On the design of multiple key hashing files for concurrent orthogonal range retrieval between two disks

This paper concerns the following problem: given a set of multi-attribute records, a fixed number of buckets and a two-disk system, arrange the records into the buckets and then store the buckets between the disks in such a way that, over all possible orthogonal range queries (ORQs), the disk access concurrency is maximized. We shall adopt the multiple key hashing (MKH) method for arranging records into buckets and use the disk modulo (DM) allocation method for storing buckets onto disks. Since the DM allocation method has been shown to be superior to any other allocation methods for allocating an MKH file onto a two-disk system for answering ORQs, the real issue is knowing how to determine an optimal way for organizing the records into buckets based upon the MKH concept.

A performance formula that can be used to evaluate the average response time, over all possible ORQs, of an MKH file in a two-disk system using the DM allocation method is first presented. Based upon this formula, it is shown that our design problem is related to a notoriously difficult problem, namely the Prime Number Problem. Then a performance lower bound and an efficient algorithm for designing optimal MKH files in certain cases are presented. It is pointed out that in some cases the optimal MKH file for ORQs in a two-disk system using the DM allocation method is identical to the optimal MKH file for ORQs in a single-disk system and the optimal average response time in a two-disk system is slightly greater than one half of that in a single-disk system.     

水调信息发布系统的设计与实现

在分析水电厂水调信息体系结构和应用需求的基础上,探讨采用现代信息技术构建基于交互式Web、自报/查询短消息、自动收发邮件及自动应答语音等的水调信息发布系统,从而实现多途径水调信息的发布、查询和管理,以解决水电厂单一模式的水调信息发布方式,提升水调信息多途径传递方式,以及信息传递的实时性和可靠性.     

在VB6．0中实现多表综合查询

利用VB6.0Data控件实现了多表任选字段的综合查询,并给出了关键部分的编码,经应用和测试,该方法不仅实用,而且操作方便、反应快捷,较数据库编程简单、灵活。     

Distributed Context Retrieval and Consistency Control in Pervasive Computing

The challenge of saturating all phases of pervasive service provision with context-aware functionality lies in coping with the complexity of maintaining, retrieving and distributing context information. To efficiently represent and query context information a sophisticated modelling scheme should exist. To distribute and synchronise context knowledge in various context repositories across a multitude of administrative domains, streamlined mechanisms are needed. This paper elaborates on an innovative context management framework that has been designed to cope with free-text and location based context retrieval and efficient context consistency control. The proposed framework has been incorporated in a multi-functional pervasive services platform, while most of the mechanisms it employs have been empirically evaluated.     

SQL extension for spatio-temporal data

An SQL extension is formalized for the management of spatio-temporal data, i.e. of spatial data that evolves with respect to time. The extension is dedicated to applications such as topography, cartography, and cadastral systems, hence it considers discrete changes both in space and in time. It is based on the rigid formalization of data types and of SQL constructs. Data types are defined in terms of time and spatial quanta. The SQL constructs are defined in terms of a kernel of few relational algebra operations, composed of the well-known operations of the 1NF model and of two more, Unfold and Fold. In conjunction with previous work, it enables the uniform management of 1NF structures that may contain not only spatio-temporal but also either purely temporal or purely spatial or conventional data. The syntax and semantics of the extension is fully consistent with the {SQL:2003} standard.     

Distributed multi-join query processing in data grids

Query processing in data grids is a difficult issue due to the heterogeneous, unpredictable and volatile behaviors of the grid resources. Applying join operations on remote relations in data grids is a unique and interesting problem. However, to the best of our knowledge, little is done to date on multi-join query processing in data grids. An approach for processing multi-join queries is proposed in this paper. Firstly, a relation-reduction algorithm for reducing the sizes of operand relations is presented in order to minimize data transmission cost among grid nodes. Then, a method for scheduling computer nodes in data grids is devised to parallel process multi-join queries. Thirdly, an innovative method is developed to efficiently execute join operations in a pipeline fashion. Finally, a complete algorithm for processing multi-join queries is given. Analytical and experimental results show the effectiveness and efficiency of the proposed approach.     

J2EE项目中数据访问策略的选择

本文介绍了目前J2EE项目数据访问策略的选择，其中重点描述了O／R映射这种数据访问策略的特点及其适用的最佳条件，它可以帮助我们在项目的开发阶段通过清晰的映射方案构造出高效率的DAO层，为项目的成功打下良好的基础，特别是对于项目的式样变更以及后期维护．这种数据访问策略提供了最大程度上的灵活性。     

逻辑与数据库技术概论

本文对二十余年来人们在逻辑与数据库相结合领域所作的工作进行了归纳总结,并把它们区分为三类:理论和完全关系结构方法,纯理论方法以及理论和不完全关系结构方法。本文简要介绍了这三种方法的基本思想和关键技术,并讨论了它们各自的特点和适用范围。     

不确定移动对象概率Skyline集的查询更新

Skyline查询的研究已从传统的静态Skyline操作延伸到动态的、不确定数据集上的Skyline查询和计算上。研究了移动环境下,查询点位置固定、目标点处于运动状态并且位置不确定情况下的连续概率Skyline计算问题。这个过程中,移动对象与查询对象之间的距离随时间不断变化。移动对象由于其运动状态导致位置无法精确定位,因此移动对象之间的支配关系只能采用概率形式表示,且随时间不断变化。给出了移动对象间的支配概率的定义,以及移动对象Skyline概率的定义,并定义了触发事件来记录对象支配概率发生变化的时刻,实现概率Skyline计算的连续跟踪和动态更新。提出了基于事件触发的连续概率Skyline查询算法(event triggered continuous probabilistic Skyline query for uncertain moving object,U-ECPS),对移动环境下的Skyline集进行连续查询和更新。大量的实验结果验证了U-ECPS算法的有效性。     

Deep Web 研究现状与展望

随着Deep Web数量和规模的快速增长,通过对其发起查询请求以得到存储在后台数据库中的相关信息,日渐成为用户获取信息的主要方式。为了方便用户有效地利用Deep Web中的信息,越来越多的研究者致力于这一领域的研究,重点之一是Deep Web后台数据库的数据集成。由于Deep Web后台数据库存储的主要是文本信息,使得从文本处理角度出发,针对Deep Web中存储的内容进行查询与检索的研究具有十分广阔的应用前景。本文对Deep Web的研究现状进行了较为详细的分析,同时对研究的发展方向进行了展望。