Events Sourcing and Command Query Responsibility Segregation Based Fast Data Architecture

With the advent of Big Data, the fields of Statistics and Computer Science coexist in current information systems. In addition to this, technological advances in embedded systems, in particular Internet of Things technologies, make it possible to develop real-time applications. These technological developments are disrupting Software Engineering because the use of large amounts of real-time data requires advanced thinking in terms of software architecture. The purpose of this article is to propose an architecture unifying not only Software Engineering and Big Data activities, but also batch and streaming architectures for the exploitation of massive data. This architecture has the advantage of making possible the development of applications and digital services exploiting very large volumes of data in real time;both for management needs and for analytical purposes. This architecture was tested on COVID-19 data as part of the development of an application for real-time monitoring of the evolution of the pandemic in Côte d’Ivoire using PostgreSQL, ELasticsearch, Kafka, Kafka Connect, NiFi, Spark, Node-Red and MoleculerJS to operationalize the architecture.

Big Data Analytics in Telecommunications: Literature Review and Architecture Recommendations

This paper focuses on facilitating state-of-the-art applications of big data analytics(BDA) architectures and infrastructures to telecommunications(telecom) industrial sector.Telecom companies are dealing with terabytes to petabytes of data on a daily basis. Io T applications in telecom are further contributing to this data deluge. Recent advances in BDA have exposed new opportunities to get actionable insights from telecom big data. These benefits and the fast-changing BDA technology landscape make it important to investigate existing BDA applications to telecom sector. For this, we initially determine published research on BDA applications to telecom through a systematic literature review through which we filter 38 articles and categorize them in frameworks, use cases, literature reviews, white papers and experimental validations. We also discuss the benefits and challenges mentioned in these articles. We find that experiments are all proof of concepts(POC) on a severely limited BDA technology stack(as compared to the available technology stack), i.e.,we did not find any work focusing on full-fledged BDA implementation in an operational telecom environment. To facilitate these applications at research-level, we propose a state-of-the-art lambda architecture for BDA pipeline implementation(called Lambda Tel) based completely on open source BDA technologies and the standard Python language, along with relevant guidelines.We discovered only one research paper which presented a relatively-limited lambda architecture using the proprietary AWS cloud infrastructure. We believe Lambda Tel presents a clear roadmap for telecom industry practitioners to implement and enhance BDA applications in their enterprises.

An architecture for mobile database management system

In order to design a new kind of mobile database management system (DBMS)more suitable for mobile computing than the existent DBMS, the essence of database systems in mobilecomputing is analyzed. An opinion is introduced that the mobile database is a kind of dynamicdistributed database, and the concept of virtual servers to translate the clients' mobility to theservers' mobility is proposed. Based on these opinions, a kind of architecture of mobile DBMS, whichis of versatility, is presented. The architecture is composed of a virtual server and a local DBMS,the virtual server is the kernel of the architecture and its functions are described. Eventually,the server kernel of a mobile DBMS prototype is illustrated.

Data Center Network Architecture

1 Introduction The history of data centers can be traced back to the 1960s. Early data centers were deployed on main- frames that were time-shared by users via remote terminals. The boom in data centers came duringthe internet era. Many companies started building large inter- net-connected facililies,

Securing Stock Transactions Using Blockchain Technology: Architecture for Identifying and Reducing Vulnerabilities Linked to the Web Applications Used (MAHV-BC)

This paper deals with the security of stock market transactions within financial markets, particularly that of the West African Economic and Monetary Union (UEMOA). The confidentiality and integrity of sensitive data in the stock market being crucial, the implementation of robust systems which guarantee trust between the different actors is essential. We therefore proposed, after analyzing the limits of several security approaches in the literature, an architecture based on blockchain technology making it possible to both identify and reduce the vulnerabilities linked to the design, implementation work or the use of web applications used for transactions. Our proposal makes it possible, thanks to two-factor authentication via the Blockchain, to strengthen the security of investors’ accounts and the automated recording of transactions in the Blockchain while guaranteeing the integrity of stock market operations. It also provides an application vulnerability report. To validate our approach, we compared our results to those of three other security tools, at the level of different metrics. Our approach achieved the best performance in each case.

