Performance evaluation of distributed crossbar switch hypermesh

The interconnection network is one of the most crucial components in any multicomputer as it greatly influences the overall system performance. Several recent studies have suggested that hypergraph networks, such as the Distributed Crossbar Switch Hypermesh (DCSH), exhibit superior topological and performance characteristics over many traditional graph networks, e.g. k-ary n-cubes. Previous work on the DCSH has focused on issues related to implementation and performance comparisons with existing networks. These comparisons have so far been confined to deterministic routing and unicast (one-to-one) communication. Using analytical models validated through simulation experiments, this thesis extends that analysis to include adaptive routing and broadcast communication. The study concentrates on wormhole switching, which has been widely adopted in practical multicomputers, thanks to its low buffering requirement and the reduced dependence of latency on distance under low traffic. Adaptive routing has recently been proposed as a means of improving network performance, but while the comparative evaluation of adaptive and deterministic routing has been widely reported in the literature, the focus has been on graph networks. The first part of this thesis deals with adaptive routing, developing an analytical model to measure latency in the DCSH, and which is used throughout the rest of the work for performance comparisons. Also, an investigation of different routing algorithms in this network is presented. Conventional k-ary n-cubes have been the underlying topology of contemporary multicomputers, but it is only recently that adaptive routing has been incorporated into such systems. The thesis studies the relative performance merits of the DCSH and k-ary n-cubes under adaptive routing strategy. The analysis takes into consideration real-world factors, such as router complexity and bandwidth constraints imposed by implementation technology. However, in any network, the routing of unicast messages is not the only factor in traffic control. In many situations (for example, parallel iterative algorithms, memory update and invalidation procedures in shared memory systems, global notification of network errors), there is a significant requirement for broadcast traffic. The DCSH, by virtue of its use of hypergraph links, can implement broadcast operations particularly efficiently. The second part of the thesis examines how the DCSH and k-ary n-cube performance is affected by the presence of a broadcast traffic component. In general, these studies demonstrate that because of their relatively high diameter, k-ary n-cubes perform poorly when message lengths are short. This is consistent with earlier more simplistic analyses which led to the proposal for the express-cube, an enhancement of the basic k-ary n-cube structure, which provides additional express channels, allowing messages to bypass groups of nodes along their paths. The final part of the thesis investigates whether this "partial bypassing" can compete with the "total bypassing" capability provided inherently by the DCSH topology

Considering students’ abilities in the academic advising process

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. Academic advising is time-consuming work. At the same time, it needs to be efficient and productive in assisting the students to choose appropriate academic courses towards the completion of their selected programs in a beneficial manner. In addition, both private and public educational institutions are, currently, operating in an extremely competitive market and are, thus, faced with various challenges. Among these are the twin challenges of student retention and the rate of success in completion of their chosen academic courses. The mentioned challenges have a direct bearing on the quality of academic advising and services provided to the students, by the individual academic institution. A number of research studies have been carried out suggesting various online academic advising systems for undergraduate and graduate programs. In this context, we develop and present, here, an academic advising system which differs from and improves upon previously suggested methodologies with the inclusion of the facility to track individual students’ performance and, thus, ability in educational subjects and programs, taken in the previous academic terms. Our suggested methodology is based on the use of this facility to guide students in the selection of courses that they may register for the forthcoming academic term. We believe that the consideration of individual students’ past academic preformation, in our suggested methodology, is a significant improvement and will assist students in making more beneficial choices when registering for academic courses

