Schema Conversion Research Articles

Retracted] Social Governance Structure Construction and Resource Allocation Methods under the Management Mode of the Internet of Things

Aiming at the problems in the social governance structure level under the management mode of the Internet of Things, this paper designs a network agent based on the idea of service grid construction that has the functions of service resource configuration discovery, load balancing, and protocol conversion. Using it as a service governance infrastructure reduces the coupling between business services and service governance, and the network agent will intercept the service call traffic within the platform to achieve cross‐protocol and cross‐frame service communication. Through the proposed global query decomposition strategy and algorithm, a global query mapping is realized, which solves the problem of global query decomposition based on the global data model. We designed the unified management mechanism of two commonly used IoT databases based on XML. This process involves the realization of heterogeneous Internet of Things database resource configuration, data mode conversion, and global query mapping. Among them, in the process of data schema conversion, the conflict of the data in the schema mapping is resolved, the XML Schema is generated, the schema mapping metadata is established, and the XML document of the data is generated. We build a framework for optimal allocation of cloud computing resources based on load forecasting and propose an adaptive elastic control system for resource allocation based on resource status monitoring and demand forecasting. In view of the low resource utilization problem caused by the resource management mode of single virtual machine serving single user adopted by Internet of Things service providers, this paper constructs a new public cloud architecture with a five‐layer structure. On the basis of this architecture, an adaptive configuration mode of virtualized resources based on a single virtual machine serving multiple users is proposed. This mode can automatically search for optimal virtualization resources for application resource requests made by different users and run different applications on the same virtual machine without affecting the quality of service, so that IoT providers can guarantee services. At the same time, it improves the utilization efficiency of IoT resources and reduces energy consumption.

Data Migration tool to minimize the spatial redundancy without affecting the query performance

Objectives: The study is to minimize the spatial redundancy without affecting the query performance, i.e., time taken to execute the query. Methods/Statistical Analysis: This paper illustrates a new method of analyzing the source database system: data, relations, etc., and generation of a Graph model based upon the database and conversion of the model by creating a new algorithm compatible with NoSQL databases, keeping in mind the following parameters: (1) Less time to execute each query, (2) Maximize spatial performance with minimum space and (3) Robustness of algorithm i.e., no data loss, metadata loss, or relational data loss during two transition stages, that is from old data migration to new model and analysis of new model (comparison with relational model). Findings: The advantage of NoSQL model is the decreased time taken to execute each query and increased speed for execution of queries due to ability to deal with the unstructured data. It was found that out of the three scenarios considered in the study that is nested, non- nested and hybrid, hybrid scenario is the one that possesses the most consistent performance and hence can be stated to be the best performer. Further, the study presented a robust algorithm for the migration of data in such a way that data loss, meta data loss, or relational data loss during transition is null or minimum. Application/Improvements: The present study proposes a method to convert the relational database to NoSQL database schema conversion model. This specific model has used the concept of embedded documents to improve query speed of NoSQL database. Keywords: Data Migration, MongoDB, Relational Database, NoSQL, SQL

Conversion of XML Schema to Data Warehouse Schema using Automatic Approach

eXtensible Markup Language (XML) is data exchange format for representation data in Web based system. XML is used by many organizations for e-commerce and internet based applications such as online shopping, digital library, and electronic devices and so on. XML data is not sufficient to analyze on the Web. So XML is required to systematically analyze by industrial organizations to enable enhanced decision making. On the other hand, Data Warehouses are used by the most of the organizations for analyzing large data on their business. Conversion of XML schema and Data Warehouse schema has emerged as a continuous research area. This paper proposes a hierarchical design framework conversion of XML schema into the various Data Warehouse schema based on ROLAP. In this paper, we describe an automatic approach to support this conversion process. Our approach is based on the source of data that are XML schema and conforming XML document for designing Data Warehouse. We define more than one Data Warehouse schemas from the given XML schema using the Schema Graph has been proposed in the conversion process.

Inference Document Type (Dtd) From Xml Document: Web Structure Mining

XML is becoming a prevalent format and defacto standard for data exchange in many applications. While traditionally, lots of data are stored and managed in relational databases. There is an urgent need to research some efficient methods to convert these data stored in relational databases to XML format when integrating and exchanging these data in XML format. The semantics of XML schemas are crucial to design, query, and store XML documents and functional dependencies are very important representations of semantic information of XML schemas. As DTDs are one of the most frequently used schemas for XML documents in these days, we will use DTDs as schemas of XML documents here. This paper studies the problem of schema conversion from relational schemas to XML DTDs. As functional dependencies play an important role in the schema conversion process, the concept of functional dependency for XML DTDs is used to preserve the semantics implied by functional dependencies and keys of relational schemas. A conversion method is proposed to convert relational schemas to XML DTDs in the presence of functional dependencies, keys and foreign keys. The methods presented here can preserve the semantics implied by functional dependencies, keys and foreign keys of relational schemas and can convert multiple relational tables to XML DTDs at the same time.

