Hesham Mohammed Ali Abdullah

@ju.edu.sa

Assistant professor
Jouf University

https://researchid.co/heshammohammedali

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

Scholar i10-index

Scopus Publications

Blockchain technology in disaster rescue wings
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.

Artificial intelligence in computer science: An overview of current trends and future directions
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.

Impact and use of blockchain technologies in organizations
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.

Innovative Modified Age of Information Metric for Packet Scheduling Using Decision Tree Classification
A.Caroline Mary, A V Senthil Kumar, and Hesham Mohammed Ali Abdullah
IEEE
AoI, Age of Information is a recent metric used in packet transfer to denote the freshness of information. In today's world, transmitting packets as fresh as possible is essential, as real-time applications play a major role. In real-time applications like tsunami-based applications, packets lose their value if they do not reach the destination sooner. Recent updates are essential to deal with real-time packets. High-priority applications require efficient packet scheduling. Based on priority, modified AoI value, etc. the packets are classified into High, medium, and low priority using a Decision tree. Modified AoI with consideration to updation is suggested to enhance packet scheduling and ensure that the updates reach on time. High-priority packets are made sure to be assigned efficiently even when the modified AoI value is at its peak. Comparisons are made to the traditional AoI technique with the proposed one to prove that the proposed method outperforms the existing ones. The significance of the research is packets are scheduled effectually as fresh as possible and also high-priority packets are scheduled effectively where delay will not be acceptable.

Comparison of Multiple Regression Particle Swarm Optimization Algorithms and Multiple Regression Multi-Objective Seven-Spot Ladybird Optimization for Host Overload / Under-Loaded Detection in Cloud Datacenter
Akram Saeed Aqlan Alhammadi, Jayakrishnan Anilakkad Raman, Mohammed A.S. Mosleh, and Hesham Mohammed Ali Abdullah
IEEE

HYBRID OPTIMIZATION BASED ON SPECTRUM AWARE OPPORTUNISTIC ROUTING FOR COGNITIVE RADIO AD HOC NETWORKS
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.

Chaotic Chicken Swarm Optimization-Based Deep Adaptive Clustering for Alzheimer Disease Detection
C. Dhanusha, A. V. Senthil Kumar, Ismail Bin Musirin, and Hesham Mohammed Ali Abdullah
Springer Singapore

A New Approach to Improve Energy Consumption Time and Life Time using Energy Based Routing in WSN
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.

An Efficient Geographical Opportunistic Routing Algorithm Using Diffusion and Sparse Approximation Models for Cognitive Radio Ad Hoc Networks
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.

Proficient opportunistic routing by queuing based optimal channel selection for the primary users in CRAHN

Vertex search based energy-efficient optimal resource allocation in Cognitive Radio Ad Hoc Networks
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.

RECENT SCHOLAR PUBLICATIONS

Blockchain Technology in Disaster Rescue Wings
DM Kumar, AVS Kumar, ID Irawati, R Latip, IMM El Emary, IB Musirin, ...
Quality of Life and Climate Change: Impacts, Sustainable Adaptation, and 2024

Comparison of Multiple Regression Particle Swarm Optimization Algorithms and Multiple Regression Multi-Objective Seven-Spot Ladybird Optimization for Host Overload/Under-Loaded
ASA Alhammadi, JA Raman, MAS Mosleh, HMA Abdullah
2023 3rd International Conference on Emerging Smart Technologies and 2023

Innovative Modified Age of Information Metric for Packet Scheduling Using Decision Tree Classification
AC Mary, AVS Kumar, HMA Abdullah
2023 Third International Conference on Ubiquitous Computing and Intelligent 2023

Hybrid optimization based on spectrum aware opportunistic routing for cognitive radio ad hoc networks
HMA Abdullah, AVS Kumar, AAQ Ahmed, MAS Mosleh
Информатика и автоматизация 22 (4), 880-905 2023

Artificial intelligence in computer science: An overview of current trends and future directions
A Prasad, AVS Kumar, P Sharma, ID Irawati, DV Chandrashekar, ...
Advances in artificial and human intelligence in the modern era, 43-60 2023

