Ahmad Jabas

• Professor (Assistant) at Shaqra University

Artificial Intelligence (AI) and Machine Learning (ML) are rapidly changing the face of Research and Development (R&D). This chapter deals with a profound review of the current status and future trends of AI and ML in R&D. First of all, it gives an overview of huge investments and fast growth in AI, for instance, spending on AI systems worldwide is...

This chapter examines the ethical complexities of Artificial Intelligence (AI) and automated decision-making systems, now integral to fields like healthcare, finance, criminal justice, and education. While AI presents immense opportunities for innovation and efficiency, it also introduces significant ethical challenges. The chapter explores foundat...

This chapter delves into the real impact of our digital dependence on our lives – how it affects our minds, and connections with others. Shedding light on the challenges faced in balancing digital and offline worlds, especially in today's fast-paced society. We see the dangers of spending a lot of time glued to screens and the signs of digital addi...

Grid computing enables access to geographically and administratively dispersed networked resources and delivers functionality of those resources to individual users. Grid computing systems are about sharing computational resources, software and data at a large scale. The main issue in grid system is to achieve high performance of grid resources....

Computational grids have become attractive and promising platforms for solving large-scale high-performance applications of multi-institutional interest. However, the management of resources and computational tasks is a critical and complex undertaking as these resources and tasks are geographically distributed and are heterogeneous in nature. This...

In order t o satisfy the client needs, his Utility should be increased by covering his Demand. The service Utility should be maximized through effective deployment of ATMs. Genetic Algorithm is one of widely used techniques to solve complex op- timization problems, such as Banking ATM's Location Problem. This paper proposes a novel Rank Based Genet...

Genetic algorithms are becoming increasingly valuable in solving large-scale, realistic, difficult problems, and selecting replica with multiple selection criteria - availability, security and time- is one of these problems. In this paper, a rank based elitist clustering Genetic Algorithm is proposed named RRWSGA, which alleviates the problem of be...

Computational grids have become attractive and promising platforms for solving large-scale high-performance applications of multi-institutional interest. However, the management of resources and computational tasks is a critical and complex undertaking as these resources and tasks are geographically distributed and a heterogeneous in nature. This p...

Mobile Ad hoc Network (MANET ) is a collection of independent wireless mobile nodes, which is deployable on the fly. This work addresses the critical problem of key distribution in MANET by mining the traffic in network layer to extract the meta-data patterns and utilize them as tokens in application layer. A simple, fault-tolerant, and scalable ap...

The large computing capacity provided by grid systems is beneficial for solving complex problems by using many nodes of the grid at the same time. The usefulness of a grid system largely depends, among other factors, on the efficiency of the system regarding the allocation of jobs to grid resources. This paper proposes an Roulette Wheel Selection G...

In most cases, the number of resources and tasks in grid computing environment is large. Accordingly, the complexity of task scheduling is significantly increased. This results very complex optimization problem. This paper proposes an improved rank-based roulette wheel selection genetic algorithm (IRRWSGA) for scheduling independent tasks in the gr...

The new elitist multi-objective genetic algorithm PPNRGA have been used for solving engineering design problems with multiple objectives. Although there exists a number of classical techniques, evolutionary algorithms (EAs) have an edge over the classical methods where they can find multiple Pareto optimal solutions in one single simulation run. Th...

In grid computing the number of resources and tasks is usually very large, which makes the scheduling task very complex optimization problem. Genetic algorithms (GAs) have been broadly used to solve these NP-complete problems efficiently. On the other hand, the standard genetic algorithm (SGA) is too slow when used in a realistic scheduling due to...

A wireless ad hoc network (MANET) is a collection of autonomous nodes or terminals that communicate with each other by forming a multihop radio network and maintaining connectivity in a decentralized manner. MANET is characterized by a rapidly changed topology. As a result packets select different multi-hops paths to reach their destinations. Even...

Mobile ad hoc network (MANET) is a collection of autonomous nodes or terminals that communicate with each other by forming a multihop radio network. These nodes maintain connectivity in a decentralized manner. MANET is characterized by a rapidly changing topology. Nowadays, simulation is the research tool of the mobile ad hoc network (MANET) commun...

Mobile ad hoc network (MANET) is a collection of autonomous nodes or terminals that communicate with each other by forming a multihop radio network. These nodes maintain connectivity in a decentralized manner. MANET is characterized by a rapidly changed topology. As a result packets select different multi-hops paths to reach their destinations. Eve...