スポーツにおける意味生成論―拡大体験の可能性とその契機―

The aim of the present study was to examine semantic generation related to experiences associated with sports activities, and to clarify the moments at which semantic generation occurs. Although Yano and Kubo did not discuss the issue of expanding experience, they acknowledge the possibility of semantic generation in dissolved experience, which is similar to expanding experience. Grupe perceived the achievement of voluntary and autotelic play following the rules of the game as the general semantic of sports, and mentioned several derived semantics, i.e. physical and self-personality experiences, health and well-being, excitement and tension, connections with others, involvement with nature, aesthetics and drama, and play-related motivation. Studies in this area have confirmed that semantic content other than play-related motivation is derived from either dissolved experience or expanding experience. Dissolved experience should therefore be interpreted as generation and expanding experience as semantic generation. Next, focusing on the expanding experience to which Yano and Kubo have not referred, a problem has arisen regarding the meaning of semantics and how to investigate the momentum of semantic generation. The results derived so far suggest that semantics refers to primary semantic actions, rather than content, and that in order to achieve semantic generation, recombination of already formed concepts is needed. In this regard, ”flesh” may be considered an opportunity for recombination, or a type of denial. With regard to situations in which semantic generation can be experienced, or more concretely, situations in which aspect modifications can be experienced, it can be considered that these represent a state of double bind as one form of communication, and the present study considers situations involving such experiences in sports. For example, when passing the ball in soccer or running a crucial leg of a long-distance race, athletes may experience an adverse situation and change their views and mind-set to overcome it. Such experiences will prompt a conversion of interpretation schema of the athlete him/herself.

Towards converting a production database schema to XML schema

Widespread usage of computers in large companies led to the development of different application specific databases at geographically different locations. Heterogeneous applications need to communicate and exchange data. It is vital to for engineering enterprises to have interoperability. Due to its generic design and high portability across heterogeneous environments, XML is more suitable for information exchange over the internet. It is widely accepted as one of the primary standards for data exchange and representation. The present work aims at introducing a powerful algorithm that converts a relational database schema (RDS) to XML schema definition (XSD). It is based on the constraint preserving mapping (CPM) algorithm. The algorithm proposed is capable of converting an RDS to XSD while preserving the semantic constraints of the underlying relational database. An application capable of achieving this task is developed based on the proposed algorithm. The method proved to be a novel approach for the schema conversion.

Co-transformations in Information System Reengineering

Database reengineering consists of deriving a new database from a legacy database and adapting the software components accordingly. This migration process involves three main steps, namely schema conversion, data conversion and program conversion. This paper explores the feasibility of transforming the application programs through code transformation patterns that are automatically derived from the database transformations. It presents the principles of a new transformational approach coupling database and program transformations and it describes a prototype CASE tool based on this approach.

VSAM conversion for COBOL programs

VSAM database systems are widely used on IBM mainframe systems. COBOL is the most frequently used host language to access VSAM databases. To fix the Year 2000 bug and migrate to new client/server technology, business organizations are re-engineering their legacy COBOL programs and converting VSAM databases to SQL databases. This paper addresses two important problems in VSAM conversion: database schema conversion and SQL query generation. It proposes a semi-automatic approach to the conversion of VSAM data sets to SQL tables and the conversion of VSAM operations to embedded SQL statements. The proposed approach and a prototype tool have been tested on COBOL programs from industry. Copyright © 1999 John Wiley & Sons, Ltd.

VSAM conversion for COBOL programs

VSAM database systems are widely used on IBM mainframe systems. COBOL is the most frequently used host language to access VSAM databases. To fix the Year 2000 bug and migrate to new client/server technology, business organizations are re-engineering their legacy COBOL programs and converting VSAM databases to SQL databases. This paper addresses two important problems in VSAM conversion: database schema conversion and SQL query generation. It proposes a semi-automatic approach to the conversion of VSAM data sets to SQL tables and the conversion of VSAM operations to embedded SQL statements. The proposed approach and a prototype tool have been tested on COBOL programs from industry. Copyright © 1999 John Wiley & Sons, Ltd.

Data Abstraction Technique for Relational Database Query Processing

AbstractThis paper proposes a schema conversion approach for relational database query processing. The approach not only maintains high data independence by encapsulating the data and its physical structures for a query with the procedures that manipulate them, but also aims to achieve high‐speed processing by dedicating the procedures to individual functions. This approach is experimentally compared with the interpretive and compilation methods in terms of data independence, performance and the procedure program size. The following conclusions are drawn from the experiments.(1) Although the effect of the change in physical structure is greater than that of the interpretive approach in regard to data independence, only a limited number of parts are affected and they are easily reorganized by each dedicated procedure. (2) The performance is extremely close to that of the compilation approach regardless of the kind of computer and programming language. Furthermore, the overhead for calling the procedures can be further reduced with the use of microprograms and hardware. (3) Although the number of specialized procedures increases, this is compensated by the relatively small program size of each procedure.