Machine Learning Security Defense Algorithms Based on Metadata Correlation Features

With the popularization of the Internet and the development of technology,cyber threats are increasing day by day.Threats such as malware,hacking,and data breaches have had a serious impact on cybersecurity.The network security environment in the era of big data presents the characteristics of large amounts of data,high diversity,and high real-time requirements.Traditional security defense methods and tools have been unable to cope with the complex and changing network security threats.This paper proposes a machine-learning security defense algorithm based on metadata association features.Emphasize control over unauthorized users through privacy,integrity,and availability.The user model is established and the mapping between the user model and the metadata of the data source is generated.By analyzing the user model and its corresponding mapping relationship,the query of the user model can be decomposed into the query of various heterogeneous data sources,and the integration of heterogeneous data sources based on the metadata association characteristics can be realized.Define and classify customer information,automatically identify and perceive sensitive data,build a behavior audit and analysis platform,analyze user behavior trajectories,and complete the construction of a machine learning customer information security defense system.The experimental results show that when the data volume is 5×103 bit,the data storage integrity of the proposed method is 92%.The data accuracy is 98%,and the success rate of data intrusion is only 2.6%.It can be concluded that the data storage method in this paper is safe,the data accuracy is always at a high level,and the data disaster recovery performance is good.This method can effectively resist data intrusion and has high air traffic control security.It can not only detect all viruses in user data storage,but also realize integrated virus processing,and further optimize the security defense effect of user big data.

Green Architecture for Dense Home Area Networks Based on Radio-over-Fiber with Data Aggregation Approach

The high-density population leads to crowded cities. The future city is envisaged to encompass a large-scale network with diverse applications and a massive number of interconnected heterogeneous wireless-enabled devices. Hence, green technology elements are crucial to design sustainable and future-proof network architectures. They are the solutions for spectrum scarcity, high latency, interference, energy efficiency, and scalability that occur in dense and heterogeneous wireless networks especially in the home area network （HAN）. Radio-over-fiber （ROF） is a technology candidate to provide a global view of HAN＇s activities that can be leveraged to allocate orthogonal channel communications for enabling wireless-enabled HAN devices transmission, with considering the clustered-frequency-reuse approach. Our proposed network architecture design is mainly focused on enhancing the network throughput and reducing the average network communications latency by proposing a data aggregation unit （DAU）. The performance shows that with the DAU, the average network communications latency reduces significantly while the network throughput is enhanced, compared with the existing ROF architecture without the DAU.

Multi-source data-based 3D digital preservation of large scale ancient chinese architecture:A case report

The 3D digitalization and documentation of ancient Chinese architecture is challenging because of architectural complexity and structural delicacy.To generate complete and detailed models of this architecture,it is better to acquire,process,and fuse multi-source data instead of single-source data.In this paper,we describe our work on 3D digital preservation of ancient Chinese architecture based on multi source data.We first briefly introduce two surveyed ancient Chinese temples,Foguang Temple and Nanchan Temple.Then,we report the data acquisition equipment we used and the multi-source data we acquired.Finally,we provide an overview of several applications we conducted based on the acquired data,including ground and aerial image fusion,image and LiDAR(light detection and ranging)data fusion,and architectural scene surface reconstruction and semantic modeling.We believe that it is necessary to involve multi-source data for the 3D digital preservation of ancient Chinese architecture,and that the work in this paper will serve as a heuristic guideline for the related research communities.

Research on the Data Mining Technology in College Students'Attendance System Based on the Big Data Architecture

With the development and improvement of the information technologies,the increasing of the upper application systems and the rapid expansion of the data accumulated in the campus information environment,a typical campus big data environment has initially been formed.Because of the characteristics of the higher education,students'mobility is great and their learning environment is uncertain,so that the students'attendance mostly used the manual naming.The student attendance system based on the big data architecture is relying on the campus network,and adopting the appropriate sensors.Through the data mining technology,combined with the campus One Card solution,we can realize the management of the attendance without naming in class.It can not only strengthen the management of the students,but can also improve the management levels of the colleges and universities.

Architecture of Integrated Data Clustering Machine

Data clustering is a significant information retrieval technique in today＇s data intensive society. Over the last few decades a vast variety of huge number of data clustering algorithms have been designed and implemented for all most all data types. The quality of results of cluster analysis mainly depends on the clustering algorithm used in the analysis. Architecture of a versatile, less user dependent, dynamic and scalable data clustering machine is presented. The machine selects for analysis, the best available data clustering algorithm on the basis of the credentials of the data and previously used domain knowledge. The domain knowledge is updated on completion of each session of data analysis.

Services oriented architecture of foundation data platform of digital city

Digital city, a large complex system, is comprised many subsystem of different fields. It involves common field data, flexible field processes, seamless intra-organization and inter-organization collaborations, and increasing connectivity and interoperability between distributed or decentralized systems. All above these are involved Foundation Data of Digital city. To promote the sustainable development of Digital City, this paper investigates to the construction of Foundation Data Platform (FDP) from the view of the architecture. The paper introduces the conceptions, characteristics and underlying problems of the FDP, and discusses the key issues of the architecture paradigms what FDP might adopted via comparing Object-Oriented Architecture (OOA), Component-Based Architecture (CBA), and Service-based Architecture (SBA). The Process Embedded Service-Oriented Architecture (SOA), one of the recent SOA Application Architecture is introduced. The results indicate that the Process Embedded SOA could promote the sustainable development of Digital City and accommodate the dynamic development environments of different fields which constantly changes requirements.

