobile Computing
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The last decade has witnessed a steep growth in multimedia traffic due to real-time content delivery such as in online games and video conferencing. In some contexts, MANETs play a key role in the hyperconnectivity of everything in multimedia services. In this context, this work proposes a new scheduling approach based on context-aware mobile nodes for their connectivity. The contribution relies on reporting not only the locations of devices in the network but also their movement identified by sensors. In order to illustrate this approach, we have developed a novel agent-based simulator called MASEMUL for illustrating the proposed approach. The results show that a movement-aware scheduling strategy defined with the proposed approach has decreased the ratio of channel interruptions over another common strategy in mobile networks.

ACS Style

Moustafa M. Nasralla; Iván García-Magariño; Jaime Lloret. MASEMUL: A Simulation Tool for Movement-Aware MANET Scheduling Strategies for Multimedia Communications. Wireless Communications and Mobile Computing 2021, 2021, 1 -12.

AMA Style

Moustafa M. Nasralla, Iván García-Magariño, Jaime Lloret. MASEMUL: A Simulation Tool for Movement-Aware MANET Scheduling Strategies for Multimedia Communications. Wireless Communications and Mobile Computing. 2021; 2021 ():1-12.

Chicago/Turabian Style

Moustafa M. Nasralla; Iván García-Magariño; Jaime Lloret. 2021. "MASEMUL: A Simulation Tool for Movement-Aware MANET Scheduling Strategies for Multimedia Communications." Wireless Communications and Mobile Computing 2021, no. : 1-12.

Journal article
Published: 15 July 2020 in Sensors
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Multi-Agent Systems can support e-Healthcare applications for improving quality of life of citizens. In this direction, we propose a healthcare system architecture named smart healthcare city. First, we divide a given city into various zones and then we propose a zonal level three-layered system architecture. Further, for effectiveness we introduce a Multi-Agent System (MAS) in this three-layered architecture. Protecting sensitive health information of citizens is a major security concern. Group key agreement (GKA) is the corner stone for securely sharing the healthcare data among the healthcare stakeholders of the city. For establishing GKA, many efficient cryptosystems are available in the classical field. However, they are yet dependent on the supposition that some computational problems are infeasible. In light of quantum mechanics, a new field emerges to share a secret key among two or more members. The unbreakable and highly secure features of key agreement based on fundamental laws of physics allow us to propose a Quantum GKA (QGKA) technique based on renowned Quantum Diffie–Hellman (QDH). In this, a node acts as a Group Controller (GC) and forms 2-party groups with remaining nodes, establishing a QDH-style shared key per each two-party. It then joins these keys into a single group key by means of a XOR-operation, acting as a usual group node. Furthermore, we extend the QGKA to Dynamic QGKA (DQGKA) by adding join and leave protocol. Our protocol performance was compared with existing QGKA protocols in terms of Qubit efficiency (QE), unitary operation (UO), unitary operation efficiency (UOE), key consistency check (KCC), security against participants attack (SAP) and satisfactory results were obtained. The security analysis of the proposed technique is based on unconditional security of QDH. Moreover, it is secured against internal and external attack. In this way, e-healthcare Multi-Agent System can be robust against future quantum-based attacks.

ACS Style

Vankamamidi S. Naresh; Moustafa M. Nasralla; Sivaranjani Reddi; Iván García-Magariño. Quantum Diffie–Hellman Extended to Dynamic Quantum Group Key Agreement for e-Healthcare Multi-Agent Systems in Smart Cities. Sensors 2020, 20, 3940 .

AMA Style

Vankamamidi S. Naresh, Moustafa M. Nasralla, Sivaranjani Reddi, Iván García-Magariño. Quantum Diffie–Hellman Extended to Dynamic Quantum Group Key Agreement for e-Healthcare Multi-Agent Systems in Smart Cities. Sensors. 2020; 20 (14):3940.

Chicago/Turabian Style

Vankamamidi S. Naresh; Moustafa M. Nasralla; Sivaranjani Reddi; Iván García-Magariño. 2020. "Quantum Diffie–Hellman Extended to Dynamic Quantum Group Key Agreement for e-Healthcare Multi-Agent Systems in Smart Cities." Sensors 20, no. 14: 3940.

