Client Layer Research Articles

Performance analysis of web application client layer development tools us-ing Angular, React and Vue as examples

The article presents a comparative analysis of tools for developing the client layer of web applications. The tools chosen for it were Angular 17.1.0, React 18.2.0 and Vue 3.3.4. The research process was carried out using the “Benchmark” test application, implemented with each technology. It was prepared as a performance tester, implementing tests consisting of operations that manipulate a table of data, in order to measure their execution time. The results of the performed tests became the basis for further analysis. As a result of the study, Angular became the most efficient tool in the largest number of tests. Slightly lower performance was observed with Vue, and the least efficient application turned out to be the one prepared with React.

Construction of real-time sharing model of energy big data based on end cloud collaboration technology

A real-time sharing model of energy big data based on end cloud collaboration technology is built to safely and efficiently share energy big data in all fields. Through the collaboration between the client layer and the cloud platform layer in the end cloud collaboration module, combined with the vertical federation learning algorithm and the homomorphic encryption algorithm, the energy big data knowledge in various fields is extracted and encrypted, and the encrypted knowledge is stored in the cloud platform as shared data. After the blockchain module combines the smart contract identification coding and parsing of such shared ciphertext, the ciphertext key is provided to the data user, and the shared energy big data plaintext is obtained after decryption, so as to realize the real-time security sharing of energy big data. According to the result analysis, the model performs well in data knowledge extraction and encryption, and has a good effect in ensuring the security and reliability of energy big data sharing. At the same time, the identification coding and analysis time of shared data knowledge is relatively short, making energy big data can be shared in real time. These results demonstrate the potential and feasibility of the model in facilitating big data sharing in the energy sector.

Peer-to-peer energy trading based on a hybrid blockchain system

The emergence of distributed energy and prosumers has greatly promoted the reform of the energy market. Blockchain technology provides a very potent solution for distributed energy transactions, however, blockchain technology still develops slowly in the energy field due to the unstable performance of the imperfect system. This paper aims to narrow this gap by the following steps. First, a function-driven integration method is proposed to combine the merit of blockchain distributed ledger and traditional centralized databases. Then a hybrid energy blockchain system architecture is designed, including the blockchain layer, smart contract layer, database layer, and client layer. Further, a peer-to-peer market mechanism considering energy storage arbitrage and fully automated matchmaking is developed on the hybrid blockchain system. The case study proves the effectiveness and safety of the system. The proposed architecture of combined blockchain and database technologies effectively paves the way for constructing a more reasonable and feasible distributed energy trading platform.

Multimedia Teaching in Teaching of College English Reading

Abstract With the advancement of society and the continuous development of information technology, the medium of multimedia has become an indispensable part of college English teaching. Because the traditional Web-based college English has a single teaching method, poor classroom effect, and low interest of students, this paper designs a multimedia teaching system based on a browser/server (B/S) network model and model view controller (MVC) design pattern. It is based on B/S network mode and MVC design mode and composed of a Web service layer, client layer, and database service layer. The system adopts a B/S network mode and MVC design pattern fusion mode to realize hierarchical control and different data categories and refinement and completion of the rational division of teaching resources, thus greatly improving the ability of data circulation in the teaching system. The system function design includes four parts: user registration and login, teacher teaching, student learning, and administrator management. The teacher teaching module completes the teacher’s uploading and online answering function for college English reading materials. The student learning module enables students to obtain classroom content and courses. The design of the system has improved the students’ interest in learning English and the classroom effect has also been significantly improved.

Research on Algorithms of University Course Multimedia Assistant System Based on Scientific Human-Computer Interaction

With the rapid advancement of artificial intelligence theory, this paper adopts the human-computer interaction method and derives the mathematical XXX. In combination with the optimization of the university course content, the performance is improved through the use of multimedia auxiliary systems and the use of B/S network model experience Formula, it consists of a client layer, a Web service layer and a database service layer. The physical architecture of the system is deployed. Finally, the statistical comparative analysis of mathematical science proves that the multimedia auxiliary algorithm has significant effects, and the artificial intelligence technology plays an active role in the multimedia auxiliary system.

