Hesham Mohammed Ali Abdullah
@ju.edu.sa
Assistant professor
Jouf University
EDUCATION
Ph.D in computer Science
RESEARCH, TEACHING, or OTHER INTERESTS
Computer Science, Computer Networks and Communications, Computer Science Applications, Software
Scopus Publications
Scholar Citations
Scholar h-index
Scopus Publications
D. Mukesh Kumar, A. V. Senthil Kumar, Indrarini Dyah Irawati, Rohaya Latip, Ibrahiem M. M. El Emary, Ismail Bin Musirin, Hesham Mohammed Ali Abdullah, Manjunatha Rao L., S. Chaya, and Nitin Arya
IGI Global
Blockchain, the base of Bitcoin, has recently received broad attention. Blockchain acts as an immutable ledger that allows transactions to take place in a decentralized manner. Blockchain-based applications are growing, covering many sectors, including financial services. The reputation of Blockchain, the base of Bitcoin, has recently received broad attention. Blockchain acts as management, and the internet of things (IoT). During disaster events, timely and targeted information provision and exchange could provide great help to the stricken population in difficult and complicated environments. This chapter reports a service-oriented system, called BlockchainDisaster Rescue Wings, for providing emergency support to sufferers and rescuers in disasters. The authors identify the most frequent request sequence patterns (FRSP) of Rescue Wings, and develop a new application for efficiently scheduling the requests to minimize the response delay. The system has been tested in several disaster rescue drills, and has been successfully applied.
Arun Prasad G, A. V. Senthil Kumar, Priyanka Sharma, Indrarini Dyah Irawati, Chandrashekar D. V., Ismail Bin Musirin, Hesham Mohammed Ali Abdullah, and Manjunatha Rao L
IGI Global
Artificial intelligence (AI) is a rapidly evolving field that has seen tremendous growth in recent years. In this chapter, the authors provide an overview of current trends in AI and their applications in computer science. They also discuss the future directions of AI research and their potential impact on the field of computer science. They start by introducing the basic concepts of AI and its various subfields. Then, they present an overview of current trends in AI research, including machine learning, natural language processing, computer vision, and robotics. The authors discuss how these trends are applied in computer science, such as autonomous vehicles, fraud detection, and personalized medicine. Finally, they discuss the future directions of AI research, including the development of more explainable AI systems, the integration of AI with other emerging technologies, and the ethical considerations of AI.
A. V. Senthil Kumar, B. Malavika, L. Manjunatha Rao, P. V. Praveen Sundar, G. Vanishree, Hesham Mohammed Ali Abdullah, Ismail Bin Musirin, and Amit Dutta
IGI Global
Blockchain consists of emerging technologies such as IT infrastructure, cloud computing, security, peer-to-peer network, and cryptographic keys. The major objective of the chapter is to demystify the technologies which are supporting the blockchain applications. The IT infrastructure enhances the blockchains by coordinating and maintaining the infrastructure to work on the security and cloud storage. The blockchain can be termed as a concept which is more secure among the relevant technologies. But still there exists the chance of an attack. The security is often implemented in the network of blockchain. This security prevents the risk of cyber-attacks and fraud practices in the network. Peer-to-peer is known as a type of computer network which is frequency implemented for the digital media file distribution. In this peer-to-peer network each node would be acting as a server as well as a client by receiving and supplying the files.
