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Prof. Rashid A. Saeed
Sudan University of Science and Technology,Electronics Engineering School

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Research Keywords & Expertise

0 Wireless Broadband
0 Wireless Communication and Networks
0 microwave (MW)/millimeter-wave (MMW)/Terahertz (THz) component designs
0 Radio Access Technology
0 cognitive radio network

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Wireless Broadband
Wireless Communication and Networks

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Journal article
Published: 28 June 2021 in IEEE Access
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An optimized design with real-time and multiple realistic constraints in complex engineering systems is a crucial challenge for designers. In the non-uniform Internet of Things (IoT) node deployments, the approximation accuracy is directly affected by the parameters like node density and coverage. We propose a novel enhanced differential crossover quantum particle swarm optimization algorithm for solving nonlinear numerical problems. The algorithm is based on hybrid optimization using quantum PSO. Differential evolution operator is used to circumvent group moves in small ranges and falling into the local optima and improves global searchability. The cross operator is employed to promote information interchange among individuals in a group, and exceptional genes can be continued moderately, accompanying the evolutionary process’s continuance and adding proactive and reactive features. The proposed algorithm’s performance is verified as well as compared with the other algorithms through 30 classic benchmark functions in IEEE CEC2017, with a basic PSO algorithm and improved versions. The results show the smaller values of fitness function and computational efficiency for the benchmark functions of IEEE CEC2019. The proposed algorithm outperforms the existing optimization algorithms and different PSO versions, and has a high precision and faster convergence speed. The average location error is substantially reduced for the smart parking IoT application.

ACS Style

Sheetal N. Ghorpade; Marco Zennaro; Bharat S. Chaudhari; Rashid A. Saeed; Hesham Alhumyani; S. Abdel-Khaled. Enhanced Differential Crossover and Quantum Particle Swarm Optimization for IoT Applications. IEEE Access 2021, 9, 1 -1.

AMA Style

Sheetal N. Ghorpade, Marco Zennaro, Bharat S. Chaudhari, Rashid A. Saeed, Hesham Alhumyani, S. Abdel-Khaled. Enhanced Differential Crossover and Quantum Particle Swarm Optimization for IoT Applications. IEEE Access. 2021; 9 ():1-1.

Chicago/Turabian Style

Sheetal N. Ghorpade; Marco Zennaro; Bharat S. Chaudhari; Rashid A. Saeed; Hesham Alhumyani; S. Abdel-Khaled. 2021. "Enhanced Differential Crossover and Quantum Particle Swarm Optimization for IoT Applications." IEEE Access 9, no. : 1-1.

Journal article
Published: 05 June 2021 in Alexandria Engineering Journal
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Single carrier multiple access division (SC-FDMA) technology is one of the good uplink modulation techniques in a wireless communication system. Promises high transmission speed, low bit error rate and high spectral efficiency with low peak to average power ratio (PAPR) compared to OFDMA. This paper is proposed analytical model and link level simulation using MATLAB® to enhance the ratio of peak average power (PAPR) performance for distributed SC-FDMA sub-carrier assignment of. The methodology using the first full-featured digital MIMO software allows for in-depth verification and improvement of MIMO technologies applied to satellite broadcasting networks. Moreover, the demonstrator allows to complete and confirm our theory and simulation-based. The aim of this paper is to enhancement PAPR by analyzing the mobile satellite digital that employed distributed sub-carrier assignment for MIMO-SC-FDMA. The model is verified and validated by link level simulation.

ACS Style

Amr M. Musa; Rania A. Mokhtar; Rashid A. Saeed; Hesham Alhumyani; S. Abdel-Khalek; Adil Omer Yousif Mohamed. Distributed SC-FDMA sub-carrier assignment for digital mobile satellite. Alexandria Engineering Journal 2021, 60, 4973 -4980.

AMA Style

Amr M. Musa, Rania A. Mokhtar, Rashid A. Saeed, Hesham Alhumyani, S. Abdel-Khalek, Adil Omer Yousif Mohamed. Distributed SC-FDMA sub-carrier assignment for digital mobile satellite. Alexandria Engineering Journal. 2021; 60 (6):4973-4980.

Chicago/Turabian Style

Amr M. Musa; Rania A. Mokhtar; Rashid A. Saeed; Hesham Alhumyani; S. Abdel-Khalek; Adil Omer Yousif Mohamed. 2021. "Distributed SC-FDMA sub-carrier assignment for digital mobile satellite." Alexandria Engineering Journal 60, no. 6: 4973-4980.