Quality of Experience Assessment of Video Streaming

This study aims to determine the user’s satisfaction level of online streaming by using different web browsers. At the client layer, the assessment of the user’s QoE is conducted by evaluating the performance of three web browsers (Google Chrome, Mozilla Firefox, and Internet Explorer). We took the subjective test by conducting different experiments with the users and ask the users to assign ratings on the provided questionnaires, and from those ratings, we calculated results in the form of Mean Opinion Score.

Quality of Experience Assessment of Video Streaming

This study aims to determine the user’s satisfaction level of online streaming by using different web browsers. At the client layer, the assessment of the user’s QoE is conducted by evaluating the performance of three web browsers (Google Chrome, Mozilla Firefox, and Internet Explorer). We took the subjective test by conducting different experiments with the users and ask the users to assign ratings on the provided questionnaires, and from those ratings, we calculated results in the form of Mean Opinion Score.

Development of computer-based methodology for remote advanced training of medical doctors

Aim. To formulate the methodology for developing the interactive virtual computer simulations with a rating assessment of trainees’ decisions and the capability of remote access.Material and Methods. The methods of knowledge engineering were used to extract and formalize expert knowledge about the structure, significance, and relevance of clinical diagnostic information. The materials for creating virtual computer simulations were based on texts from the archival medical records, laboratory data, and multimedia results of instrumental methods of study. A three-tier network architecture was applied to provide the capabilities of remote access. It was organizationally represented by three components: a client layer, a business logic layer, and a data layer. Data transfer was provided by the Web protocols while microservices represented the infrastructure.Results. The information was formalized and structured after expert analysis and identification of significant diagnostic and prognostic data. The process included defining the domain model, identifying the aggregates and connections between them, and designing software and user interfaces. Possible solutions for trainees are now presented in the form of interactive reference lists. The artifacts of the user’s work are saved in the storage represented by the module for working with the server file system and the object-relational database management system. Each task module contains static and interactive blocks of information. The purpose of static blocks is to provide trainees with the necessary information for making clinical and diagnostic decisions. The interactive blocks allow selecting one or more solutions from the list. The content and sequence of further information presentation are determined by the trainees’ answers to the questions of an interactive block. Trainees’ decision-making competencies are evaluated using the rating system. The final personal rating is calculated as a multiplication of all coefficients related to the trainees’ decisions. This approach integrates a rating system with the trajectory chosen by the trainee for task completion.Conclusions. The distance learning technologies, developed for clinical disciplines in this study, are quite new and innovative. The repository of virtual computer simulations is under development to improve the methodological support of remote clinical training.

Model-View-Controller based Context Visualization Method for Multimedia English Teaching System: A Case Study of Multimedia Technology Teaching

With the rapid development of multimedia technology, the medium of multimedia has become an indispensable part of in modern education. College English teaching should also be combined with multimedia technology because the traditional College English teaching has singular teaching method, limited teaching resource, poor learning efficiency and low interest of students. Therefore, this paper initiates to design a multimedia teaching system based on B/S network model and MVC design pattern for college English reading teaching. This teaching innovation is based on B/S network mode and MVC design mode, and is composed of Web service layer, client layer and database service layer. The system adopts B/S network and MVC design pattern fusion mode to realize hierarchical control, and different data classification. It refines the functional division of teaching resources, thus greatly improving the capacity of data circulation in the teaching system. The system function design includes four parts: user registration and login, teacher’s teaching, student’s learning and administrator’s management. The teacher’s teaching module completes the teacher's uploading and online answering function for college English reading materials. The student learning module enables students to obtain classroom learning content and reading resource. Finally, this research discovered that the design of this system has improved the students’ interest in learning English and the teaching quality has also been significantly improved.

