With the increasing use of social networks, the storage and retrieval of videos and images has been the object of attention when it comes to performance. This study aims to evaluate the performance of nosql databases ...
详细信息
With the increasing use of social networks, the storage and retrieval of videos and images has been the object of attention when it comes to performance. This study aims to evaluate the performance of nosql databases in transactions involving digital media and in the simulation of a social network, comparing results with a relational database. The results showing that the nosql databases are more efficient than relational databases in applications involving digital media.
In this Innovative Practice Full Paper, we present our strategy for fostering synergy between nosql teaching and research. In response to the surging demand for nosql database technology, we developed the ‘nosql Data...
详细信息
ISBN:
(数字)9798350351507
ISBN:
(纸本)9798350363067
In this Innovative Practice Full Paper, we present our strategy for fostering synergy between nosql teaching and research. In response to the surging demand for nosql database technology, we developed the ‘nosql Database Systems' course. The course serves as a catalyst for students to participate in nosql research projects, facilitated by tailored research-based courses. We demonstrate the seamless integration of nosql education and research within our curriculum, showcasing student-led research projects directly stemming from the course. Furthermore, we explore the positive outcomes of sustained research endeavors. By this, we mean that subsequent projects build upon prior ones, thereby enhancing the overall quality of research within a one- or two-semester timeframe allocated for each student. Emphasizing the importance of nurturing synergy between teaching and research, we elaborate on how our nosql curriculum benefits students in learning and engaging in research in the nosql field, supported by their feedback. We also discuss the mutually beneficial relationship between faculty research efforts focused on teaching topics and the resulting enhancements in teaching quality. Finally, we share the challenges encountered along the way.
Nowadays, access to electronic medical records is an essential requirement. However, in the current healthcare system, patient records are created by the healthcare provider and stored locally in the provider's da...
详细信息
ISBN:
(纸本)9781665461672
Nowadays, access to electronic medical records is an essential requirement. However, in the current healthcare system, patient records are created by the healthcare provider and stored locally in the provider's data system. This is particularly detrimental when a service user needs to query their profile from different providers or providers desire to query a service user profile from other providers as needed. Hence, blockchain is effectively background technology to resolve this problem because of its existing features. Currently, there are many models proposed based on blockchain technology 2.0. However, these systems still take a long time for a transaction (from 6 to 10 minutes). Another obvious problem is that healthcare providers participating in the system must use the SQL database because the integrity of data is required. Meantime, the nosql database is primary care on the decentralized environments. Therefore, the problem of converting big data from SQL to nosql is also important in the healthcare system. In this article, we propose to realize an electronic medical records system by using a third-generation version of blockchain technology with many advantages. Especially the time for a transaction is only about 6 seconds based on the new data mechanism. Besides, there is a solution to convert big data from SQL to nosql safely and effectively.
A few years ago, information size increased unexpectedly and a data explosion happened. In this world of growing information, a change in database generation may also be required. Historically, we used a structured qu...
详细信息
ISBN:
(纸本)9781665464642
A few years ago, information size increased unexpectedly and a data explosion happened. In this world of growing information, a change in database generation may also be required. Historically, we used a structured query language that works best with structured data. Now, we want to work with unstructured data as well as with structured data. The solution is to use not only SQL (nosql) database, this means not only structured query language. Recently, nosql databases are widely used in many organizations. Moreover, the data is kept in external services like Database as a Service (DaaS), where server-side and client-side security concerns are created. Additionally, the database’s query processing by several clients using complicated techniques and a shared resource environment may lead to ineffective data processing and retrieval. An effective data processing technique among several customers can be used to retrieve data in a secure and effective manner. In this paper, we present an Efficient Secure Query Processing Algorithm for Unstructured Data (ESQPA_U) for efficient query processing by applying data compression techniques before transferring the encrypted results from the server to clients. We have solved security concerns by using CryptDB to encrypt a database on the server to protect the data. Encryption methods have recently been suggested to give customers secrecy in cloud storage. The queries can be processed using encrypted data using this technique without having to first decrypt it. In order to evaluate ESQPA_U performance, it is contrasted with CryptDB existing query processing method. According to results, storage space is more effective and can save up to 57% of its original space.