Performance Evaluation of SDN-WISE in Mobile Wireless Sensors Networks

Wireless Sensors Networks (WSNs) are the backbone of numerous IoT applications such as smart homes, smart cities, smart farming, smart health, and weather monitoring. Software-Defined Networking (SDN) is an emerging communication paradigm that aims to facilitate the management of WSNs and extend their lifetime by shifting the heavy and energy consuming task of routing from sensors to a powerful and unlimited energy server, named the controller. SDN-WISE is a popular SDN implementation for WSNs. This framework has been evaluated and tested in static WSNs where the sensors have fixed positions. However, most IoT applications incorporate mobile nodes such as robots, self-driving cars, and unmanned aerial vehicles, hence the need of evaluating this framework in mobile WSNs. In this paper, we implement mobility scenarios in SDN-WISE. We then conduct an analysis of the performance of SDN-WISE in both static and mobile scenarios. Our simulation results reveal that SDN-WISE achieves a poor performance in mobile WSNs compared to the static counterparts. This stresses the urgent need to develop efficient routing protocols to handle mobility in SDN-WISE

Predicting new crescent moon visibility applying machine learning algorithms

The world\u27s population is projected to grow 32% in the coming years, and the number of Muslims is expected to grow by 70%—from 1.8 billion in 2015 to about 3 billion in 2060. Hijri is the Islamic calendar, also known as the lunar Hijri calendar, which consists of 12 lunar months, and it is tied to the Moon phases where a new crescent Moon marks the beginning of each month. Muslims use the Hijri calendar to determine important dates and religious events such as Ramadan, Haj, Muharram, etc. Till today, there is no consensus on deciding on the beginning of Ramadan month within the Muslim community. This is mainly due to the imprecise observations of the new crescent Moon in different locations. Artificial intelligence and its sub-field machine learning have shown great success in their application in several fields. In this paper, we propose the use of machine learning algorithms to help in determining the start of Ramadan month by predicting the visibility of the new crescent Moon. The results obtained from our experiments have shown very good accurate prediction and evaluation performance. The Random Forest and Support Vector Machine classifiers have provided promising results compared to other classifiers considered in this study in predicting the visibility of the new Moon

An overview of technologies deployed in GCC Countries to combat COVID-19

Since December 2019, COVID-19 and all of its variants continue to ravage the planet with consequent negative impact that has completely changed our lives within a short period of time after the outbreak of the Virus. On March 11, 2020, COVID-19 was declared a global pandemic by the World Health Organization. Since then, a group of new COVID-19 variants has emerged posing a greater danger to humanity. By the start of August 2021, the reported COVID-19 related death toll across the globe has rocketed to 4,233,139. To deal with the COVID-19 pandemic, countries across the world have rushed to develop various techniques in order to embrace an array of solutions to the problem. Covid-19 negatively affected countries in several sectors including industry, business, health, and education to name a few. The Gulf Cooperation Council (GCC) countries are among the top countries which use cutting-edge technologies in several sectors. This significantly helped these countries to overcome the spread of this virus. In this paper, we present an overview of the technologies, techniques, solutions, and strategies deployed by the Gulf Cooperation Council (GCC) countries to combat the COVID-19 pandemic in order to safeguard their citizens and speedy return of life to normalc

An overview of technologies deployed in GCC Countries to combat COVID-19

Since December 2019, COVID-19 and all of its variants continue to ravage the planet with consequent negative impact that has completely changed our lives within a short period of time after the outbreak of the Virus. On March 11, 2020, COVID-19 was declared a global pandemic by the World Health Organisation. Since then, a group of new COVID-19 variants has emerged posing a greater danger to humanity. By the start of August 2021, the reported COVID-19 related death toll across the globe has rocketed to 4,233,139. To deal with the COVID-19 pandemic, countries across the world have rushed to develop various techniques in order to embrace an array of solutions to the problem. Covid-19 negatively affected countries in several sectors including industry, business, health, and education to name a few. The Gulf Cooperation Council (GCC) countries are among the top countries which use cutting-edge technologies in several sectors. This significantly helped these countries to overcome the spread of this virus. In this paper, we present an overview of the technologies, techniques, solutions, and strategies deployed by the Gulf Cooperation Council (GCC) countries to combat the COVID-19 pandemic in order to safeguard their citizens and speedy return of life to normalcy