Journal article
Published: 06 July 2020 in Electronics
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Real-time data management analytics involve capturing data in real-time and, at the same time, processing data in a light way to provide an effective real-time support. Real-time data management analytics are key for supporting decisions of business intelligence. The proposed approach covers all these phases by (a) monitoring online information from websites with Selenium-based software and incrementally conforming a database, and (b) incrementally updating summarized information to support real-time decisions. We have illustrated this approach for the investor–company field with the particular fields of Bitcoin cryptocurrency and Internet-of-Things (IoT) smart-meter sensors in smart cities. The results of 40 simulations on historic data showed that one of the proposed investor strategies achieved 7.96% of profits on average in less than two weeks. However, these simulations and other simulations of up to 69 days showed that the benefits were highly variable in these two sets of simulations (respective standard deviations were 24.6% and 19.2%).

ACS Style

Iván García-Magariño; Moustafa M. Nasralla; Shah Nazir. Real-Time Analysis of Online Sources for Supporting Business Intelligence Illustrated with Bitcoin Investments and IoT Smart-Meter Sensors in Smart Cities. Electronics 2020, 9, 1101 .

AMA Style

Iván García-Magariño, Moustafa M. Nasralla, Shah Nazir. Real-Time Analysis of Online Sources for Supporting Business Intelligence Illustrated with Bitcoin Investments and IoT Smart-Meter Sensors in Smart Cities. Electronics. 2020; 9 (7):1101.

Chicago/Turabian Style

Iván García-Magariño; Moustafa M. Nasralla; Shah Nazir. 2020. "Real-Time Analysis of Online Sources for Supporting Business Intelligence Illustrated with Bitcoin Investments and IoT Smart-Meter Sensors in Smart Cities." Electronics 9, no. 7: 1101.

Journal article
Published: 30 June 2020 in Electronics
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The recent advancements of wireless technology and applications make downlink scheduling and resource allocations an important research topic. In this paper, we consider the problem of downlink scheduling for multi-user scalable video streaming over OFDMA channels. The video streams are precoded using a scalable video coding (SVC) scheme. We propose a fuzzy logic-based scheduling algorithm, which prioritises the transmission to different users by considering video content, and channel conditions. Furthermore, a novel analytical model and a new performance metric have been developed for the performance analysis of the proposed scheduling algorithm. The obtained results show that the proposed algorithm outperforms the content-blind/channel aware scheduling algorithms with a gain of as much as 19% in terms of the number of supported users. The proposed algorithm allows for a fairer allocation of resources among users across the entire sector coverage, allowing for the enhancement of video quality at edges of the cell while minimising the degradation of users closer to the base station.

ACS Style

Peter E. Omiyi; Moustafa M. Nasralla; Ikram Ur Rehman; Nabeel Khan; Maria G. Martini. An Intelligent Fuzzy Logic-Based Content and Channel Aware Downlink Scheduler for Scalable Video over OFDMA Wireless Systems. Electronics 2020, 9, 1071 .

AMA Style

Peter E. Omiyi, Moustafa M. Nasralla, Ikram Ur Rehman, Nabeel Khan, Maria G. Martini. An Intelligent Fuzzy Logic-Based Content and Channel Aware Downlink Scheduler for Scalable Video over OFDMA Wireless Systems. Electronics. 2020; 9 (7):1071.

Chicago/Turabian Style

Peter E. Omiyi; Moustafa M. Nasralla; Ikram Ur Rehman; Nabeel Khan; Maria G. Martini. 2020. "An Intelligent Fuzzy Logic-Based Content and Channel Aware Downlink Scheduler for Scalable Video over OFDMA Wireless Systems." Electronics 9, no. 7: 1071.