Preprint content
Published: 15 March 2021
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Cognitive radio (CR) is one of the most promising technology soon due to the scarcity of the spectrum, especially at microwave band. CR faces massive resistance from the industry because of the potential interference caused by the secondary users. Spectrum sensing forms an important functionality for CR systems. However, such detection performance is usually compromised by shadowing and fading channel conditions. Cooperative sensing is one of the crucial solutions to overcome degraded detection performance. To improve the sensing performance and reduce the reporting error, a distributed architecture for processing and fusion of sensing information is proposed in this work. In dense network scenarios, the decision fusion for cooperated users could be complex and reported sensing traffic may require large bandwidth. This paper proposes a new distributed detection and adapted threshold based on controlled false alarm probability to improve sensing reliability and efficiency in a highly Rayleigh faded environment. A distributed detection is developed by selecting fusion nodes (FN) that are dynamically selected from a group of nodes. The detection threshold is calculated adaptively using the link quality indicator (LQI) of the sensing channel. Moreover, the proposed method can significantly minimize the typically transmitted bits in the reporting channel. The paper also discussed in detail the design parameter of the CR number on the performance of fusion values. The simulation analysis shows that the performance of the distributed cooperative sensing (DCS) process is considerably improved by the adapted threshold. The numerical results demonstrated that the error was remarkably minimized. The ROC curve of the sensing process is notably improved for detection probability and false alarm probability, respectively. Finally, it was shown that the requirement of sensitivity can be greatly improved up to 0.95.

ACS Style

Rania A. Mokhtar; Rashid Saeed; Hesham Alhumyani. Cooperative Fusion Architecture-based Distributed Spectrum Sensing Under Rayleigh Fading Channel. 2021, 1 .

AMA Style

Rania A. Mokhtar, Rashid Saeed, Hesham Alhumyani. Cooperative Fusion Architecture-based Distributed Spectrum Sensing Under Rayleigh Fading Channel. . 2021; ():1.

Chicago/Turabian Style

Rania A. Mokhtar; Rashid Saeed; Hesham Alhumyani. 2021. "Cooperative Fusion Architecture-based Distributed Spectrum Sensing Under Rayleigh Fading Channel." , no. : 1.

Review article
Published: 12 March 2021 in Security and Communication Networks
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Recently, interest in Internet of Vehicles’ (IoV) technologies has significantly emerged due to the substantial development in the smart automobile industries. Internet of Vehicles’ technology enables vehicles to communicate with public networks and interact with the surrounding environment. It also allows vehicles to exchange and collect information about other vehicles and roads. IoV is introduced to enhance road users’ experience by reducing road congestion, improving traffic management, and ensuring the road safety. The promised applications of smart vehicles and IoV systems face many challenges, such as big data collection in IoV and distribution to attractive vehicles and humans. Another challenge is achieving fast and efficient communication between many different vehicles and smart devices called Vehicle-to-Everything (V2X). One of the vital questions that the researchers need to address is how to effectively handle the privacy of large groups of data and vehicles in IoV systems. Artificial Intelligence technology offers many smart solutions that may help IoV networks address all these questions and issues. Machine learning (ML) is one of the highest efficient AI tools that have been extensively used to resolve all mentioned problematic issues. For example, ML can be used to avoid road accidents by analyzing the driving behavior and environment by sensing data of the surrounding environment. Machine learning mechanisms are characterized by the time change and are critical to channel modeling in-vehicle network scenarios. This paper aims to provide theoretical foundations for machine learning and the leading models and algorithms to resolve IoV applications’ challenges. This paper has conducted a critical review with analytical modeling for offloading mobile edge-computing decisions based on machine learning and Deep Reinforcement Learning (DRL) approaches for the Internet of Vehicles (IoV). The paper has assumed a Secure IoV edge-computing offloading model with various data processing and traffic flow. The proposed analytical model considers the Markov decision process (MDP) and ML in offloading the decision process of different task flows of the IoV network control cycle. In the paper, we focused on buffer and energy aware in ML-enabled Quality of Experience (QoE) optimization, where many recent related research and methods were analyzed, compared, and discussed. The IoV edge computing and fog-based identity authentication and security mechanism were presented as well. Finally, future directions and potential solutions for secure ML IoV and V2X were highlighted.

ACS Style

Elmustafa Sayed Ali; Mohammad Kamrul Hasan; Rosilah Hassan; Rashid A. Saeed; Mona Bakri Hassan; Shayla Islam; Nazmus Shaker Nafi; Savitri Bevinakoppa. Machine Learning Technologies for Secure Vehicular Communication in Internet of Vehicles: Recent Advances and Applications. Security and Communication Networks 2021, 2021, 1 -23.

AMA Style

Elmustafa Sayed Ali, Mohammad Kamrul Hasan, Rosilah Hassan, Rashid A. Saeed, Mona Bakri Hassan, Shayla Islam, Nazmus Shaker Nafi, Savitri Bevinakoppa. Machine Learning Technologies for Secure Vehicular Communication in Internet of Vehicles: Recent Advances and Applications. Security and Communication Networks. 2021; 2021 ():1-23.

Chicago/Turabian Style

Elmustafa Sayed Ali; Mohammad Kamrul Hasan; Rosilah Hassan; Rashid A. Saeed; Mona Bakri Hassan; Shayla Islam; Nazmus Shaker Nafi; Savitri Bevinakoppa. 2021. "Machine Learning Technologies for Secure Vehicular Communication in Internet of Vehicles: Recent Advances and Applications." Security and Communication Networks 2021, no. : 1-23.