Akram Saeed Aqlan Alhammadi, Jayakrishnan Anilakkad Raman, Mohammed A.S. Mosleh, and Hesham Mohammed Ali Abdullah
IEEE
Hesham Abdullah, A.V. Senthil Kumar, Ammar Qasem Ahmed, and Mohammed Saeed Mosleh
SPIIRAS
Opportunistic routing has increased the efficiency and reliability of Cognitive Radio Ad-Hoc Networks (CRAHN). Many researchers have developed opportunistic routing models, among them the Spectrum Map-empowered Opportunistic Routing (SMOR) model, which is considered a more efficient model in this field. However, there are certain limitations in SMOR, which require attention and resolution. The issue of delay and degradation of packet delivery ratio due to non-consideration of network bandwidth and throughput are addressed in this paper. In order to resolve these issues, a hybrid optimization algorithm comprising firefly optimization and grey wolf optimization algorithms are used in the basic SMOR routing model. Thus, developed Hybrid Firefly and Grey-Wolf Optimization-based SMOR (HFGWOSMOR) routing model improves the performance by high local as well as global search optimization. Initially, the relationship between the delay and throughput is analyzed and then the cooperative multipath communication is established. The proposed routing model also computes the energy values of the received signals within the bandwidth threshold and time; hence, the performance issues found in SMOR are resolved. To evaluate its efficiency, the proposed model is compared with SMOR and other existing opportunistic routing models, which show that the proposed HFGWOSMOR performs better than other models.
C. Dhanusha, A. V. Senthil Kumar, Ismail Bin Musirin, and Hesham Mohammed Ali Abdullah
Springer Singapore
Poornimha J, A V Senthil Kumar, and Hesham Mohammed Ali Abdullah
IEEE
A Wireless Sensor network (WSN) is comprised of numerous sensors that assist in the monitoring of physical environments, temperature of various applications, vibration, gravity, and signal detectors that relay data to the main node or center, which then processes the information. The key feature of sensor nodes in Wireless Sensor Network (WSN) is their low energy requirements and the simple processing capabilities. Therefore, an efficient use of resources is imperative in WSN-based applications. In this study a proposal for a new approach to maximize the sensor node lifetime is being reviewed. Once a route has been discovered, the network uses the shortest path algorithm. During routing, it searches for the energy nodes and adopts the direction of energy thereby changing the path from the shortest to that based on the energy level. The sensor values that have the most remaining energy will be chosen as the secondary path. This study identifies that the proposed method performs up to three times better than the existing outing method that is being followed.
A. V. Senthil Kumar, Hesham Mohammed Ali Abdullah, and P. Hemashree
Springer International Publishing
Spectrum-Map-empowered Opportunistic Routing (SMOR) systems have been created to accomplish dynamic opportunistic links and dependable end-to-end transmission in Cognitive radio ad-hoc networks (CRAHNs). However, only delay has been considered in the mathematical analysis of SMOR in both regular and large-scale networks which results in degraded routing performance. This work examines the transmission delay and the network throughput is evaluated and the relationship between them to develop modified SMOR algorithm by incorporating the concept of acknowledgment (ACK) for each node in the routing link. The Modified SMOR for regular CRAHN utilizes Diffusion approximation based Markov chain modeling and queuing network theory while for large-scale CRAHN utilizes sparse approximation based stochastic geometry and queuing network theory for examining delay and throughput. The Modified SMOR-1 and Modified SMOR-2 are proposed for satisfying the opportunistic routing mechanisms. The experimental results illustrate that the modified SMOR improves the reliability and dynamic routing performance.
Hesham Mohammed Ali Abdullah and A.V. Senthil Kumar
SPIIRAS
Cognitive Radio Ad Hoc Networks (CRAHN) is the infrastructure-less network model of Cognitive radios developed in an ad hoc manner. Regulating resource allocation in CRAHN is considered to be an energy constrained problem. Many researches have been performed for allocating spectrum in an efficient way using various protocols. In this paper, the Spectrum-Map-Empowered Opportunistic Routing (SMOR) model has been utilized as the fundamental model for routing and an energy efficient optimal spectrum allocation solution is provided. In the proposed model, the previously modified SMOR model is enhanced for the main objective of energy efficient and optimal resource allocation using Vertex search algorithm with a gradient-based approximation. Initially, the resource allocation problem is modelled into a non-convex optimization problem. The power allocation, data rate adaptation, channel allocation, and user scheduling policies are optimized for maximization of the energy efficiency during data transmission. The proposed Vortex search algorithm resolves this optimization problem by determining the training interval for the channel estimation and power consumption. The experimental results prove that the proposed Vertex search based modified SMOR (VS-M-SMOR) model provides efficient routing with energy efficient optimal resource allocation.