Most Internet of Vehicles (IoV) applications are delay-sensitive and require resources for data storage and tasks processing, which is very difficult to afford by vehicles. Such tasks are often offloaded to more powerful entities, like cloud and fog servers. Fog computing is decentralized infrastructure located between data source and cloud, supplies several benefits that make it a non-frivolous extension of the cloud. The high volume data which is generated by vehicles’ sensors and also the limited computation capabilities of vehicles have imposed several challenges on VANETs systems. Therefore, VANETs is integrated with fog computing to form a paradigm namely Vehicular Fog Computing (VFC) which provide low-latency services to mobile vehicles. Several studies have tackled the task offloading problem in the VFC field. However, recent studies have not carefully addressed the transmission path to the destination node and did not consider the energy consumption of vehicles. This paper aims to optimize the task offloading process in the VFC system in terms of latency and energy objectives under deadline constraint by adopting a Multi-Objective Evolutionary Algorithm (MOEA). Road Side Units (RSUs) x-Vehicles Mutli-Objective Computation offloading method (RxV-MOC) is proposed, where an elite of vehicles are utilized as fog nodes for tasks execution and all vehicles in the system are utilized for tasks transmission. The well-known Dijkstra's algorithm is adopted to find the minimum path between each two nodes. The simulation results show that the RxV-MOC has reduced significantly the energy consumption and latency for the VFC system in comparison with First-Fit algorithm, Best-Fit algorithm, and the MOC method.
This paper explores VANET topics: architecture, characteristics, security, routing protocols, applications, simulators, and 5G integration. We update, edit, and summarize some of the published data as we analyze each notion. For ease of comprehension and clarity, we give part of the data as tables and figures. This survey also raises issues for potential future research topics, such as how to integrate VANET with a 5G cellular network and how to use trust mechanisms to enhance security, scalability, effectiveness, and other VANET features and services. In short, this review may aid academics and developers in choosing the key VANET characteristics for their objectives in a single document.
Community structures are fundamental in understanding the structure and functionality of complex networks. Different optimization algorithms, including both single-objective and multi-objective approaches, have been employed to address the challenge of community detection. Recently, multi-objective evolutionary algorithms (MOEAs) have attracted many researchers to identify communities in static networks. Many algorithms have been proposed to find a solution that achieves a trade-off between exploring new areas of the solution space and improving the quality of existing solutions. In this trade-off is crucial; whereas exploitation improves existing solutions, it may fail to find better solutions from insufficiently explored regions o
... Show MoreIn this work the effect of choosing tri-circular tube section had been addressed to minimize the end effector’s error, a comparison had been made between the tri-tube section and the traditional square cross section for a robot arm, the study shows that for the same weight of square section and tri-tube section the error may be reduced by about 33%.
A program had been built up by the use of MathCAD software to calculate the minimum weight of a square section robot arm that could with stand a given pay load and gives a minimum deflection. The second part of the program makes an optimization process for the dimension of the cross section and gives the dimensions of the tri-circular tube cross section that have the same weight of
... Show MoreIn the last few years, the Internet of Things (IoT) is gaining remarkable attention in both academic and industrial worlds. The main goal of the IoT is laying on describing everyday objects with different capabilities in an interconnected fashion to the Internet to share resources and to carry out the assigned tasks. Most of the IoT objects are heterogeneous in terms of the amount of energy, processing ability, memory storage, etc. However, one of the most important challenges facing the IoT networks is the energy-efficient task allocation. An efficient task allocation protocol in the IoT network should ensure the fair and efficient distribution of resources for all objects to collaborate dynamically with limited energy. The canonic
... Show MoreMagnetic levitation (Maglev) systems are employed in a wide range of applications and are therefore of significant practical importance, which has led to growing research interest. This paper presents the design of a terminal synergetic control (TSC) and feedback linearization-based proportional-integral-derivative plus second-order derivative (FL-PIDD2) controller for the Maglev system. For developing the control law of both controllers, the mathematical model of the Maglev system is converted into a canonical system where the expression of the nonlinearity is displayed in the last differential dynamic equation of the system. The determination of the TSC and FL-PIDD2 gains for achieving the desired dynamic response is carried out using the
... Show MoreThe main focus of this research is to examine the Travelling Salesman Problem (TSP) and the methods used to solve this problem where this problem is considered as one of the combinatorial optimization problems which met wide publicity and attention from the researches for to it's simple formulation and important applications and engagement to the rest of combinatorial problems , which is based on finding the optimal path through known number of cities where the salesman visits each city only once before returning to the city of departure n this research , the benefits of( FMOLP) algorithm is employed as one of the best methods to solve the (TSP) problem and the application of the algorithm in conjun
... Show MoreBackground: University students in Iraq face rising obesity risk linked to physical inactivity, prolonged sedentary behavior, insufficient sleep, and academic stress. Longitudinal evidence examining the combined influence of these behaviors on weight status in Iraqi universities remains limited. Objective: This study examined six-month longitudinal associations of physical activity, sedentary behavior, sleep duration, and perceived stress with body mass index and percentage body fat among Iraqi university students. Methods: A prospective multi-behavioral study was conducted at six public universities in Iraq. Six hundred undergraduate students aged 18–25 years were followed monthly during one academic semester. Validated questionn
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