Journal article
Published: 09 March 2021 in IEEE Access
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Timing synchronization has a vital role in swarm drones’ network (SDN) or a swarm of unmanned aerial vehicle (UAV) network. Current timing synchronization methods focus on enhancing single-hop skews which remarkably improve timing synchronization precision at this level. The improper clock of the drone system can cause interference, affect spectrum precision and interrupt the operation of the transceiver. In the drones’ network, master drones’ (MD) neighbor drone’s timing synchronization approaches like Reference Broadcast System (RBS) realize a good performance. However, the requirement of one super drone with a large number of broadcasts for RBS makes it unrealistic to use in some situations like SDN network situation. Appropriate study and adjustments are needed to have real timing synchronization by eliminating the clocks drift and enhancing the timing synchronization precision. Therefore, a new self-timing synchronization approach is proposed in this paper where several MD drones can autonomously generate swarm clusters. The cluster head (CH) instigates a timing synchronization procedure starting with intra-Swarm cluster timing synchronization. The intermediate drones (ID) are elected between two swarm clusters to synchronize all drones in line with the inter-swarm cluster timing synchronization approach. The proposed approach is distributed and flexible to achieve high timing synchronization precision. The paper proposes a novel self-timing synchronization approach for in large scale semi-flat SND network architecture. Self-timing synchronization is swarm cluster-based and applicable for a huge number of master drones in SDN. One is the intra-Swarm cluster where the timing synchronization procedure starts with the CH to synchronize all CM. Secondly, in the inter-swarm cluster timing synchronization, two clusters are synchronized via intermediate drone (ID). However, the simulations demonstrated that in many cases all CHs are synchronized by the synchronized CHs from intra-swarm cluster timing synchronizations; this increased the system throughput and synchronization delay to about 75% compared to what we planned to achieve. Moreover, the simulation results also proved that the achieved synchronization precision can be used for position estimation and prediction with high accuracy.

ACS Style

Fawaz Alsolami; Fahad A. Alqurashi; Mohammad Kamrul Hasan; Rashid A. Saeed; S. Abdel-Khalek; Anis Ben Ishak. Development of Self-Synchronized Drones’ Network using Cluster-based Swarm Intelligence Approach. IEEE Access 2021, PP, 1 -1.

AMA Style

Fawaz Alsolami, Fahad A. Alqurashi, Mohammad Kamrul Hasan, Rashid A. Saeed, S. Abdel-Khalek, Anis Ben Ishak. Development of Self-Synchronized Drones’ Network using Cluster-based Swarm Intelligence Approach. IEEE Access. 2021; PP (99):1-1.

Chicago/Turabian Style

Fawaz Alsolami; Fahad A. Alqurashi; Mohammad Kamrul Hasan; Rashid A. Saeed; S. Abdel-Khalek; Anis Ben Ishak. 2021. "Development of Self-Synchronized Drones’ Network using Cluster-based Swarm Intelligence Approach." IEEE Access PP, no. 99: 1-1.

Journal article
Published: 25 February 2021 in Results in Physics
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Nowadays under COVID 2019, e-learning has become a potential prop approach of technology in education that provides contemporary learners with authentic knowledge acquisitions. As a practical contribution, electronic examination (e-exam) is a novel approach in e-learning designed to solve traditional examination issues. It is a combination of assorted questions designed by specialized software to detect an individual’s performance. Despite intensive research in this area, the performance of e-exams faces challenges such as authentication of the examinee’s identity and answered papers. This paper aims to present the experiences of educational organizations in e-exam and e-evaluation as an essential tool of e-learning in various countries. The paper recommends that under the global pandemic COVID 2019 evaluating students using intensive continuous evaluation, including e-exam supported by authentication methods, which may help detect and reduce or even prevent student violations. The results show that the most used LMS tools were the Moodle and proprietary solutions which were 75% both among many other LMS tools i.e., Blackboard and eFront. The least develop countries are prefer to use open source and proprietary due to the zero cost of these solutions. The internet speed, cost and authenticity were the most challenges faced e-exams centers, which were 99%, 82%, and 68%, respectively.

ACS Style

Fatima Rayan Awad Ahmed; Thowiba E. Ahmed; Rashid A. Saeed; Hesham Alhumyani; S. Abdel-Khalek; Hanaa Abu-Zinadah. Analysis and challenges of robust E-exams performance under COVID-19. Results in Physics 2021, 23, 103987 .

AMA Style

Fatima Rayan Awad Ahmed, Thowiba E. Ahmed, Rashid A. Saeed, Hesham Alhumyani, S. Abdel-Khalek, Hanaa Abu-Zinadah. Analysis and challenges of robust E-exams performance under COVID-19. Results in Physics. 2021; 23 ():103987.

Chicago/Turabian Style

Fatima Rayan Awad Ahmed; Thowiba E. Ahmed; Rashid A. Saeed; Hesham Alhumyani; S. Abdel-Khalek; Hanaa Abu-Zinadah. 2021. "Analysis and challenges of robust E-exams performance under COVID-19." Results in Physics 23, no. : 103987.

Correction
Published: 12 February 2021 in Wireless Personal Communications
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There were errors in the first and fourth authors' names in the initial online publication. The original article has been corrected.