Journal article
Published: 27 April 2020 in IEEE Access
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The developments in wireless technology and applications in recent years have increased the interest in downlink scheduling and resource allocations among researchers. Moreover, fair scheduling and balanced Quality of Service (QoS) delivery for various forms of traffic are needed for Long-Term Evolution (LTE) wireless systems. This paper proposes hybrid QoS-aware downlink scheduling approaches that aim to address different traffic classes and balance the QoS delivery with improvements to the overall system performance under channel and bandwidth constraints. Moreover, this research introduces a taxonomy that classifies the scheduling algorithms into four main classes: delay aware, queue aware, target bit-rate aware and hybrid aware. The latter class is the scheduling class that is proposed in this paper; it considers channel, queue and delay parameters in its scheduling metric. Using simulations, we compare and analyze different downlink scheduling rules for their network-centric performance metrics, e.g., average packet loss ratio, average throughput, average packet delay, system fairness, and system spectral efficiency. The simulation results show that the queue-aware and delay-aware scheduling rules deliver the best QoS performance for video traffic classes, whereas our proposed hybrid scheduling rules deliver balanced QoS for various types of traffic classes. Employing QoS balancing scheduling rules in an LTE downlink is suggested to provide high QoS delivery for different traffic classes.

ACS Style

Moustafa M. Nasralla. A Hybrid Downlink Scheduling Approach for Multi-Traffic Classes in LTE Wireless Systems. IEEE Access 2020, 8, 82173 -82186.

AMA Style

Moustafa M. Nasralla. A Hybrid Downlink Scheduling Approach for Multi-Traffic Classes in LTE Wireless Systems. IEEE Access. 2020; 8 (99):82173-82186.

Chicago/Turabian Style

Moustafa M. Nasralla. 2020. "A Hybrid Downlink Scheduling Approach for Multi-Traffic Classes in LTE Wireless Systems." IEEE Access 8, no. 99: 82173-82186.

Conference paper
Published: 03 January 2020 in Advances in Intelligent Systems and Computing
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Universities and colleges in the UK welcome about 30,000 students with special needs each year. Research shows that the dropout rate for disabled students is much higher at 31.5% when compared with about 12.3% for non-disabled students in the EU. Supporting young students with special educational needs while pursuing higher education is an ambitious and important role, which needs to be adopted by tertiary education providers worldwide. We propose, MALSEND, a conceptual platform based on human-machine intelligence (HMI), a collective intelligence of human and machine to understand patterns of learning of disabled students in higher education. This platform aims to accommodate and analyse data sets features of universities activities to discover trends in performances with regards to subject areas for autistic students, dyslexic students and students having attention deficit hyperactive disorder (ADHD), among others. Analysis of variables, such as students’ performances in modules, courses and other engagement-indices will give new insights into research questions, career advice and institutional policymaking. This paper describes the developmental activities of the MALSEND concept in phases.

ACS Style

Drishty Sobnath; Sakirulai Olufemi Isiaq; Ikram Ur Rehman; Moustafa Nasralla. Using Machine Learning Advances to Unravel Patterns in Subject Areas and Performances of University Students with Special Educational Needs and Disabilities (MALSEND): A Conceptual Approach. Advances in Intelligent Systems and Computing 2020, 509 -517.

AMA Style

Drishty Sobnath, Sakirulai Olufemi Isiaq, Ikram Ur Rehman, Moustafa Nasralla. Using Machine Learning Advances to Unravel Patterns in Subject Areas and Performances of University Students with Special Educational Needs and Disabilities (MALSEND): A Conceptual Approach. Advances in Intelligent Systems and Computing. 2020; ():509-517.

Chicago/Turabian Style

Drishty Sobnath; Sakirulai Olufemi Isiaq; Ikram Ur Rehman; Moustafa Nasralla. 2020. "Using Machine Learning Advances to Unravel Patterns in Subject Areas and Performances of University Students with Special Educational Needs and Disabilities (MALSEND): A Conceptual Approach." Advances in Intelligent Systems and Computing , no. : 509-517.

Conference paper
Published: 01 September 2019 in 2019 IEEE 24th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD)
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In wireless systems, content-aware MAC layer scheduling strategies contribute to supporting an adequate Quality of Service (QoS) and Quality of Experience (QoE) for the users. Content related information that can be used in such strategies include information about the video frame type (Intra-Predicted, Inter-Predicted or Backward-Predicted). Frame type identification and prediction in the MAC layer scheduler (as well as in other network locations) is hence a critical part of content-aware resource management and traffic engineering in video streaming. It is important to note that, when encryption is adopted at the upper layers, packet inspection is not possible. To address this issue, we propose an adaptive clustering and prediction algorithm. The algorithm uses unsupervised clustering combined with an adaptive classification approach to automatically group packets into frame clusters. Unlike conventional video traffic classifiers, our approach requires neither a-priori knowledge of video frames pattern nor a training set of frames. Instead, this approach automatically classifies packets into different frame types by employing simple statistical features. The proposed method continuously learns from the upcoming traffic thus the proper frame class labels can be easily discovered. Furthermore, the proposed method uses an autoregressive integrated moving average (ARIMA) algorithm to predict the upcoming traffic frame type. A large number of experiments has been carried out using data from several video samples. Results show the robustness and the effectiveness of our classification method, which is capable of achieving a detection rate of up to 97.3% for I frames and overall 2 identification accuracy of 91.3% (for all I, P and B frames).

