Five Steps to Construct a Model of Data Allocation for Distributed Database Systems

The allocation of data to nodes in a computer communications network is a critical issue in distributed database design, specially in wide area network where optimizing the distributed queries is the main objective. Numerous models of data allocation have been presented so far (Ceri and Pelagatti, 1986; Lee et al., 1994; Apers, 1988; Mahmood et al., 1994; Theel, 1994; Saha and Mukherjee, 1994; Walfson and Jajodia, 1995), but no optimal or universally accepted algorithm exists yet, and very few algorithms have been implemented to date (Rob and Cornonel, 1993). In this paper a method to construct a model of data allocation for distributed database system has been proposed. The adopted method for the construction of the data allocation model leads to an efficient model of its kind. The proposed model not only solves distributed database design problem, but also solves distributed database maintenance problem by covering initial allocation and post allocation of the data. The efficiency of proposed model has been proved by comparing proposed model with other relevant models.     

浅谈分布式数据库系统查询优化

分布式数据库系统的查询优化,就是要寻找执行代价最小的查询执行策略,使系统执行效率达到最高。我们在应用中需要选择适当优化方法,在执行代价和便捷度之间得到最佳执行方案。     

基于禁忌GEP的分布式数据库查询优化算法

为了更好地解决分布式查询优化问题,论文在传统GEP算法的基础上,结合禁忌搜索策略,提出了基于禁忌GEP的分布式数据库查询优化算法（DistributeddatabasequeryoptimizationalgorithmbaseduponTabu-GEP,DDQO-TGEP）。仿真实验表明,随着查询关系个数的增加,DDQO-TGEP算法执行查询时所需要的查询优化时间和最优查询策略生成时间都比传统的GA和GP算法显著下降,其中查询优化时间最大下降约42．16％,最优查询策略生成时间最大下降约36．8％。     

GeMDA: A Multidimensional Data Partitioning Technique for Multiprocessor Database Systems

Several studies have repeatedly demonstrated that both the performance and scalability of a shared-nothing parallel database system depend on the physical layout of data across the processing nodes of the system. Today, data is allocated in these systems using horizontal partitioning strategies. This approach has a number of drawbacks. If a query involves the partitioning attribute, then typically only a small number of the processing nodes can be used to speedup the execution of this query. On the other hand, if the predicate of a selection query includes an attribute other than the partitioning attribute, then the entire data space must be searched. Again, this results in waste of computing resources. In recent years, several multidimensional data declustering techniques have been proposed to address these problems. However, these schemes are too restrictive (e.g., FX, ECC, etc.), or optimized for a certain type of queries (e.g., DM, HCAM, etc.). In this paper, we introduce a new technique which is flexible, and performs well for general queries. We prove its optimality properties, and present experimental results showing that our scheme outperforms DM and HCAM by a significant margin.     

并行数据库数据分布策略研究

数据分布是并行数据库系统实现的基础,其方法的优劣,直接影响到并行数据库的运行效率。通过对一维、多维几种数据分布方法的分析、对比,阐述并行数据库数据分布策略及方向。     

分布式数据库系统的查询优化策略

简要的介绍了分布式数据库系统的概念和特点,并在分析比较分布式数据库系统和集中式数据库系统查询优化目标不同特点的基础上,归纳出分布式数据库系统的查询优化目标和代价分析,进而提出查询优化的策略,并在举例中重点讨论了操作执行顺序的不同对查询性能的影响。     

一种广域网中分布式数据库设计的数据分配方法

在广域网中，片段分配是分布式数据库设计中的一个主要问题，因为它关系到整个分布式数据库系统的性能。基于一个较简单、全面的分配模型提出了一个片段分配的启发式算法，旨在尽量减少通讯代价的基础上找到一个接近最优解。     

舰艇编队防空目标分配优化算法研究

针对所要解决的舰艇编队防空目标分配问题,文章结合现代防空作战特点,建立了防空目标分配模型,并讨论了数学模型的求解问题。对模拟退火算法、遗传算法、禁忌搜索算法进行了分析和研究,运用MATLAB软件编程仿真来解决所建立的防空目标分配模型。研究表明,禁忌搜索算法每次都能以100%的概率搜索到全局最优解,但由于其搜索时间过长而且搜索时间的随机性太强,不适用于解决战时的目标分配问题。而模拟退火算法和遗传算法则可以在较短的时间内达到较高的搜索概率,在实际运用中,应根据所限定时间的不同来对这两种算法进行选择使用。另外,从程序的复杂度上来看,模拟退火算法的程序相对较为简单,而遗传算法的程序相对较为复杂。     

A Graphical Approach to Allocating Class Fragments in Distributed Objectbase Systems

This paper contributes by providing an allocation taxonomy to analyze DOBS models and identify the primary characteristics of a DOBS allocation. A graphical optimization technique, based on the work by Kernighan and Lin (The Bell System, Technical Journal, pp. 291–307, 1970), is basis of our approach. The algorithm attempts to arrive at a near optimal distribution of fragments by exchanging and/or moving fragments between every pair of sites. The algorithms are implemented and are tested with carefully generated test data to obtain an analysis of the performance. The design, implementation and analysis of the allocation algorithms form the most significant contribution of this paper. Several significant insights are derived from the analysis of the results obtained that can be usefully applied to any real life DOBS allocation design. The applicability of the allocation algorithms for the DOBS model of interest may be verified by a cost benefit analysis based on their efficiency. The optimization of the initial allocation is meaningful only if the improvement obtained by optimization justifies the additional overhead. If significant improvement is not obtainable by optimization then our efficient initial allocation scheme alone may serve the purpose.     