ACS Style

Mona Bakri Hassan; Sameer Alsharif; Hesham Alhumyani; Elmustafa Sayed Ali; Rania A. Mokhtar; Rashid A. Saeed. Correction to: An Enhanced Cooperative Communication Scheme for Physical Uplink Shared Channel in NB‑IoT. Wireless Personal Communications 2021, 1 -1.

AMA Style

Mona Bakri Hassan, Sameer Alsharif, Hesham Alhumyani, Elmustafa Sayed Ali, Rania A. Mokhtar, Rashid A. Saeed. Correction to: An Enhanced Cooperative Communication Scheme for Physical Uplink Shared Channel in NB‑IoT. Wireless Personal Communications. 2021; ():1-1.

Chicago/Turabian Style

Mona Bakri Hassan; Sameer Alsharif; Hesham Alhumyani; Elmustafa Sayed Ali; Rania A. Mokhtar; Rashid A. Saeed. 2021. "Correction to: An Enhanced Cooperative Communication Scheme for Physical Uplink Shared Channel in NB‑IoT." Wireless Personal Communications , no. : 1-1.

Article
Published: 23 January 2021 in Wireless Personal Communications
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Narrowband-IoT (NB-IoT) is a standard-based Low Power Wide Area Network technology developed to connect a wide range of new Internet of Things (IoT) devices and services. NB-IoT bandwidth is limited to a single narrow-band of 180 kHz. Although NB-IoT provides low-cost connectivity, it provides channel to large number of smart IoT installed in households, building etc. However, in NB-IoT systems, repeating same signal over additional period of time has been taken as a key technique to enhance radio coverage up to 20 dB compared to the conventional LTE. Performance of NB-IoT system optimization and modeling are still challenging particularly coverage improvement in the case of real applications. For example, the narrow bandwidth in IoT and low energy have led to problematic issues in communication between IoT devices and network station, which results in low transmitter channel quality. Repetition process is used in the paper to enhance coverage and throughput, however in mean time increase the number of repetitions demands high bandwidth. So, an enhanced cooperative relay is used with repetition to reduce the demanded bandwidth. In this paper, we proposed an enhanced repetitions cooperative process of narrowband physical uplink shared channel (NPUSCH). The NPUSCH is transmitted using one or more resource units (RUs) and each of these RUs are repeated up to 128 times to enhance coverage as well as to meet requirement of ultra-low end IoT. The optimum number of repetitions of identical slots for NPUSCH per RUs is calculated and then simulated. In addition, the paper describes the analytical simulation to evaluate the proposed repetition of cooperative process performance for LTE-NPUSCH channel. Results show dramatical enhancement of uplink NB-IoT channel quality where the performance evaluation metrics were BLER, data rate, system throughput, spectral efficiency and transmission delay. The enhanced cooperative communication scheme for NPUSCH transmission channel in NB-IoT is achieved an average 23% enhancement in overall network throughput.

ACS Style

Mona Bakri Hassan; Sameer Alsharif; Hesham Alhumyani; Elmustafa Sayed Ali; Rania A. Mokhtar; Rashid A. Saeed. An Enhanced Cooperative Communication Scheme for Physical Uplink Shared Channel in NB-IoT. Wireless Personal Communications 2021, 1 -20.

AMA Style

Mona Bakri Hassan, Sameer Alsharif, Hesham Alhumyani, Elmustafa Sayed Ali, Rania A. Mokhtar, Rashid A. Saeed. An Enhanced Cooperative Communication Scheme for Physical Uplink Shared Channel in NB-IoT. Wireless Personal Communications. 2021; ():1-20.

Chicago/Turabian Style

Mona Bakri Hassan; Sameer Alsharif; Hesham Alhumyani; Elmustafa Sayed Ali; Rania A. Mokhtar; Rashid A. Saeed. 2021. "An Enhanced Cooperative Communication Scheme for Physical Uplink Shared Channel in NB-IoT." Wireless Personal Communications , no. : 1-20.

Chapter
Published: 01 January 2021 in Advances in Systems Analysis, Software Engineering, and High Performance Computing
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One of the most important requirements is security and accessibility efforts which are represented as a critical issue that should be considered in many applications for the purpose of system confidentiality and safety. To ensure the security of current and emerging CPSs by taking into consideration the unique challenges present in this environment, development of current security mechanisms should be further studied and deployed in a manner that make it becomes more compatible with CPS environment, introduce a safer environment and maintain the quality of service at the same time. Systems known as intrusion detection systems (IDS) and intrusion prevention systems (IPS) are the most common security mechanisms used in networking and communication applications. These systems are based on artificial intelligence (AI) where computer-based algorithms are used to analyze, diagnose, and recognize that threats pattern according to an expected suspicious pattern.

ACS Style

Sara A. Mahboub; Elmustafa Sayed Ali Ahmed; Rashid A. Saeed. Smart IDS and IPS for Cyber-Physical Systems. Advances in Systems Analysis, Software Engineering, and High Performance Computing 2021, 109 -136.