ACS Style

Hadi Saki; Nabeel Khan; Maria G Martini; Moustafa Nasralla. Machine Learning Based Frame Classification for Videos Transmitted over Mobile Networks. 2019 IEEE 24th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD) 2019, 1 -6.

AMA Style

Hadi Saki, Nabeel Khan, Maria G Martini, Moustafa Nasralla. Machine Learning Based Frame Classification for Videos Transmitted over Mobile Networks. 2019 IEEE 24th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD). 2019; ():1-6.

Chicago/Turabian Style

Hadi Saki; Nabeel Khan; Maria G Martini; Moustafa Nasralla. 2019. "Machine Learning Based Frame Classification for Videos Transmitted over Mobile Networks." 2019 IEEE 24th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD) , no. : 1-6.

Conference paper
Published: 23 August 2019 in Communications in Computer and Information Science
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Technological research and innovation have advanced at a rapid pace in recent years, and one group hoping to benefit from this, is visually impaired people (VIP). Technology may enable them to find new ways of travelling around smart cities, thus improving their quality of life (QoL). Currently, there are approximately 110 million VIP worldwide, and continuous research is crucial to find innovative solutions to their mobility problems. Recent advances such as the increase in Unmanned Aerial Vehicles (UAVs), smartphones and wearable devices, together with an ever-growing uptake of deep learning, computer vision, the Internet of Things (IoT), and virtual and augmented reality (VR)/(AR), have provided VIP with the hope of having an improved QoL. In particular, indoor and outdoor spaces could be improved with the use of such technologies to make them suitable for VIP. This paper examines use cases both indoors and outdoors and provides recommendations of how deep learning and computer vision-enabled UAVs could be employed in smart cities to improve the QoL for VIP in the coming years.

ACS Style

Moustafa M. Nasralla; Ikram Ur Rehman; Drishty Sobnath; Sara Paiva. Computer Vision and Deep Learning-Enabled UAVs: Proposed Use Cases for Visually Impaired People in a Smart City. Communications in Computer and Information Science 2019, 91 -99.

AMA Style

Moustafa M. Nasralla, Ikram Ur Rehman, Drishty Sobnath, Sara Paiva. Computer Vision and Deep Learning-Enabled UAVs: Proposed Use Cases for Visually Impaired People in a Smart City. Communications in Computer and Information Science. 2019; ():91-99.

Chicago/Turabian Style

Moustafa M. Nasralla; Ikram Ur Rehman; Drishty Sobnath; Sara Paiva. 2019. "Computer Vision and Deep Learning-Enabled UAVs: Proposed Use Cases for Visually Impaired People in a Smart City." Communications in Computer and Information Science , no. : 91-99.

Journal article
Published: 07 February 2019 in Electronics
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This paper presents a QoS-aware, content-aware and device-aware nonintrusive medical QoE (m-QoE) prediction model over small cell networks. The proposed prediction model utilises a Multilayer Perceptron (MLP) neural network to predict m-QoE. It also acts as a platform to maintain and optimise the acceptable diagnostic quality through a device-aware adaptive video streaming mechanism. The proposed model is trained for an unseen dataset of input variables such as QoS, content features and display device characteristics, to produce an output value in the form of m-QoE (i.e. MOS). The efficiency of the proposed model is validated through subjective tests carried by medical experts. The prediction accuracy obtained via the correlation coefficient and Root Mean-Square-Error (RMSE) indicates that the proposed model succeeds in measuring m-QoE closer to the visual perception of the medical experts. Furthermore, we have addressed two main research questions: (1) How significant is ultrasound video content type in determining m-QoE? (2) How much of a role does the screen size and device resolution play in medical experts’ diagnostic experience? The former is answered through the content classification of ultrasound video sequences based on their spatiotemporal features, by including these features in the proposed prediction model, and validating their significance through medical experts’ subjective ratings. The latter is answered by conducting a novel subjective experiment of the ultrasound video sequences across multiple devices.