Towards introducing and verifying heterogeneous data integration model for cloud

In today's scenario when more and more enterprises are shifting towards cloud computing, the variety volume and velocity of the cloud is expected to cope up to the expectations. Although big data centers and latest technologies have handled huge volumes of data but still the problem of integrating heterogeneous data on the cloud persists. This paper proposes a model for integrating heterogeneous data on the cloud focusing on the security of data at rest. The model is based on service oriented computing, as services are based on fundamental features of interoperability and loose coupling. The different layers of the proposed model deal with various aspects of data interpretation on cloud. The client layer provides interface to the client and works on basic request and response parameters. The service inventory layer comprises of different services working on integration and encryption of data and the cloud data layer holds the actual data in uniform format. The paper aims to provide a solution to the heterogeneous data integration problem on cloud and data security at rest.

DeepFog: Fog Computing-Based Deep Neural Architecture for Prediction of Stress Types, Diabetes and Hypertension Attacks

The use of wearable and Internet-of-Things (IoT) for smart and affordable healthcare is trending. In traditional setups, the cloud backend receives the healthcare data and performs monitoring and prediction for diseases, diagnosis, and wellness prediction. Fog computing (FC) is a distributed computing paradigm that leverages low-power embedded processors in an intermediary node between the client layer and cloud layer. The diagnosis for wellness and fitness monitoring could be transferred to the fog layer from the cloud layer. Such a paradigm leads to a reduction in latency at an increased throughput. This paper processes a fog-based deep learning model, DeepFog that collects the data from individuals and predicts the wellness stats using a deep neural network model that can handle heterogeneous and multidimensional data. The three important abnormalities in wellness namely, (i) diabetes; (ii) hypertension attacks and (iii) stress type classification were chosen for experimental studies. We performed a detailed analysis of proposed models’ accuracy on standard datasets. The results validated the efficacy of the proposed system and architecture for accurate monitoring of these critical wellness and fitness criteria. We used standard datasets and open source software tools for our experiments.

Open-Source Network Optimization Software in the Open SDN/NFV Transport Ecosystem

Transport ecosystems that combine software defined networking (SDN) and network function virtualization (NFV) are characterized by an unprecedented network control and resource dynamicity. Manual optimization is unmanageable. In this context, open systems that manage and orchestrate SDN/NFV-enabled networks offer programming frameworks that abstract the low-level particularities in the data-plane forwarding devices and in the hardware appliances that provide the IT resources. Although these open systems present notable complexity, their programming abstractions promote a client layer where third-party applications can provide different functionalities thus enabling optimization-as-a-service business opportunities. In this paper, we cover open-source optimization software initiatives for offline planning and online provisioning and orchestration of SDN/NFV networks. With this goal in mind, we first focus on open software (and framework) initiatives through a set of realistic use cases that require optimization in multi-layer optical transport scenarios and ecosystems that combine transport with IT resources. The importance of a joint optimization of both network and IT domains is emphasized, a new paradigm triggered by SDN/NFV technologies. We discuss the theoretical limits to algorithm performances, and review available open-source frameworks for problem modeling that enable the interaction with solvers. Finally, we focus on the Net2Plan open-source network planning tool, a Java-based software that suitably embraces the multiple features required in the optimization of joint transport network and IT resource SDN/NFV ecosystems. Recent works based on Net2Plan are reviewed to illustrate its suitability for rapid algorithm prototyping, and for interaction with SDN/NFV-enabled networks.

Mist Data: Leveraging Mist Computing for Secure and Scalable Architecture for Smart and Connected Health

The smart health paradigms employ Internet-connected wearables for tele-monitoring, diagnosis providing inexpensive healthcare solutions. Mist computing reduces latency and increases throughput by processing data near the edge of the network. In the present paper, we proposed a secure mist Computing architecture that is validated on recently released public geospatial health dataset. Results and discussion support the efficacy of proposed architecture for smart geospatial health applications. The present research paper proposed SoA-Mist i.e. a three-tier secure framework for efficient management of geospatial health data with the use of mist devices. It proposed the security aspects in client layer, mist layer, fog layer and cloud layer. It has defined the prototype development by using win-win spiral model with use case and sequence diagram. Overlay analysis has been performed with the developed framework on malaria vector borne disease positive maps of Maharastra state in India from 2011 to 2014 in mobile clients as test case. Finally, It concludes with the comparison analysis of cloud based framework and proposed SoA-Mist framework.