一种基于量子遗传算法的分布式异构数据库查询优化方法

对于分布式异构数据库,查询优化既是非常复杂的问题,又是影响系统性能的关键因素。该文结合遗传算法和量子计算的优点,提出了基于量子遗传算法的分布式异构数据库查询优化方法。仿真实验表明,该方法有效地提高了分布式异构数据库的查询优化效率。     

分布式数据库系统数据复制技术的研究

数据复制是分布式数据库系统中一项非常重要的技术,它提高了分布式数据库的容灾能力,降低了事务的响应时间。该文对数据复制技术进行了详细的研究,并介绍了数据复制在Oracle数据库中的应用。     

分布式数据库的复制和分片

该文通过对集中式数据库和分布式数据库进行比较,指出集中式数据库在存储能力,访问速度等方面存在的问题,对分布式数据库中的数据复制和分片的概念,原则,方法进行详细的论述,最后,对数据复制和分片要解决的关键问题进行分析。     

分布式数据库的复制和分片

该文通过对集中式数据库和分布式数据库进行比较,指出集中式数据库在存储能力,访问速度等方面存在的问题,对分布式数据库中的数据复制和分片的概念,原则,方法进行详细的论述,最后,对数据复制和分片要解决的关键问题进行分析。     

分布式数据库系统数据复制技术的研究

数据复制是分布式数据库系统中一项非常重要的技术,它提高了分布式数据库的容灾能力,降低了事务的响应时间。该文对数据复制技术进行了详细的研究,并介绍了数据复制在Oracle数据库中的应用。     

基于MongoDB数据库的智能医疗分布式数据提取算法

智能医疗分布式数据提取受到数据节点数目的 影响,为了提高智能医疗分布式数据提取算法的性能,提出了基于MongoDB数据库的智能医疗分布式数据提取算法.在引入MongoDB数据库集群结构的基础上,构建了分布式数据的自定义词库,同时提取出分布式数据的标本名,完成了智能医疗分布式数据的预处理;利用建立分布式数据动态簇的步骤,...     

A Model for Query Decomposition and Answer Construction in Heterogeneous Distributed Database Systems

The problem of retrieving information from a collection of heterogeneous distributed databases has attracted a number of solutions. However, the task of integrating established database systems is complicated not only by the differences between the database systems themselves, but also by the differences in structure and semantics of the information contained within them. The problem is exacerbated when one needs to provide access to such a system for naive end-users.This paper is concerned with a Knowledge-Based Systems approach to solving this problem for clearly bounded situations, in which both the domain and the types of query are constrained. At the user interface, dialogue is conducted in terms of concepts with which the user is familiar, and these are then mapped into appropriate database queries. To achieve this a model for query decomposition and answer construction has been used. This model is based around the development of an Intensional Structure containing information necessary for the recapture of semantic information lost in the query decomposition process and required in the answer construction process. The model has been successfully implemented in combination with an embedded KBS, within a five-layer representation model.     

分布式数据库查询优化策略研究

分布式数据库系统由于数据的分布和冗余使得分布式查询处理增加了许多新的内容和复杂性,因此分布式查询处理的优化显得尤为重要。本文简要介绍分布式查询优化的目标、策略,并针对分布式数据库系统的查询优化,讲述三个典型的算法:INGRES算法、SystemR*算法、SDD-1算法,并进行对比、优化、总结,最后对SDD-1算法进行改进。     

分布式远动调度系统中实时数据库的研究与实现

本文描述了在计算机和网络新技术的基础上用Java语言开发出大规模、更高性能、分布式的以及跨平台的新型远动系统,对远动系统核心技术实时数据库技术进行研究。首先对远动系统监控的数据信息进行分类并将其作为实现分布式远程接口类的底层类,再根据分布式RMI接口通过聚集这几个类封装成为实现接口的类,最后完成了用数据集组件来实现分布式实时数据库的构想。依此方法建立的实时数据库将非常的灵活,使实时数据库甚至实现了跨平台(操作系统、硬件、网络平台)运行在任何支持JRE(Java Run Environment,Java运行环境)的平台上。     

工业监控系统中的分布式实时数据库研究

分析了工业监控系统中的分布式实时数据库的的功能与特点、结构、数据对象和事务的种类。提出建立内存数据库保证系统实时性并讨论了PC机和嵌入系统上实现内存数据库管理的区别和难点。着重研究了根据数据相关度分配数据的分布机制的实现和基于价值函数的事务并发调度。为构建工业监控系统中的分布式实时数据库提供了一条思路。     

面向林业管护的分布式数据挖掘系统的研究

首先,本文介绍了分布式数据挖掘技术、其研究现状及在林业中的应用前景;其次,设计了一个针对数字林业管护的分布式数据挖掘系统,并详细研究了各个部件的功能及系统的工作原理;最后,选择一个应用环节,引入遗传算法,具体的实现数据挖掘技术在数字林业建设中的应用.