ACS Style

Ikram Ur Rehman; Moustafa M. Nasralla; Nada Y. Philip. Multilayer Perceptron Neural Network-Based QoS-Aware, Content-Aware and Device-Aware QoE Prediction Model: A Proposed Prediction Model for Medical Ultrasound Streaming Over Small Cell Networks. Electronics 2019, 8, 194 .

AMA Style

Ikram Ur Rehman, Moustafa M. Nasralla, Nada Y. Philip. Multilayer Perceptron Neural Network-Based QoS-Aware, Content-Aware and Device-Aware QoE Prediction Model: A Proposed Prediction Model for Medical Ultrasound Streaming Over Small Cell Networks. Electronics. 2019; 8 (2):194.

Chicago/Turabian Style

Ikram Ur Rehman; Moustafa M. Nasralla; Nada Y. Philip. 2019. "Multilayer Perceptron Neural Network-Based QoS-Aware, Content-Aware and Device-Aware QoE Prediction Model: A Proposed Prediction Model for Medical Ultrasound Streaming Over Small Cell Networks." Electronics 8, no. 2: 194.

Conference paper
Published: 01 November 2018 in 2018 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies (3ICT)
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There is a significant increase in mobile internet usage resulting in demand for traffic volume, frequency efficiency and energy and cost reduction, for which small cell networks are expected to play a key role. Due to high bandwidth requirement, mobile health applications (m-health) and medical video streaming in particular will benefit from small cell networks in terms of Quality of Service (QoS) and Quality of Experience (QoE) enhancements. This paper presents content-aware and device-aware medical Quality of Experience evaluations in terms of subjective (e.g. MOS) and objective (e.g. PSNR and SSIM) quality metrics obtained over small cell networks. Furthermore, we address the following two main research questions: (1) How significant is ultrasound video content type in determining medical QoE? (2) How much of a role does the display device play in medical experts’ diagnostic experience? The former is answered through the content classification of ultrasound video sequences based on their spatio-temporal features and validating their significance through medical experts’ subjective ratings. The latter is answered by conducting a subjective experiment of the ultrasound video sequences across multiple devices, ranging in screen size and resolution.

ACS Style

Ikram Ur Rehman; Moustafa Nasralla; Ajaz Ali; Ikechukwu Maduka; Nada Y. Philip. The Influence of Content and Device Awareness on QoE for Medical Video Streaming over Small Cells : subjective and objective quality evaluations. 2018 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies (3ICT) 2018, 1 -7.

AMA Style

Ikram Ur Rehman, Moustafa Nasralla, Ajaz Ali, Ikechukwu Maduka, Nada Y. Philip. The Influence of Content and Device Awareness on QoE for Medical Video Streaming over Small Cells : subjective and objective quality evaluations. 2018 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies (3ICT). 2018; ():1-7.

Chicago/Turabian Style

Ikram Ur Rehman; Moustafa Nasralla; Ajaz Ali; Ikechukwu Maduka; Nada Y. Philip. 2018. "The Influence of Content and Device Awareness on QoE for Medical Video Streaming over Small Cells : subjective and objective quality evaluations." 2018 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies (3ICT) , no. : 1-7.

Conference paper
Published: 01 November 2018 in 2018 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies (3ICT)
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The recent advancements in wireless technologies and applications make downlink scheduling and resource allocation a hot topic of research. Hence, fair scheduling and balanced Quality of Service (QoS) delivery for different types of traffic (e.g., VoIP, video, and best-effort) are vital for next-generation wireless networks. In this paper, we analyze various downlink scheduling algorithms in terms of network-oriented performance parameters such as average throughput, system fairness, average packet loss ratio, and system spectral efficiency. In addition, we show the effect of the QoS Class Identifier (QCI) parameters on different delay-aware scheduling algorithms. Furthermore, we propose a group of algorithms to improve the existing Log-rule, Linear-rule, and Modified Largest Weighted Delay First (M-LWDF) scheduling strategies. This is achieved by including in the algorithms the QCI parameters in order to balance the QoS delivery for different traffic-classes with improvement to the overall system performance. Through simulation, we show that the proposed scheduling algorithms utilising the QCI and QoS parameters introduce improved QoS performance for different traffic classes (i.e., real-time (RT) and non-real-time (NRT)).