Impact and Use of Blockchain Technologies in Organizations
AVS Kumar, B Malavika, LM Rao, PVP Sundar, G Vanishree, ...
Supporting Technologies and the Impact of Blockchain on Organizations and 2023

Chaotic chicken swarm optimization-based deep adaptive clustering for alzheimer disease detection
C Dhanusha, AVS Kumar, IB Musirin, HMA Abdullah
Pervasive Computing and Social Networking: Proceedings of ICPCSN 2021, 709-719 2022

A New Approach to Improve Energy Consumption Time and Life Time using Energy Based Routing in WSN
J Poornimha, AVS Kumar, HMA Abdullah
2021 Emerging Trends in Industry 4.0 (ETI 4.0), 1-6 2021

An Efficient Geographical Opportunistic Routing Algorithm Using Diffusion and Sparse Approximation Models for Cognitive Radio Ad Hoc Networks
AV Senthil Kumar, HMA Abdullah, P Hemashree
New Trends in Computational Vision and Bio-inspired Computing: Selected 2020

Selective Cooperative Jamming Based Relay Selection and Blowfish Encryption for Enhancing Channel and Data Security in CRAHN Routing
HMA Abdullah, AVS Kumar
Enabling Technologies and Architectures for Next-Generation Networking 2019

Enabling Technologies and Architectures for Next-Generation Networking Capabilities
M Elkhodr
IGI Global 2018

Proficient Opportunistic Routing by Queuing Based Optimal Channel Selection for the Primary Users in CRAHN
HMA Abdullah, AVS Kumar
ARPN Journal of Engineering and Applied Sciences 13 (5), 1649 - 1657 2018

Vertex Search Based Energy-Efficient Optimal Resource Allocation in Cognitive Radio Ad Hoc Networks
HMA ABDULLAH, AVS KUMAR
Труды СПИИРАН 2 (57), 5-25 2018

HFSA-SORA: Hybrid firefly simulated annealing based spectrum opportunistic routing algorithm for Cognitive Radio Ad hoc Networks (CRAHN)
HMA Abdullah, AVS Kumar
2017 IEEE International Conference on Intelligent Computing and Control 2018

Modified SMOR Using Sparsity Aware Distributed Spectrum Map for Enhanced Opportunistic Routing in Cognitive Radio Adhoc Networks
hesham mohammed ali abdullah, DAVS Kumar
Journal of Advanced Research in Dynamical and Control Systems 9 (6), 184-196 2017

HB-SOR: Hybrid Bat Spectrum Map Empowered Opportunistic Routing And Energy Reduction For Cognitive Radio Ad Hoc Networks (CRAHNs)
HMA Abdullah, DAVS Kumar
International Journal of Scientific and Research Publications(IJSRP) 7 2017

A hybrid artificial bee colony based spectrum opportunistic routing algorithm for cognitive radio ad hoc networks
HMA Abdullah, AS Kumar
International Journal of Scientific & Engineering Research 7 (6), 294-303 2016

A Survey on Spectrum-Map Based on Normal Opportunistic Routing Methods for Cognitive Radio Ad Hoc Networks
HMA Abdullah, AVS Kumar
International Journal of Advanced Networking and Applications 7 (3), 2761 2015

MOST CITED SCHOLAR PUBLICATIONS

Vertex Search Based Energy-Efficient Optimal Resource Allocation in Cognitive Radio Ad Hoc Networks
HMA ABDULLAH, AVS KUMAR
Труды СПИИРАН 2 (57), 5-25 2018
Citations: 5

A New Approach to Improve Energy Consumption Time and Life Time using Energy Based Routing in WSN
J Poornimha, AVS Kumar, HMA Abdullah
2021 Emerging Trends in Industry 4.0 (ETI 4.0), 1-6 2021
Citations: 2

Enabling Technologies and Architectures for Next-Generation Networking Capabilities
M Elkhodr
IGI Global 2018
Citations: 2