Big Data Storage Architecture Design in Cloud Computing

To solve the lag problem of the traditional storage technology in mass data storage and management,the application platform is designed and built for big data on Hadoop and data warehouse integration platform,which ensured the convenience for the management and usage of data.In order to break through the master node system bottlenecks,a storage system with better performance is designed through introduction of cloud computing technology,which adopts the design of master-slave distribution patterns by the network access according to the recent principle.Thus the burden of single access the master node is reduced.Also file block update strategy and fault recovery mechanism are provided to solve the management bottleneck problem of traditional storage system on the data update and fault recovery and offer feasible technical solutions to storage management for big data.

An On-chip Interconnection QoS Verification Platform of Processor of Large Data for Architectural Modeling Analysis

This paper presents introduction for a QoS verification of on-chip interconnection based on the new progress of the industry, which combined with an AMD processor chip design for big data. Some verification experience in architectural modeling and simulation of on-chip interconnection is also introduced in this paper.

A Case Study in Teaching Pipes-and-filters and Batch Sequential Software Architectures

In this paper,a case study is carried out in comparison of pipes-and-filters architecture and batch sequential architecture.Concepts on a data flow system and the two mentioned architectures are presented.A Java template class design in implementing the "pipes" and "filters" in the pipes-and-filters architecture is given at the design level.Finally,this paper uses a concrete example to show how to use Java to implement the pipesand-filters architecture.Using varied amount of data from text files,performance and memory usage of the two architectures are illustrated.

Clustered Single-Board Devices with Docker Container Big Stream Processing Architecture

The expanding amounts of information created by Internet of Things(IoT)devices places a strain on cloud computing,which is often used for data analysis and storage.This paper investigates a different approach based on edge cloud applications,which involves data filtering and processing before being delivered to a backup cloud environment.This Paper suggest designing and implementing a low cost,low power cluster of Single Board Computers(SBC)for this purpose,reducing the amount of data that must be transmitted elsewhere,using Big Data ideas and technology.An Apache Hadoop and Spark Cluster that was used to run a test application was containerized and deployed using a Raspberry Pi cluster and Docker.To obtain system data and analyze the setup’s performance a Prometheusbased stack monitoring and alerting solution in the cloud based market is employed.This Paper assesses the system’s complexity and demonstrates how containerization can improve fault tolerance and maintenance ease,allowing the suggested solution to be used in industry.An evaluation of the overall performance is presented to highlight the capabilities and limitations of the suggested architecture,taking into consideration the suggested solution’s resource use in respect to device restrictions.

A Comparison of Several Performance Dashboards Architectures

A performance dashboard is a full-fledged business information system that is built on a business-intelligence and data- integration infrastructure. It has been one of the most hot research topics. Now many corporations have involved in the performance dashboard Architectures related techniques and many performance dashboard Architectures have been put forward. This is a favorable situation to study and application of performance dashboard related techniques. Though interesting, there are also some problems for so many Architectures forms. For to a novice or user with little knowledge about performance dashboard Architectures, it is still very hard to make a reasonable choice. What differences are there for different performance dashboard Architectures and what characteristics and advantages each has? To answer these problems, the characteristics, architectures and applications of several popular performance dashboard Architectures are analyzed and discussed in detail. From the comparison of these Architectures, users can better understand the different performance dashboard Architectures and more reasonably choose what they want.

Architecture and Methodology of Unit Testing Embedding Pair-Wise Mode for Small Team

In this paper, the new organization for unit testing embedding pair-wise mode is proposed with the core thought focused on the cooperation of programmer and tester by “cross-testing”. The typical content of unit testing for the new organizing mode should have three aspects, including self-checking, cross-testing and independent-testing. For cross-testing, executing “pair-wise” mode, mainly tackles data testing, function testing and state testing, which function testing must be done by details and state testing must be considered for completeness. With the specializing of independent-testing, it should be taken as more rigid testing without arbitrariness. Consequently, strategy and measure are addressed for data testing focusing on boundary testing and function/state testing. And organizing method of procedure and key points of tackling unit testing are investigated for the new organizing mode. In order to assess the validity of our study and approach, a series of actual examples are demonstrated for GUI software. The result indicates that the execution of unit testing for the new organizing mode is effective and applicable.