To improve the retrieval efficiency and accuracy of bill of quantities, a high-precision intelligent retrieval algorithm based on Elasticsearch (ES) engine, improved TF-IDF algorithm, and Jaccard similarity dynamic we...
详细信息
To improve the retrieval efficiency and accuracy of bill of quantities, a high-precision intelligent retrieval algorithm based on Elasticsearch (ES) engine, improved TF-IDF algorithm, and Jaccard similarity dynamic weighting algorithm is proposed. According to the features of bill of quantities, a kind of characteristic word extracting method based on TF-IDF and RE regular expression is proposed. The extracted characteristic words are divided into text features, specification features, and numeric features. The text features and specification features are stored in the nosql database of MongoDB to generate a historical feature database. The retrieval process of the to-be-retrieved bill is divided into two steps. The first step is named approximately retrieving, which extracts the ES searching words of the bill based on the historical feature database, and uses the ES engine to obtain the approximate matching database. The second step is designed to accurately retrieve the bill by dynamically computing the final similarity based on the three types of features and their weighted factors.
When referring to health data processing and management quickly comes across the challenge for storing this kind of information. This article resumes the research for a storage model able to support a baby's multi...
详细信息
When referring to health data processing and management quickly comes across the challenge for storing this kind of information. This article resumes the research for a storage model able to support a baby's multimodal healthcare predictive system, which our team is developing. We have took a structured approach where we define the data characteristics, the systems requirements and most significant operations required to our “business”. Understanding relational and non-relational approaches, and differences between nosql database categories we have defined what we consider the best approach for our scenario, is this case a mix of document and extensible record stores. Finally we analyze the different available technologies/platforms on this categories and how they can support our system requirements.
Rapid speeds have been acquired throughout the past decade using GPUs and nosql-databases. This paper presents a concept of a GPU-extended non-relational database management system. The research focuses on implementin...
详细信息
ISBN:
(数字)9781665404990
ISBN:
(纸本)9781665405003
Rapid speeds have been acquired throughout the past decade using GPUs and nosql-databases. This paper presents a concept of a GPU-extended non-relational database management system. The research focuses on implementing kernels and performing the basic aggregation functions over a JSON file. Different comparisons with the Numpy library, a CPU-counterpart and MongoDb show the importance of the concept. The hypothesis is to check if GPU can speed up nosql-database queries which we prove using our methods.
Internet of Things (IoT) is becoming part of our daily life. Indeed, studies predict a sharp market growth by 2020. One of the challenges of this fast-growing market is how to store and manage the amount of non-struct...
详细信息
Internet of Things (IoT) is becoming part of our daily life. Indeed, studies predict a sharp market growth by 2020. One of the challenges of this fast-growing market is how to store and manage the amount of non-structured data generated by IoT devices. In this paper, we propose a hybrid storage architecture for IoT for addressing scalability, performance, and heterogeneity issues. We selected three of the most commonly used nosql databases (Redis, MongoDB, and Cassandra) to perform the first evaluation of our architecture. Our results suggest that the hybrid storage architecture is a feasible and promising approach to address some of the issues related to the ever-growing amount of data generated by IoT devices. Additionally, our findings also show that Redis achieves a better overall performance for the two chosen types of data, namely scalar and positional.
Traditional relational database design uses conceptual, logical, and physical modeling based on Peter Chen's methods. UML (Unified Modeling Language), though being a set of software development tools, is often use...
详细信息
ISBN:
(数字)9781728132891
ISBN:
(纸本)9781728132907
Traditional relational database design uses conceptual, logical, and physical modeling based on Peter Chen's methods. UML (Unified Modeling Language), though being a set of software development tools, is often used to conceptually model data and relationships. This paper presents a methodical approach to logically and physically model data in MongoDB by utilizing UML conceptual modeling aids. Application of data models greatly impacts performance, scalability and flexibility of data systems. Furthermore, application life-cycle and expansion impact long-term decisions made during modeling. This paper takes into consideration application requirements, access patterns and life-cycle during logical and physical modeling in a cloud environment. The flexibility that a nosql modeling paradigm embodies makes logical and physical modeling complex, with no hard-and-fast rules. This paper presents logical and physical modeling concepts required during designing database applications with MongoDB.
暂无评论