Traditional Database Model Research Articles

Research and Design of Smart Grid Monitoring System Based on Cloud Computing

Real-time data of power system is an important data for power system equipment measurement and acquisition. These data are important basis for analyzing power system stability, predicting grid load and power equipment failure and aging, and are the data that must be monitored for grid operation. Aiming at the problem of massive monitoring data access and processing in smart grid monitoring system, this paper proposes a smart grid monitoring system based on cloud computing framework by comprehensively utilizing geographic information technology, network communication technology and distributed database technology. The system’s workflow is more efficient and reliable for information processing than traditional database models and existing methods.

Application Research of Mobile Database Model Based on Ad Hoc Network

Mobile database is a kind of distributed database which is able to support mobile computing. For traditional mobile database model, there are some problems in Ad hoc network such as significant increase in the number of transaction conflicts, in communication costs, etc. Therefore, it is necessary to improve the traditional mobile database model. The paper aims at proposing algorithms of data synchronization and transaction redo etc. to enable mobile host to get access to the database efficiently and correctly. The experimental results show that the new mobile database model has good stability. 1. Preface With the development of network technology, information technology and database technology, mobile application has gradually changed people's life and work. However, as a main support of mobile application -- mobile database is able to meets the needs of getting the information that one needs anytime and anywhere. That is to say a new era has opened up and it would have gradual impact on us in every aspect. Traditional mobile database model mainly includes server, mobile support node and mobile host. The traditional mobile database has the following problems: the location of the mobile node is not fixed, the network communication is not symmetrical, and disconnections of the network occur frequently, the storage capacity and the processing ability are limited. However, the network based on traditional mobile database model has a large number of basic communication facilities such as base stations, mobile switching centers, etc., and most of them have been built around the city. Therefore, it is not necessary to consider too much about the effects of environment. As a multi-hop, centerless, self-organizing wireless network, Ad hoc network is adopted mostly because the environment or other factors are not conducive to laying infrastructure or the infrastructure has been damaged. In reality, one of the typical applications of Ad hoc network is for the investigation teams to perform field missions, to help disaster relief, and mine surveying, etc. In Ad hoc network, in view of the reasons such as limited capacity of energy and storage of the mobile host, limited bandwidth, and frequent disconnections with the master server, etc., it will bring about a lot of problems to apply the traditional database model to Ad hoc networks, it is necessary to improve the traditional mobile database model to accommodate Ad hoc network. Many experts have done in-depth study on mobile database, including Mallikharjuna Rao, N. Naidu, etc. who have applied fuzzy database to mobile database model, thus it solved the problem of uncertain data storage, improved the performance of mobile database model; Le Gruenwald, Shankar M. Banik, who also provides the methods of

NoSQL기반의 MapReduce를 이용한 방화벽 로그 분석 기법

방화벽은 대표적인 네트워크 보안 장비로서 대부분의 네트워크 내/외부에 설치되어 패킷의 입/출입을 통제하는 시스템이다. 때문에 이에 저장된 로그 데이터를 분석하는 것은 네트워크 보안연구에 중요한 기초 자료를 제공해 줄 수 있다. 그런데 최근 기술의 발달로 인터넷망의 속도가 향상되고, 네트워크가 대형화 되면서 방화벽에서 저장하는 로그데이터들의 양도 대용량화 또는 빅데이터화 되어 가고 있다. 이러한 추세 속에서, 기존의 전통적인 RDBMS방식으로 로그데이터를 분석하는 데는 한계가 있다. 본 논문은 NoSQL 기반의 MapReduce 설계를 이용한 방화벽 로그 분석기법을 통해 NoSQL방식을 도입하는 것이 대용량 로그 데이터를 더욱 효율적으로 분석할 수 있다는 점을 발견했다. 우리는 기존의 RDBMS방식과의 데이터 처리 성능을 비교하여 NoSQL방식 데이터베이스의 우수한 성능을 입증하였고, 이를 바탕으로 제안하는 설계 기법을 평가하기 위해 3가지 공격 패턴을 선정하고 이를 집계 하여 분석을 수행하는 실험을 통해 제안하는 분석 기법의 성능 및 정확성을 입증하였다. As the firewall is a typical network security equipment, it is usually installed at most of internal/external networks and makes many packet data in/out. So analyzing the its logs stored in it can provide important and fundamental data on the network security research. However, along with development of communications technology, the speed of internet network is improved and then the amount of log data is becoming 'Massive Data' or 'BigData'. In this trend, there are limits to analyze log data using the traditional database model RDBMS. In this paper, through our Method of Analyzing Firewall log data using MapReduce based on NoSQL, we have discovered that the introducing NoSQL data base model can more effectively analyze the massive log data than the traditional one. We have demonstrated execellent performance of the NoSQL by comparing the performance of data processing with existing RDBMS. Also the proposed method is evaluated by experiments that detect the three attack patterns and shown that it is highly effective.

An object-oriented database management system for computer-aided design of tall buildings

An effective database and database management system is the key to the success of an integrated approach to software engineering applications in general, and Computer-Aided Design (CAD) for structural applications in particular. Due to the inherent nature of CAD data such as dynamic modeling, a wide range of data types, large data volume, etc., the traditional database models, such as hierarchical, network and relational models, are unable to handle the aforementioned applications satisfactorily. An object-oriented data modeling is known to be the most effective approach. However, many of the commercial object-oriented databases are designed for information management, and they are inadequate for CAD application due to the different features of the object-hierarchy and varying data management objectives during the design cycles. This paper presents a hierarchical index-based object-oriented database management model for CAD applications. To deal with the object hierarchy encountered in CAD for the design of tall buildings, the proposed database consists of several salient features: a hierarchical object model, its related storage structure, a data dictionary, a class factory and an index system. The proposed database management model has been implemented into an integrated CAD system for design application of tall buildings.

A recursive approach to office object modelling

Office modelling aims at providing abstract, conceptual tools for describing office semantics in order to ease high-level and are more likely to correct application programming. Advanced office systems are complex organizations of objects, procedures, activities, locations, etc., incorporating independent user workstations with which people cooperate in executing complicated office tasks. Office information systems support the representation, storage, access and maintenance of complex data objects occurring frequently in office environments. Based on the structural aspects of such office objects, we provide language constructs to model office procedures which are perceived as being based on the following semantic primitives: complex data object constructors that accept object components (e.g., addresses, dates, text-fragments) and return office objects of composite type (e.g., letters, forms, memos), component selectors that select specific object components from composite data objects, and operations for recognizing the type of a given complex data object. We gain our language constructs by generalizing the corresponding solutions provided by conventional, record-based database models. This leads us from the ‘flat structures’ of traditional database models to ‘recursive structures’ allowing for flexible representations of non-formatted and highly related data as required for advanced office object modelling.