On the Efficiency of Flexible Ethernet Client Architectures in Optical Transport Networks [Invited

The data-center interconnection (DCI) market has been rising sharply for some time, leading to the development of networking solutions tailored specifically for it. On the side of the transport network, DCI devices are characterized by simple, footprint-efficient designs focused on scalability, but still leverage the benefits of flexible-rate transponders on the line-side, to extract the most from costly optical transport infrastructures. Accompanying this evolution arose the need for a technology that could provide a flexible client layer where aggregation was done outside the transport device, but flows could still be efficiently mapped to flexible-rate transponder modules. In this context, the appearance of Flex Ethernet (FlexE) is targeted at decoupling the rates of interfaces connecting routers to transport boxes, from the actual flows traversing them. Through the introduction of an additional mapping/de-mapping layer, the capacity of multiple Ethernet interfaces can be virtualized in a resource pool for different flows. This paper addresses the application of FlexE to dense wavelength division multiplexing (DWDM) transport scenarios. Specifically, it evaluates how agnostic to FlexE a transport box should be, considering the potential trade-off between its complexity and the ability to efficiently fill lightpaths. Through a network simulation handling the provisioning of Ethernet flows in a DCI scenario, we evaluate the various FlexE use cases envisioned for transport networks, and how they affect the efficiency of router port usage and transport box provisioning, as well as their effect on the capacity of the DWDM layer.

Adaptive Fault Detection Technology Research Based on Distributed Database Disaster

Distributed storage systems demonstrate superior performance in terms of capacity, I/O throughput and scalability, but the reliability of inexpensive components is not high, and it is easy to cause catastrophic consequences of data loss. Fault detection is a key technology to provide high availability for distributed system, the new adaptive fault detection system architecture is proposed in this paper, which considered availability and disaster recovery ability, is divided into four levels: 1) Client layer: in this layer, customers can keep in touch with local network or outside network disaster recovery/backup center; 2) Server layer: in this layer, the high availability is guaranteed by its backup scheme; 3) Local recovery layer: in this layer, data backup and recovery are realized through local real-time replication; 4)Remote recovery layer: in this layer, data backup and recovery are realized (delayed) through remote backup database. And we evaluated and tested this method in our lab network environment.

User Behavior in Mass Media Websites

Mass media websites can be worthy to understand user trends in web services. RTVE, the National Broadcaster in Spain is a sample of such kind of service. Trend points to a shorter user interaction over the last three years, and a more straight access to content. Besides the number of pages consumed in a visit is becoming smaller as well. This article reviews these trends with data obtained from public sources, and analyze the distribution of web pages in the client layer and the corresponding distribution observed in the server layer. The two distributions can be characterized by Zipf-like distributions and ?, the degree of disparity in the popularity distribution, is calculated for both. In all cases ? is higher to one implying a huge concentration of popularity on a few objects.

Challenges and solutions in remote laboratories. Application to a remote laboratory of an electro-pneumatic classification cell

The field of remote laboratories has been developed over the years. These laboratories are valuable educational tools that allow students and faculty interact with real equipment through the Internet, as if they were physically in front of the system. When a remote laboratory is developed, many technical difficulties are found, mainly with respect to the links between the different elements such as physical system, database and clients. In this work, we analyze the challenges and propose approaches to develop remote laboratories that achieve flexibility, scalability and greater educational value. In particular, we present a remote laboratory for automatic control, which includes an electro-pneumatic classification cell. The architecture of the laboratory is based on the three-tier architecture (physical system layer, server layer and client layer). The client layer has been implemented with web standards such as HTML5, AJAX and CSS3, the clients interact with the system using a content management system and the communication interface between the physical system and the database uses a middleware based on OPC (Ole for Process Control). Engineering students have regularly used the remote laboratory and they have evaluated it through surveys.