AMA Style

Sara A. Mahboub, Elmustafa Sayed Ali Ahmed, Rashid A. Saeed. Smart IDS and IPS for Cyber-Physical Systems. Advances in Systems Analysis, Software Engineering, and High Performance Computing. 2021; ():109-136.

Chicago/Turabian Style

Sara A. Mahboub; Elmustafa Sayed Ali Ahmed; Rashid A. Saeed. 2021. "Smart IDS and IPS for Cyber-Physical Systems." Advances in Systems Analysis, Software Engineering, and High Performance Computing , no. : 109-136.

Chapter
Published: 01 January 2021 in Advances in Systems Analysis, Software Engineering, and High Performance Computing
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Cyber-physical systems (CPS) have emerged with development of most great applications in the modern world due to their ability to integrate computation, networking, and physical process. CPS and ML applications are widely used in Industry 4.0, military, robotics, and physical security. Development of ML techniques in CPS is strongly linked according to the definition of CPS that states CPS is the mechanism of monitoring and controlling processes using computer-based algorithms. Optimizations adopted with ML in CPS include domain adaptation and fine tuning of current systems, boosting, introducing more safety and robustness by detection and reduction of vulnerabilities, and reducing computation time in time-critical systems. Generally, ML helps CPS to learn and adapt using intelligent models that are generated from training of large-scale data after processing and analysis.

ACS Style

Rania Salih Ahmed; Elmustafa Sayed Ali Ahmed; Rashid A. Saeed. Machine Learning in Cyber-Physical Systems in Industry 4.0. Advances in Systems Analysis, Software Engineering, and High Performance Computing 2021, 20 -41.

AMA Style

Rania Salih Ahmed, Elmustafa Sayed Ali Ahmed, Rashid A. Saeed. Machine Learning in Cyber-Physical Systems in Industry 4.0. Advances in Systems Analysis, Software Engineering, and High Performance Computing. 2021; ():20-41.

Chicago/Turabian Style

Rania Salih Ahmed; Elmustafa Sayed Ali Ahmed; Rashid A. Saeed. 2021. "Machine Learning in Cyber-Physical Systems in Industry 4.0." Advances in Systems Analysis, Software Engineering, and High Performance Computing , no. : 20-41.

Review
Published: 01 January 2021 in Sustainability
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The Industrial Internet of things (IIoT) helps several applications that require power control and low cost to achieve long life. The progress of IIoT communications, mainly based on cognitive radio (CR), has been guided to the robust network connectivity. The low power communication is achieved for IIoT sensors applying the Low Power Wide Area Network (LPWAN) with the Sigfox, NBIoT, and LoRaWAN technologies. This paper aims to review the various technologies and protocols for industrial IoT applications. A depth of assessment has been achieved by comparing various technologies considering the key terms such as frequency, data rate, power, coverage, mobility, costing, and QoS. This paper provides an assessment of 64 articles published on electricity control problems of IIoT between 2007 and 2020. That prepares a qualitative technique of answering the research questions (RQ): RQ1: “How cognitive radio engage with the industrial IoT?”, RQ2: “What are the Proposed architectures that Support Cognitive Radio LPWAN based IIOT?”, and RQ3: What key success factors need to comply for reliable CIIoT support in the industry?”. With the systematic literature assessment approach, the effects displayed on the cognitive radio in LPWAN can significantly revolute the commercial IIoT. Thus, researchers are more focused in this regard. The study suggests that the essential factors of design need to be considered to conquer the critical research gaps of the existing LPWAN cognitive-enabled IIoT. A cognitive low energy architecture is brought to ensure efficient and stable communications in a heterogeneous IIoT. It will protect the network layer from offering the customers an efficient platform to rent AI, and various LPWAN technology were explored and investigated.

ACS Style

Nahla Nurelmadina; Mohammad Hasan; Imran Memon; Rashid Saeed; Khairul Zainol Ariffin; Elmustafa Ali; Rania Mokhtar; Shayla Islam; Eklas Hossain; Arif Hassan. A Systematic Review on Cognitive Radio in Low Power Wide Area Network for Industrial IoT Applications. Sustainability 2021, 13, 338 .

AMA Style

Nahla Nurelmadina, Mohammad Hasan, Imran Memon, Rashid Saeed, Khairul Zainol Ariffin, Elmustafa Ali, Rania Mokhtar, Shayla Islam, Eklas Hossain, Arif Hassan. A Systematic Review on Cognitive Radio in Low Power Wide Area Network for Industrial IoT Applications. Sustainability. 2021; 13 (1):338.

Chicago/Turabian Style

Nahla Nurelmadina; Mohammad Hasan; Imran Memon; Rashid Saeed; Khairul Zainol Ariffin; Elmustafa Ali; Rania Mokhtar; Shayla Islam; Eklas Hossain; Arif Hassan. 2021. "A Systematic Review on Cognitive Radio in Low Power Wide Area Network for Industrial IoT Applications." Sustainability 13, no. 1: 338.