ACS Style

Moustafa Nasralla; Ikram Ur Rehman. QCI and QoS Aware Downlink Packet Scheduling Algorithms for Multi-Traffic Classes over 4G and beyond Wireless Networks. 2018 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies (3ICT) 2018, 1 -7.

AMA Style

Moustafa Nasralla, Ikram Ur Rehman. QCI and QoS Aware Downlink Packet Scheduling Algorithms for Multi-Traffic Classes over 4G and beyond Wireless Networks. 2018 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies (3ICT). 2018; ():1-7.

Chicago/Turabian Style

Moustafa Nasralla; Ikram Ur Rehman. 2018. "QCI and QoS Aware Downlink Packet Scheduling Algorithms for Multi-Traffic Classes over 4G and beyond Wireless Networks." 2018 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies (3ICT) , no. : 1-7.

Review article
Published: 06 September 2018 in Computer Communications
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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.

ACS Style

Moustafa M. Nasralla; Nabeel Khan; Maria G Martini. Content-aware downlink scheduling for LTE wireless systems: A survey and performance comparison of key approaches. Computer Communications 2018, 130, 78 -100.

AMA Style

Moustafa M. Nasralla, Nabeel Khan, Maria G Martini. Content-aware downlink scheduling for LTE wireless systems: A survey and performance comparison of key approaches. Computer Communications. 2018; 130 ():78-100.

Chicago/Turabian Style

Moustafa M. Nasralla; Nabeel Khan; Maria G Martini. 2018. "Content-aware downlink scheduling for LTE wireless systems: A survey and performance comparison of key approaches." Computer Communications 130, no. : 78-100.

Conference paper
Published: 01 July 2018 in 2018 8th International Conference on Computer Science and Information Technology (CSIT)
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High-Efficiency Video Coding (HEVC) is the latest video compression standard developed by the Joint Collaborative Team on Video Coding (JCT-VC). This standard is developed with an aim to reduce the video bitrate requirements by 50% with no degradation in the video quality. In the field of telemedicine, the HEVC standard can help in lowering the bitrate requirements for coding medical videos and thus enhance their compression efficiency and transmission performance over communication channels. In this paper, a comparative performance evaluation of the HEVC standard with its predecessor the H.264/AVC has been carried out in the context of medical videos. The evaluation results are achieved using three different configuration modes currently provided by the JCT-VC team, namely the random access, low delay and intra configurations. In order to perform a fair comparative evaluation, the H.264/AVC standard is also configured to match as close as possible to the configuration modes of the HEVC standard. The encoded videos of both HEVC and H.264 standards are transmitted over simulated 4G networks in order to study its influence on system resource utilisation and transmission efficiency. The test results show that the HEVC standard gives higher compression efficiency over the H.264/AVC standard, resulting in a reduction in bitrate requirements, which further helps in achieving better quality transmission over LTE/LTE-A networks.

ACS Style

Moustafa Nasralla; Manzoor Razaak; Ikram Ur Rehman; Maria G. Martini. A Comparative Performance Evaluation of the HEVC Standard with its Predecessor H.264/AVC for Medical videos over 4G and beyond Wireless Networks. 2018 8th International Conference on Computer Science and Information Technology (CSIT) 2018, 50 -54.

AMA Style

Moustafa Nasralla, Manzoor Razaak, Ikram Ur Rehman, Maria G. Martini. A Comparative Performance Evaluation of the HEVC Standard with its Predecessor H.264/AVC for Medical videos over 4G and beyond Wireless Networks. 2018 8th International Conference on Computer Science and Information Technology (CSIT). 2018; ():50-54.

Chicago/Turabian Style

Moustafa Nasralla; Manzoor Razaak; Ikram Ur Rehman; Maria G. Martini. 2018. "A Comparative Performance Evaluation of the HEVC Standard with its Predecessor H.264/AVC for Medical videos over 4G and beyond Wireless Networks." 2018 8th International Conference on Computer Science and Information Technology (CSIT) , no. : 50-54.

