In the present era, the use of the Internet has drastically increased in the sharing of digital information. In this case, the digital information is stored using cloud technology or nosql databases. However, there is...
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In the present era, the use of the Internet has drastically increased in the sharing of digital information. In this case, the digital information is stored using cloud technology or nosql databases. However, there is a significant challenge in protecting and managing the cloud and nosql-based data and extracting required information from these sources while maintaining the actual information. The network traffic has also increased significantly, which requires more memory and sufficient systems to manage and monitor the influx of Big Data. Traditional relational databases face issues in managing and securing the cloud-based dynamic data generated from various sources. nosql databases have recently been used to store and manage dynamic data effectively. However, there are security and privacy issues with the nosql databases, which remain challenging to provide. Consequently, in the present study, we propose a novel algorithm that enhances the security of the nosql databases and predicts its success rate. Initially, we implemented the Fernet data masking algorithm to secure the nosql database. Then, the secured data is classified and predicted using an innovative proposed method called the Ensemble Bagging Classifier-Logistic Regression (EBC-LR) to validate the accuracy of the secured nosql database. The experimental outcomes depict that our proposed algorithm achieves 85 percent accuracy, better than traditional methods in enhancing the security of nosql databases. Our proposed algorithm can effectively predict secure standard databases with the highest success rate.
Abstract nosql databases are famed for the characteristics of high scalability, high availability, and high faulttolerance. So nosql databases are used in a lot of applications. The data partitioning strategy and frag...
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Abstract nosql databases are famed for the characteristics of high scalability, high availability, and high faulttolerance. So nosql databases are used in a lot of applications. The data partitioning strategy and fragment allocation strategy directly affect nosql database systems＇ performance. The data partition strategy of large, global databases is performed by horizontally, vertically partitioning or combination of both. In the general way the system scatters the related fragments as possible to improve operations＇ parallel degree. But the operations are usually not very complicated in some applications, and an operation may access to more than one fragment. At the same time, those fragments which have to be accessed by an operation may interact with each other. The general allocation strategies will increase system＇s communication cost during operations execution over sites. In order to improve those applications＇ performance and enable nosql database systems to work efficiently, these applications＇ fragments have to be allocated in a reasonable way that can reduce the communication cost i.e., to minimize the total volume of data transmitted during operations execution over sites. A strategy of clustering fragments based onhypergraph is proposed, which can cluster fragments which were accessed together in most operations to the same cluster. The method uses a weighted hypergraph to represent the fragments＇ access pattem of operations. A hypergraph partitioning algorithm is used to cluster fragments in our strategy. This method can reduce the amount of sites that an operation has to span. So it can reduce the communication cost over sites. Experimental results confirm that the proposed technique will effectively contribute in solving fragments re-allocation problem in a specific application environment of nosql database system.
Many big data applications such as smart transportation, healthcare, and e-commerce need to store and query large collections of small XML documents, which has become a fundamental problem. However, existing solutions...
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Many big data applications such as smart transportation, healthcare, and e-commerce need to store and query large collections of small XML documents, which has become a fundamental problem. However, existing solutions are inadequate to deliver satisfactory query performance in such circumstances. In this paper, we propose a framework named XML2HBase to address this problem using HBase, a widely deployed nosql database. Within this framework, we design a novel encoding scheme called Pathed-Dewey Order and a two-layer mapping method to store XML documents in HBase tables. XML queries, which are represented as XPath expressions, are evaluated through their translation into queries over HBase tables. Based on an in-depth analysis of the characteristics of the proposed approach, we design and integrate four optimization strategies to reduce storage space and query response time. Extensive experiments on two well-known XML benchmarks demonstrate the superior performance of XML2HBase over three state-of-the-art methods. (C) 2021 Elsevier Inc. All rights reserved.
This paper is focused on nosql databases which designed to handle the problem of storing large amounts of data. nosql database sacrifice some consistency to achieve horizontal scalability and highperformance. We aim a...
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ISBN:
(纸本)9783319092652;9783319092645
This paper is focused on nosql databases which designed to handle the problem of storing large amounts of data. nosql database sacrifice some consistency to achieve horizontal scalability and highperformance. We aim at giving a systematic overview of nosql, introducing concepts, techniques and categories. For each category we give several typical nosql databases and discuss them in detail. Finally we analysis the challenges of nosql databases and give some predictions.
Since its emergence, nosql databases have firmly established themselves as an indispensable software component of modern cloud-native applications. However, it also becomes increasingly challenging to perform critical...
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ISBN:
(纸本)9781665406017
Since its emergence, nosql databases have firmly established themselves as an indispensable software component of modern cloud-native applications. However, it also becomes increasingly challenging to perform critical management tasks such as troubleshooting unexpected performance problems. This is due to the ever-increasing diversity and specialization of nosql databases that make it difficult to observe the internal activities. To address these challenges, we have designed and built a technique for introspecting nosql databases. Our technique traces system call sequences of key operations under controlled workloads and filters scaling patterns from constant components. Novel algorithms are developed to uncover repeating patterns of system calls from massive amounts of traces and filter out background noise with high efficiency. The evaluation shows that our technique can greatly enhance the visibility into the nosql databases enabling us to diagnose performance problems or gain insights into internal activities.
nosql database is famed for the characteristics of high scalability, high availability, and high fault-tolerance. It is used to manage data for a lot of applications. The computing model has been transferred to "...