Chapter
Published: 01 January 2021 in Handbook of Research on Innovations and Applications of AI, IoT, and Cognitive Technologies
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The use of AI algorithms in the IoT enhances the ability to analyse big data and various platforms for a number of IoT applications, including industrial applications. AI provides unique solutions in support of managing each of the different types of data for the IoT in terms of identification, classification, and decision making. In industrial IoT (IIoT), sensors, and other intelligence can be added to new or existing plants in order to monitor exterior parameters like energy consumption and other industrial parameters levels. In addition, smart devices designed as factory robots, specialized decision-making systems, and other online auxiliary systems are used in the industries IoT. Industrial IoT systems need smart operations management methods. The use of machine learning achieves methods that analyse big data developed for decision-making purposes. Machine learning drives efficient and effective decision making, particularly in the field of data flow and real-time analytics associated with advanced industrial computing networks.

ACS Style

Mona Bakri Hassan; Elmustafa Sayed Ali Ahmed; Rashid A. Saeed. Machine Learning for Industrial IoT Systems. Handbook of Research on Innovations and Applications of AI, IoT, and Cognitive Technologies 2021, 336 -358.

AMA Style

Mona Bakri Hassan, Elmustafa Sayed Ali Ahmed, Rashid A. Saeed. Machine Learning for Industrial IoT Systems. Handbook of Research on Innovations and Applications of AI, IoT, and Cognitive Technologies. 2021; ():336-358.

Chicago/Turabian Style

Mona Bakri Hassan; Elmustafa Sayed Ali Ahmed; Rashid A. Saeed. 2021. "Machine Learning for Industrial IoT Systems." Handbook of Research on Innovations and Applications of AI, IoT, and Cognitive Technologies , no. : 336-358.

Chapter
Published: 01 January 2021 in Advances in Systems Analysis, Software Engineering, and High Performance Computing
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A smart grid is an advanced utility, stations, meters, and energy systems that comprises a diversity of power processes of smart meters, and various power resources. The cyber-physical systems (CPSs) can play a vital role boosting the realization of the smart power grid. Applied CPS techniques that comprise soft computing methods, communication network, management, and control into a smart physical power grid can greatly boost to realize this industry. The cyber-physical smart power systems (CPSPS) are an effective model system architecture for smart grids. Topics as control policies, resiliency methods for secure utility meters, system stability, and secure end-to-end communications between various sensors/controllers would be quite interested in CPSPS. One of the essential categories in CPSPS applications is the energy management system (EMS). The chapter will spotlight the model and design the relationship between the grid and EMS networks with standardization. The chapter also highlights some necessary standards in the context of CPSPS for the grid infrastructure.

ACS Style

Nagi Faroug M. Osman; Ali Ahmed A. Elamin; Elmustafa Sayed Ali Ahmed; Rashid A. Saeed. Cyber-Physical System for Smart Grid. Advances in Systems Analysis, Software Engineering, and High Performance Computing 2021, 301 -323.

AMA Style

Nagi Faroug M. Osman, Ali Ahmed A. Elamin, Elmustafa Sayed Ali Ahmed, Rashid A. Saeed. Cyber-Physical System for Smart Grid. Advances in Systems Analysis, Software Engineering, and High Performance Computing. 2021; ():301-323.

Chicago/Turabian Style

Nagi Faroug M. Osman; Ali Ahmed A. Elamin; Elmustafa Sayed Ali Ahmed; Rashid A. Saeed. 2021. "Cyber-Physical System for Smart Grid." Advances in Systems Analysis, Software Engineering, and High Performance Computing , no. : 301-323.

Chapter
Published: 01 January 2021 in Handbook of Research on Innovations and Applications of AI, IoT, and Cognitive Technologies
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Internet of vehicles (IoV) has recently become an emerging promising field of research due to the increasing number of vehicles each day. It is a part of the internet of things (IoT) which deals with vehicle communications. As vehicular nodes are considered always in motion, they cause frequent changes in the network topology. These changes cause issues in IoV such as scalability, dynamic topology changes, and shortest path for routing. In this chapter, the authors will discuss different optimization algorithms (i.e., clustering algorithms, ant colony optimization, best interface selection [BIS] algorithm, mobility adaptive density connected clustering algorithm, meta-heuristics algorithms, and quality of service [QoS]-based optimization). These algorithms provide an important intelligent role to optimize the operation of IoV networks and promise to develop new intelligent IoV applications.

ACS Style

Elmustafa Sayed Ali Ahmed; Zahraa Tagelsir Mohammed; Mona Bakri Hassan; Rashid A. Saeed. Algorithms Optimization for Intelligent IoV Applications. Handbook of Research on Innovations and Applications of AI, IoT, and Cognitive Technologies 2021, 1 -25.

AMA Style

Elmustafa Sayed Ali Ahmed, Zahraa Tagelsir Mohammed, Mona Bakri Hassan, Rashid A. Saeed. Algorithms Optimization for Intelligent IoV Applications. Handbook of Research on Innovations and Applications of AI, IoT, and Cognitive Technologies. 2021; ():1-25.