Journal article
Published: 01 July 2018 in Computer Networks
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ACS Style

Moustafa M. Nasralla; Manzoor Razaak; Ikram Ur Rehman; Maria G. Martini. Content-aware packet scheduling strategy for medical ultrasound videos over LTE wireless networks. Computer Networks 2018, 140, 126 -137.

AMA Style

Moustafa M. Nasralla, Manzoor Razaak, Ikram Ur Rehman, Maria G. Martini. Content-aware packet scheduling strategy for medical ultrasound videos over LTE wireless networks. Computer Networks. 2018; 140 ():126-137.

Chicago/Turabian Style

Moustafa M. Nasralla; Manzoor Razaak; Ikram Ur Rehman; Maria G. Martini. 2018. "Content-aware packet scheduling strategy for medical ultrasound videos over LTE wireless networks." Computer Networks 140, no. : 126-137.

Conference paper
Published: 21 November 2016 in 2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom)
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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.

ACS Style

Ikram Ur Rehman; Nada Y. Philip; Moustafa Nasralla. A hybrid quality evaluation approach based on fuzzy inference system for medical video streaming over small cell technology. 2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom) 2016, 1 -6.

AMA Style

Ikram Ur Rehman, Nada Y. Philip, Moustafa Nasralla. A hybrid quality evaluation approach based on fuzzy inference system for medical video streaming over small cell technology. 2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom). 2016; ():1-6.

Chicago/Turabian Style

Ikram Ur Rehman; Nada Y. Philip; Moustafa Nasralla. 2016. "A hybrid quality evaluation approach based on fuzzy inference system for medical video streaming over small cell technology." 2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom) , no. : 1-6.

Conference paper
Published: 01 June 2015 in 2015 IEEE International Conference on Communication Workshop (ICCW)
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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.

ACS Style

Nabeel Khan; Moustafa M. Nasralla; Maria G. Martini. Network and user centric performance analysis of scheduling strategies for video streaming over LTE. 2015 IEEE International Conference on Communication Workshop (ICCW) 2015, 1753 -1758.

AMA Style

Nabeel Khan, Moustafa M. Nasralla, Maria G. Martini. Network and user centric performance analysis of scheduling strategies for video streaming over LTE. 2015 IEEE International Conference on Communication Workshop (ICCW). 2015; ():1753-1758.

Chicago/Turabian Style

Nabeel Khan; Moustafa M. Nasralla; Maria G. Martini. 2015. "Network and user centric performance analysis of scheduling strategies for video streaming over LTE." 2015 IEEE International Conference on Communication Workshop (ICCW) , no. : 1753-1758.

Conference paper
Published: 01 June 2015 in 2015 IEEE International Conference on Communication Workshop (ICCW)
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This paper proposes an approach for the evaluation of DASH-based video transmission from a server located in a Content Delivery Network (CDN) to multiple LTE users. The approach is based on utilizing an analytical model for the HTTP/TCP transmission in the wired/core link, and simulation traces for the packet transmission in the wireless/access link. The core and access link are separately considered by using the Wireless Transmission Control Protocol (WTCP) at the eNodeB, and three scheduling approaches are used for delivering the video packets in the access link. Therefore, in our proposed approach, we emulate DASH-based end-to-end video delivery and observe how the scheduling strategy affects the video streaming quality depending on the number of users in the system.

ACS Style

Ognen Ognenoski; Moustafa M. Nasralla; Manzoor Razaak; Maria G Martini; Peter Amon. DASH-based video transmission over LTE networks. 2015 IEEE International Conference on Communication Workshop (ICCW) 2015, 1783 -1787.

AMA Style

Ognen Ognenoski, Moustafa M. Nasralla, Manzoor Razaak, Maria G Martini, Peter Amon. DASH-based video transmission over LTE networks. 2015 IEEE International Conference on Communication Workshop (ICCW). 2015; ():1783-1787.

Chicago/Turabian Style

Ognen Ognenoski; Moustafa M. Nasralla; Manzoor Razaak; Maria G Martini; Peter Amon. 2015. "DASH-based video transmission over LTE networks." 2015 IEEE International Conference on Communication Workshop (ICCW) , no. : 1783-1787.