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nosql database is famed for the characteristics of high scalability, high availability, and high fault-tolerance. It is used to manage data for a lot of applications. The computing model has been transferred to "computing close to data". Therefore, the location of fragment directly affects system's performance. Every site's load dynamical changes because of the increasing data and the ever-changing operation pattern. So system has to re-allocate fragment to improve system's performance. The general fragment re-allocation strategies of nosql database scatter the related fragments as possible to improve the operations' parallel degree. But those fragments may interact with each other in some application's operations. So the high parallel degree of operation may increase system's communication cost such as data are transferred by network. In this paper, the authors propose a fragment re-allocation strategy based on hypergraph. This strategy uses a weighted hypergraph to represent the fragments' access pattern of operations. A hypergraph partitioning algorithm is used to cluster fragments in the strategy. This strategy can improve system's performance according to reducing the communication cost while guaranteeing the parallel degree of operations. Experimental results confirm that the strategy will effectively contribute in solving fragment re-allocation problem in specific application environment of nosql database system, and it can improve system's performance.
With the continuous development of science and technology, we have fully entered the information age, people's entertainment life is becoming more and more abundant, and the Internet has also provided people with ...
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With the continuous development of science and technology, we have fully entered the information age, people's entertainment life is becoming more and more abundant, and the Internet has also provided people with a lot of convenience. The advent of the Internet age means that more and more various kinds of data are appearing, and the situation is becoming more and more abundant. The use of traditional relational databases can no longer store these data, nor can it be queried. With the continuous development of voice technology, database technology based on nosql has become a research hotspot. The availability of nosql databases is very high, the scalability is also very high, and the efficiency is very high when processing data. Based on the development of 5G networks and the development of big data technology, this research proposes a brand-new business architecture. This architecture can use the network to store data on the basis of massive data. At the same time, we also described the business scenario, providing a new idea for more intelligent education services. We use this model for teaching in schools, and we can transmit some spoken language resources to the school through the Internet for students to use for learning. Nowadays, the application range of AI technology and intelligent technology has become more and more extensive, and these technologies have also been applied in the education field. We can apply this brand-new technology in teaching to promote the development of teaching and improve students' enthusiasm and learning effect.
The Internet will become to the Internet of Things (IoT). It provides connectivity for everyone and everything that embeds some intelligence in Internet-connected objects to communicate, exchange information, take dec...
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ISBN:
(纸本)9781509011254
The Internet will become to the Internet of Things (IoT). It provides connectivity for everyone and everything that embeds some intelligence in Internet-connected objects to communicate, exchange information, take decisions, invoke actions and provide amazing services. This will bring a new ubiquitous computing and communication era and change people's lives (drastically/entirely). Moreover, the most important component in IoT is database that used for collecting and storing a lot of data from ubiquitous sensing devices. Even though, cloud-based storage solutions are becoming increasingly popular in recent years, it is inconvenient for residential environments because the sensing devices should be connected to the internet for simultaneously sending data to cloud computing. However, this solution has a high cost implication and high power consumption. Therefore, the credit-card sized computer which is fully functional is a good alternative. It is small and inexpensive computer that provides a new opportunity for IoT hardware. As a result, it is possible to use Raspberry Pi as a database server. In this paper, we will explain how to construct a database server for IoT middleware that has data distribution and low-power consumption by using credit-card size computers which have satisfactory performances and affordable price.
In this work, an efficient data storage method of nosql database is proposed for mobile devices and Internet applications to monitor appliance status in a home environment in real-time, and a home energy management (H...
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ISBN:
(纸本)9781479959679
In this work, an efficient data storage method of nosql database is proposed for mobile devices and Internet applications to monitor appliance status in a home environment in real-time, and a home energy management (HEM) mobile App for monitoring this information is also developed. An HBase cluster is constructed as a testbed for evaluation. The evaluation is conducted based on the developed APP accessing data stored by the proposed method, and it shows promising efficiency. This App together with the proposed method can help users better aware of the details of their home energy usage, and can even help other remote software agents/applications to deliver further useful applications, e.g. large scale monitoring on demand response.
database systems are at the heart of modern information systems and have become primary targets of cybersecurity attacks. With the advent of mobile and big data computing, new database models and systems, such as mobi...
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ISBN:
(纸本)9781467388450
database systems are at the heart of modern information systems and have become primary targets of cybersecurity attacks. With the advent of mobile and big data computing, new database models and systems, such as mobile and nosql databases, have been emergent and gaining popularity. Nevertheless, these new systems not only recapitulate some of the important security issues in traditional database systems but also introduce new security challenges. Few educational resources are readily available for the security education of these new database systems. This paper presents our ongoing work on developing a set of hands-on labs for the security education of mobile and nosql databases. We discuss the security issues of mobile and nosql databases, present a list of labs that are being developed, and use an example to illustrate the design of the labs.
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