Chicago/Turabian Style

Elmustafa Sayed Ali Ahmed; Zahraa Tagelsir Mohammed; Mona Bakri Hassan; Rashid A. Saeed. 2021. "Algorithms Optimization for Intelligent IoV Applications." Handbook of Research on Innovations and Applications of AI, IoT, and Cognitive Technologies , no. : 1-25.

Chapter
Published: 01 January 2019 in Cloud Security
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Vehicular ad-hoc networks (VANET) have become an important research area due to their ability to allow sharing resources among the users to carry out their application and provide services of transport and traffic management. VANET communication allows exchange of sensitive information among nearby vehicles such as condition of weather and road accidents in order to improve vehicle traffic efficiency through Intelligent Transportation Systems (ITS). Many technologies have been developed to enhance ITS. Recently, vehicular cloud computing (VCC) has been developed in order to overcome the drawbacks VANET. VCC technology provides low-cost services to vehicles and capable of managing road traffic efficiently by using the vehicular sources (such as internet) to make decisions and for storage. VCC is considered as the basis for improving and developing intelligent transportation systems. It plays a major role in people's lives due to its safety, security, trust, and comfort to passengers and drivers. This chapter investigates the vehicular cloud computing. The authors first concentrate on architectures. Then, they highlight applications and features provided by VCC. Additionally, they explain the challenges for VCC. Finally, the authors present opportunities and future for VCC.

ACS Style

Zeinab E. Ahmed; Rashid A. Saeed; Amitava Mukherjee. Challenges and Opportunities in Vehicular Cloud Computing. Cloud Security 2019, 2168 -2185.

AMA Style

Zeinab E. Ahmed, Rashid A. Saeed, Amitava Mukherjee. Challenges and Opportunities in Vehicular Cloud Computing. Cloud Security. 2019; ():2168-2185.

Chicago/Turabian Style

Zeinab E. Ahmed; Rashid A. Saeed; Amitava Mukherjee. 2019. "Challenges and Opportunities in Vehicular Cloud Computing." Cloud Security , no. : 2168-2185.

Conference paper
Published: 01 August 2018 in 2018 International Conference on Computer, Control, Electrical, and Electronics Engineering (ICCCEEE)
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recently, Free Space Optical (FSO) communication has been evaluated in indoor and outdoor experimental environments for other communication applications, which opens the study of environmental effects in FSO communications, these effects represents the nature environments around us such as rain and fog, which are termed by mathematical distribution models such as Iognormal and Gamma-gamma distribution. One of the major solutions that proposed to reduce these effects and enhance the received signal is the use of Multiple Input Multiple Output MIMO diversity techniques in FSO which is also considered in this study in addition to Gamma-Gamma turbulence channel. In this paper, a simulation based study is performed to evaluate Free Space Optics Communication FSOC which represents the latest technologies that implies the highest data rate links which is been used in more sensitive communication fields such as satellite communications. The results obtained from Matlab modeling. Simulations showed that better received signal can be achieved.

ACS Style

Rashid A. Saeed; Esra B. Abbas. Performance Evaluation of MIMO FSO Communication with Gamma-Gamma Turbulence Channel using Diversity Techniques. 2018 International Conference on Computer, Control, Electrical, and Electronics Engineering (ICCCEEE) 2018, 1 -5.

AMA Style

Rashid A. Saeed, Esra B. Abbas. Performance Evaluation of MIMO FSO Communication with Gamma-Gamma Turbulence Channel using Diversity Techniques. 2018 International Conference on Computer, Control, Electrical, and Electronics Engineering (ICCCEEE). 2018; ():1-5.

Chicago/Turabian Style

Rashid A. Saeed; Esra B. Abbas. 2018. "Performance Evaluation of MIMO FSO Communication with Gamma-Gamma Turbulence Channel using Diversity Techniques." 2018 International Conference on Computer, Control, Electrical, and Electronics Engineering (ICCCEEE) , no. : 1-5.

Book chapter
Published: 01 January 2018 in Advances in Computer and Electrical Engineering
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Vehicular ad-hoc networks (VANET) have become an important research area due to their ability to allow sharing resources among the users to carry out their application and provide services of transport and traffic management. VANET communication allows exchange of sensitive information among nearby vehicles such as condition of weather and road accidents in order to improve vehicle traffic efficiency through Intelligent Transportation Systems (ITS). Many technologies have been developed to enhance ITS. Recently, vehicular cloud computing (VCC) has been developed in order to overcome the drawbacks VANET. VCC technology provides low-cost services to vehicles and capable of managing road traffic efficiently by using the vehicular sources (such as internet) to make decisions and for storage. VCC is considered as the basis for improving and developing intelligent transportation systems. It plays a major role in people's lives due to its safety, security, trust, and comfort to passengers and drivers. This chapter investigates the vehicular cloud computing. The authors first concentrate on architectures. Then, they highlight applications and features provided by VCC. Additionally, they explain the challenges for VCC. Finally, the authors present opportunities and future for VCC.

ACS Style

Zeinab E. Ahmed; Rashid A. Saeed; Amitava Mukherjee. Challenges and Opportunities in Vehicular Cloud Computing. Advances in Computer and Electrical Engineering 2018, 57 -74.

