EAI Endorsed Transactions on Cloud Systems

A Review on Quantum Computing Trends & Future Perspectives

2022-08-09T07:59:01+00:00

Over the last decade, there has been an exponential growth in high-performance computing. Computing such as cloud and fog computing is gaining popularity, whereas, Cloud computing is a computing organization where a large number of systems are connected to the internet for application, data, and storage services. Quantum computing is the use of quantum-mechanical phenomena such as superposition and entanglement to perform computation. In this paper, we describe the basic concept, history of quantum computing and development in network and cryptography, and future game design based on quantum. Specifically, we present the latest development in quantum networking and cryptography. Finally, we discuss the current research solutions and open issues for future research in quantum computing.

Investigation of Security Breaches Due to Resource Sharing in Virtual Machine Migration Using Hybrid Ant Colony Optimization with ANN

2022-08-09T08:08:37+00:00

Cloud computing is one of the active research areas in High Performance Computing. It helps to share the resources globally in a distributed manner. In this paper, hybrid ACO with ANN is designed to ensure the best and the secured VM consolidation process. Initially, the objectives constraints for power consumption, resource deterioration and the SLA parameters are modelled for the Physical Machines and Virtual Machines. The selection of VMs is explored by the concept of Ant Colony Optimization that select the best VMs by the predefined SLA parameters. Also, the eavesdropping attack is also modulated in the cloud shared environment. The proposed hybrid ACO with ANN is implemented in CloudSim and it’s compared with the honeybee with GA and PSO with GA. The simulation results have proved the efficiency of the VMs consolidation process with the security constraints in terms of time-related on uptime and downtime of the servers.

COVID-19 Fake News Detection Using Machine Learning Techniques: A Comparative Study

2022-08-09T08:12:26+00:00

Fake news has become one of the most serious issues in recent years, especially on social media. For example, during the covid-19 pandemic, a great deal of false information about the virus spread easily and quickly through the internet. In this area, researchers have given substantial answers to this problem utilizing various machine learning techniques. However, there are some gaps that need to be clarified. In the context of COVID-19 fake news detection, in this study, we present a comparison of four major machine learning algorithms: SVM, Nave Bayes, Logistic Regression, and Random Forest. We proposed four new machine learning models by combining these algorithms with two feature extraction techniques (TF-IDF and CountVectorizer). On three datasets, we tested the suggested models and analyzed their performance. According to the obtained results, we concluded that some properties of the used datasets can affect the obtained results. In addition, we find the best model overall.

Service Level Agreement (SLA) Chains Supported by Cloud in a Complex Port Ecosystem with Competing Stakeholder Goals: Editorial

2022-08-09T08:16:44+00:00

Investigating the IoT Security and Privacy Challenges: Summary and Recommendations

2022-08-31T12:07:37+00:00

With the development of innovative technology transformation like cloud and Internet of Things (IoT), more technology companies are pursuing research in employing such innovations. Smart homes and cities are just two examples of the many systems and technologies that the IoT can endorse. IoT - based smart objects communicate with other parts, such as proxies, portable devices, as well as data collectors. Although these components help to tackle a number of societal issues and offer users new, cutting-edge services, their confined processing power makes them susceptible to well-known privacy and security attacks. This in turn highlights the demand for a strong technical as well as legislative foundation and asserts the significance of validity and reliability in IoT. This paper provides an insight of the IoT, security, as well as privacy challenges, and also discusses the recommendations for IoT solutions. Further we also highlighting some unresolved problems that require further study.

The application of a optimal controller for the flexible joint robot

2022-09-09T12:23:20+00:00

This paper describes the operation of a single Degree of Freedom (DOF) flexible robotic arm by the optimal controller. The derived model is based on Euler- Lagrange approach, while the first and second-order (super twisting) Sliding Mode Control (SMC) is proposed as a nonlinear control strategy. Exploration of a flexible robotic arm with using state-of-the-art controllers is essential for practical applications. This is even more refreshing when these arms have joints that work independently of each other to create a smooth connection between the joints, but it still ensures the natural properties like a real human arm. This system has many similarities with the flexible link system of the MIMO model in its operational state analysis. Control laws must be followed by logical rules in a coherent whole. The next step is to design a controller to fit the structure of the system. The author also compared the use of the above controller with a system without using any controller to determine the effectiveness of using the above controller.

Neural Networks Application for the Data of LQG Regulator for the Flexible Joint Robot

2022-11-15T13:27:06+00:00

This paper describes the investigation of a flexible robotic arm with Degree of Freedom (DOF) through Linear Quadratic Gaussian (LQG) regulator under the influence of noise signals with using diagrams below. The derived model is based on the Euler-Lagrange approach while LQG mode is proposed as a modern control method. A flexible robotic arm that is test in the modern regulator is essential for applications. This is even more interesting while these arms have joints that work independently of each other, but they still ensure a tight connection between the joints. Testing the stability characteristics of the system through this regulator helps readers determine the output signals of a system exactly. From here, the author came up with strategies the match the requirements. Although the initial stage of the operating cycle is not stable with the use of LQG regulator, most of later stages of this process of closed systems of robotic systems gradually become stable. In particular, adjusting LQG for flexible joint robot gives satisfactory simulation results. This promises a positive result of other joint robot. Neural networks applied in this paper have proven its effectiveness in information security issues. It is also very useful for tight control of possible situations such as a large scale attack on network systems, automated control systems. The main contributions of this paper have been clearly demonstrated through two strategies that need to be addressed: LQG, neural networks for the data of LQG regulator.The methods described above have not been previously published for this model. Therefore, this article was born to outline the above objectives and the plans have been satisfactorily implemented. These studies are important because they serve as a necessary database in the selection of control strategies according to the requirements. Simulation results are done by Matlab. The purpose of the study of this paper: the author has searched for a stability of the system through the above methods. The applied method is a thorough study of the structure of the system as well as the construction of algorithms to form the regulator. The result ia a reliable simulation of events after the system is controlled by these regulators.

System Modeling and Artificial Neural Network (ANN) Design for Lateral and Longitudinal of F-16

2022-11-18T08:56:24+00:00

Today, the classical control methods are still widely used because of their excellent performance in a working environment with conditions of geo-graphical distance. They are suitable for functions of the system: more flexible operating system, easy to perform, less unwanted ricks occur, the efficiency of controlling a system better. Besides the traditional control methods, the author has applied more modern and smarter algorithms such as artificial intelligence to control a system on the ground or a system moving in the air. In this paper, artificial neural network (ANN) is applied for a flight model to demonstrate its effectiveness in all cases. ANN in this article to show off its amazing application for flying devices. This is a useful method because it is highly secure. Simulation is done by Matlab.