Smart Application for Every Car (SAEC). (AR Mobile Application)

Technology is continuously evolving at an exponential rate. Fast technological advances are being made, especially in the field of smart phones, that facilitate the conduct of our daily activities in many areas such as driving. The ever-increasing number of vehicles on roads increases the likelihood of traffic accidents, resulting in higher number of deaths and serious injuries to drivers, passengers, and pedestrians. Among the main causes of road accidents are over speeding, unsafe lane jumping, and failure to keep a safe distance between vehicles, to name a few. In an attempt to contribute to the improvement of road traffic safety, we have developed an Augmented Reality-based Smart Vehicle Driver Assistance application. The application is designed to enhance vehicle driver\u27s safety, in particular, but is also considered to lead to incremental improvement of safety of road traffic. The application can run on both Android and iOS platforms and incorporates several beneficial features required by a vehicle driver such as monitoring of vehicle speed, warning the driver in case of lane deviation, detection of road signs, and to alert the driver if the vehicle is not being driven at a safe distance from the vehicle in front. In addition to providing information to improve safe driving, the application also helps the vehicle driver save parking location of the vehicle in order to efficiently identify the parking location when retrieving the vehicle. This feature is very useful at large and unfamiliar parking areas, such as at airports or one-off large public gatherings, especially in inclement weather. The application also includes other useful functions such as the payment of parking fees, storage of information regarding vehicle maintenance, and keeping the vehicle legal document up to date. The application uses the stored information to display reminders of the appropriate action that needs to be taken before it becomes overdue

Considering Students’ Abilities in the Academic Advising Process

Academic advising is time-consuming work. At the same time, it needs to be efficient and productive in assisting the students to choose appropriate academic courses towards the completion of their selected programs in a beneficial manner. In addition, both private and public educational institutions are, currently, operating in an extremely competitive market and are, thus, faced with various challenges. Among these are the twin challenges of student retention and the rate of success in completion of their chosen academic courses. The mentioned challenges have a direct bearing on the quality of academic advising and services provided to the students, by the individual academic institution. A number of research studies have been carried out suggesting various online academic advising systems for undergraduate and graduate programs. In this context, we develop and present, here, an academic advising system which differs from and improves upon previously suggested methodologies with the inclusion of the facility to track individual students’ performance and, thus, ability in educational subjects and programs, taken in the previous academic terms. Our suggested methodology is based on the use of this facility to guide students in the selection of courses that they may register for the forthcoming academic term. We believe that the consideration of individual students’ past academic preformation, in our suggested methodology, is a significant improvement and will assist students in making more beneficial choices when registering for academic courses

Learning human anatomy using ARA mobile application

© 2019 University of Bahrain. All rights reserved. Smartphones with mobile applications have become part of everyday life, as they transformed the ways people manage their tasks. Many fields and sectors are using mobile applications to facilitate their services. Education is an important field that can utilize the various features of mobile applications to assist students and educators. Students are learning several subjects and concepts in schools, including biology. With traditional teaching methods, students may face difficulties in grasping knowledge about human anatomy. This can affect the teaching effectiveness, students\u27 learning process, their engagement in class, and their academic performance. To take full advantage of the technological tools available in the market and to improve teaching effectiveness in the biology field, this paper proposes an Augmented Reality Anatomy mobile application (ARA for short). With ARA, students can learn about human anatomy and organs using augmented reality technology. Among the interesting features of ARA are: Visualizing human anatomy as 3D models, examining the different human organs, controlling their visibility, recognizing drawings of organs, learning about each organ structure, function, and how to keep it healthy, and taking pictures and sharing them using social media platforms. More importantly, the proposed application enables the visualization of human anatomy without resorting to the marker tracking method. To evaluate the usefulness and the usability of the proposed application, the latter has been tested with students at the Genius Kids Center in Abu Dhabi, UAE. Positive feedback has been received from students who have enjoyed learning and interacting with human anatomy