AMA Style

Zeinab E. Ahmed, Rashid A. Saeed, Amitava Mukherjee. Challenges and Opportunities in Vehicular Cloud Computing. Advances in Computer and Electrical Engineering. 2018; ():57-74.

Chicago/Turabian Style

Zeinab E. Ahmed; Rashid A. Saeed; Amitava Mukherjee. 2018. "Challenges and Opportunities in Vehicular Cloud Computing." Advances in Computer and Electrical Engineering , no. : 57-74.

Chapter
Published: 01 January 2018 in Advances in Computer and Electrical Engineering
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Integration of vehicular ad-hoc network (VANET) and cellular network is a promising architecture for future machine-to-machine applications. This integration helps the vehicles have steady internet connection through cellular network (i.e., LTE), and at same time communicate with other vehicles. However, dead spot areas and unsuccessful handoff processes due to the high speed of vehicles that can disrupt the implementation of this kind of architecture. In this chapter, simplified cluster-based gateway selection (SCGS) scheme for multi-hop relay in VANET network is proposed. The scheme is achieved by utilizing a new routing protocol called an enhanced hybrid wireless mesh protocol (E-HWMP). The simulations results show that SCGS scheme through E-HWMP protocol performed better than ad-hoc on demand distance vector (AODV) routing protocol. Furthermore, SCGS scheme through E-HWMP is compared with other cluster-based gateway selections used in the previous works; the result shows that SCGS scheme through E-HWMP protocol outperforms the other cluster-based gateway selections schemes.

ACS Style

Amal Ahmed Eltahir; Rashid A. Saeed. V2V Communication Protocols in Cloud-Assisted Vehicular Networks. Advances in Computer and Electrical Engineering 2018, 125 -150.

AMA Style

Amal Ahmed Eltahir, Rashid A. Saeed. V2V Communication Protocols in Cloud-Assisted Vehicular Networks. Advances in Computer and Electrical Engineering. 2018; ():125-150.

Chicago/Turabian Style

Amal Ahmed Eltahir; Rashid A. Saeed. 2018. "V2V Communication Protocols in Cloud-Assisted Vehicular Networks." Advances in Computer and Electrical Engineering , no. : 125-150.

Chapter
Published: 01 January 2018 in Advances in Computer and Electrical Engineering
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Vehicular ad hoc networks are relied upon to essentially enhance movement security and transportation productivity. Accessible correspondence, stockpiling, and calculation assets of the associated vehicles are not well used to meet the administration necessities of canny transportation frameworks. Vehicular cloud computing (VCC) is a promising methodology that makes utilization of the preferences of distributed computing and applies them to vehicular systems. Vehicles have turned out to be prepared with different sensors and assets, making them competent to convey, to share assets, and to carry on helpfully. VC can be depicted from the point of view of uses and administrations offered by vehicles that have a place with a vehicular ad hoc network (VANET) due to the impediment of calculation, stockpiling, and data transfer capacity assets for complex in-vehicle sight and sound amusement applications.

ACS Style

Sawsan Elfatih Ibrahim; Rashid Saeed; Amitava Mukherjee. Resource Management in Vehicular Cloud Computing. Advances in Computer and Electrical Engineering 2018, 75 -97.

AMA Style

Sawsan Elfatih Ibrahim, Rashid Saeed, Amitava Mukherjee. Resource Management in Vehicular Cloud Computing. Advances in Computer and Electrical Engineering. 2018; ():75-97.

Chicago/Turabian Style

Sawsan Elfatih Ibrahim; Rashid Saeed; Amitava Mukherjee. 2018. "Resource Management in Vehicular Cloud Computing." Advances in Computer and Electrical Engineering , no. : 75-97.

Conference paper
Published: 01 August 2017 in 2017 Joint International Conference on Information and Communication Technologies for Education and Training and International Conference on Computing in Arabic (ICCA-TICET)
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This paper reviews different wireless enterprise architecture standards to enable public safety voice communication interoperability using two-way radio. Different consoles and other means of third party between receiver and transmitter were used. The paper makes individual brief study to those solutions to compare between then, their optimal working areas and tabulates the results.

ACS Style

Adil Akasha Mohamed; Rashid A. Saeed; Nidhal Odeh. Public safety telecommunication interoperability two-way radio systems. 2017 Joint International Conference on Information and Communication Technologies for Education and Training and International Conference on Computing in Arabic (ICCA-TICET) 2017, 1 -5.

AMA Style

Adil Akasha Mohamed, Rashid A. Saeed, Nidhal Odeh. Public safety telecommunication interoperability two-way radio systems. 2017 Joint International Conference on Information and Communication Technologies for Education and Training and International Conference on Computing in Arabic (ICCA-TICET). 2017; ():1-5.

Chicago/Turabian Style

Adil Akasha Mohamed; Rashid A. Saeed; Nidhal Odeh. 2017. "Public safety telecommunication interoperability two-way radio systems." 2017 Joint International Conference on Information and Communication Technologies for Education and Training and International Conference on Computing in Arabic (ICCA-TICET) , no. : 1-5.