New geo-portal for MODIS/SEVIRI image products with geolocation-based retrieval functionality

A large number of remote sensing data sets have been collected in recent years by Earth observation instruments such as the moderate resolution imaging spectroradiometer (MODIS) aboard the Terra/Aqua satellite and the spinning enhanced visible and infrared imager (SEVIRI) aboard the geostationary platform Meteosat Second Generation. The advanced remote sensing products resulting from the analysis of these data are useful in a wide variety of appli- cations but require significant resources in terms of storage, retrieval, and analysis. Despite the wide availability of these MODIS/SEVIRI products, the data coming from these instruments are spread among different locations and retrieved from different sources, and there is no common data repository from which the data or the associated products can be retrieved. We take a first step toward the development of a geo-portal for storing and efficiently retrieving MODIS/ SEVIRI remote sensing products. The products are obtained using an automatic system that processes the data as soon as they are provided by the collecting antennas, and then the final products are uploaded with a one day delay in the geo-portal. Our focus in this work is on describing the design and efficient implementation of the geo-portal, which allows for a user- friendly and effective access to a full repository of MODIS/SEVIRI advanced products (com- prising tens of terabytes of data) using geolocation retrieval capabilities. The geo-portal has been implemented as a web application composed of different layers. Its modular design provides quality of service and scalability (capacity for growth without any quality losing), allowing for the addition of components without the need to modify the entire system. On the client layer, an intuitive web browser interface provides users with remote access to the system. On the server layer, the system provides advanced data management and storage capabilities. On the storage layer, the system provides a secure massive storage service. An experimental evaluation of the geo-portal in terms of efficiency and product retrieval accuracy is also presented and discussed. © 2015 Society of Photo-Optical Instrumentation Engineers (SPIE) (DOI: 10.1117/1.JRS.9.096079)

Remote Laboratory for Cybersecurity of Industrial Control Systems

The increasing application of information and communication technologies (ICT) to industrial control systems has improved the scalability and flexibility of these systems, enabling the possibility to access them from external nodes. However, in many cases, the evolution of these elements has exposed industrial control systems (ICS) to a series of threats for which they are usually unprepared. These systems are currently found not only in industrial settings but also in all kinds of critical infrastructures. For that reason, it is essential to promote education in the field of cybersecurity for industrial control systems, being hands-on experience the most important aspect. In this work, we present a remote laboratory that enables performing cybersecurity tests on real industrial control elements. This platform consists of a test environment that has been added to our remote laboratory of automatic control (LRA-ULE), and lets students work with industrial equipment used in real installations such as PLCs, gateways or electrical meters. The communications architecture is based on a three-layer structure (physical, server and client layer), which is also used in the rest of the LRA-ULE platform. Moreover, a web-based front-end to interact with the system and a set of practical tasks have been developed, so that students can learn to configure and run a vulnerability scanner or to interpret vulnerability reports.

Impact of traffic distribution on web cache performance

Caches are a critical element of web-based information systems. Understanding the expected behaviour of cache policies is especially important for achieving good quality of service. Existing works have suggested that the behaviour of the web demand can be modelled as a Zipf distribution with α ≤ 1. New evidence, which is presented in this paper, shows that today websites are following Zipf distributions with α > 1. This article analyses real logs obtained from the client layer of high traffic websites. The main result of this article is that under these conditions, the cache hit ratio can be extremely high with a very small cache size. This means that a very expensive and high resource demanding cache is not needed for effective implementation: a cache size equal to 0.6% of the working set is enough to reach more than 80% of hit ratio, once the right replacement policy has been chosen.