嵌入式移动数据库系统中的数据查询

数据库技术一直在随着计算的发展而不断进步,凡是有数据的地方,就要用到数据库来协助管理数据。本文介绍了位置相关查询优化和数据广播两种普遍用于移动数据库查询的方法,并结合移动数据库中的缓存技术,提出了嵌入式移动数据库的查询优化方法。     

基于IIPP的数字图书馆的主动信息服务

使用包含各种多媒体数据的信息“推送”和“拉取”技术显得越来越重要。在“推送”和“拉取”的基础上再融入人工智能、知识发现、数据库技术等等,就形成了智能信息推拉技术。这项技术是当前因特网、数据库系统以及数字电视广播的一个热点。这种技术的引入,可以提高服务的智能水平,从而从根本上解决“推送”“拉取”技术应用过程中遇到的问题。     

嵌入式移动数据库查询优化策略研究

随着通信技术和网络技术的发展,嵌入式移动数据库正成为数据库领域的一个新的研究方向.针对嵌入式移动数据库中频繁断接性、低带宽等特性,介绍了数据广播和客户缓存两种用于嵌入式移动数据库中处理断接操作的方法,提出了基于语义的查询优化策略.研究表明,该策略能够提高移动数据库查询的效率.     

嵌入式移动数据库查询优化策略研究

随着通信技术和网络技术的发展,嵌入式移动数据库正成为数据库领域的一个新的研究方向。针对嵌入式移动数据库中频繁断接性、低带宽等特性,介绍了数据广播和客户缓存两种用于嵌入式移动数据库中处理断接操作的方法,提出了基于语义的查询优化策略。研究表明,该策略能够提高移动数据库查询的效率。     

移动数据库管理系统的特性

移动DBMS(数据库管理系统)的计算环境是传统分布式DBMS的扩展．可以被看作是客户端与固定服务器结点动态连接的分布式系统。     

基于大数据的数字图书馆信息服务研究

在大数据时代,数字信息化服务被应用于社会的各个领域.从海量的数据信息中获取准确并且有用的信息,是大数据时代人们关注的重点问题.数字图书馆是人们获取信息服务重要渠道,把大数据技术应用于数字图书馆信息服务中是科技发展的必然趋势.针对大数据技术和数字图书馆的特点进行了阐述,结合数字图书馆的信息服务体系和模式特点,对基于大数据的数字图书馆信息服务进行了分析和研究.     

在3G时代下我国数字图书馆移动信息服务的发展研究

本文介绍了在新的时代下,数字图书馆所面临的机遇和挑战,在众多且需求各异的信息人群面前,如何为其提供全面、优质的服务是图书馆管理者必须面对并且急需解决的问题。3G时代是一个信息剧增,同时也是信息需求剧增的时代,图书馆作为提供信息、知识的专门场所,应适应时代要求,秉着以人为本的理念为广大用户提供优质、快捷的服务。     

试论移动数字图书馆现状及其发展策略

信息是现代社会的战略资源,是市场竞争的重要手段。移动数字图书馆是依托无线移动网络、国际互联网以及多媒体技术,借助各种移动设备,如手机、掌上电脑、笔记本等,人们可以灵活方便的进行图书信息查询、浏览,获取信息知识的一种崭新信息服务系统。移动数字图书馆是数字图书馆功能的延伸,也是科学技术发展必然的产物。本文主要分析了,现阶段我国移动数学图书馆的现状及其发展策略。     

移动数据库中数据更新与广播的并发控制

移动数据库系统中数据更新与数据广播并发处理,导致移动客户读取的数据可能不一致,本文分析了在移动数据库中数据更新与数据广播并发处理中可能出现的三类数据冲突,并提出了基于UFBL0原则的并发控制策略来解决上述的问题。该策略具有较好的独立性,对服务器和移动客户机的影响都较小,并且可以较大限度地提高广播给用户的数据项当前性。     

Broadcasting and querying multi-dimensional index trees in a multi-channel environment

The continuous broadcast of data together with an index structure is an effective way of disseminating data in a wireless, mobile environment. The availability of an index allows a reduction in the tuning time and thus leads to lower power consumption for a mobile client. This paper considers scheduling index trees in multiple channel environments in which a mobile client can tune into a specified channel at one time instance. Let T be an n-node index tree of height h representing multi-dimensional index structure to be broadcast in a c  -channel environment. We describe two algorithms generating broadcast schedules that differ in the worst-case performance experienced by a client executing a general query. A general query is a query which results in an arbitrary traversal of the index tree, compared to a simple query in which a single path is traversed. Our first algorithm schedules any tree using minimum cycle length and it executes a simple query within one cycle. However, a general query may require O(hc)$O(\mathit{hc})$ cycles and thus result in a high latency. The second algorithm generates a schedule of minimum cycle length on which a general query takes at most O(c)$O(c)$ cycles. For some queries this is the best possible latency.     

Efficient query execution on broadcasted index tree structures

The continuous broadcast of data together with an index structure is an effective way of disseminating data in a wireless mobile environment. The index allows a mobile client to tune in only when relevant data is available on the channel and leads to reduced power consumption for the clients. This paper investigates the execution of queries on broadcasted index trees when query execution corresponds to a partial traversal of the tree. Queries exhibiting this behavior include range queries and nearest neighbor queries. We present two broadcast schedules for index trees and two query algorithms executed by mobile clients. Our solutions simultaneously minimize tuning time and latency and adapt to the client’s available memory. Experimental results using real and synthetic data compare results for a broadcast with node repetition to one without node repetition and they show how a priority-based data management can help reduce tuning time and latency.     

Query optimization for broadcast database

In a mobile environment, the broadcast paradigm has been recognized as an effective way to disseminate frequently requested information to multiple ‘mobile clients’. In this paper, we show that to query the broadcast database efficiently, database items must be organized over the broadcast channel in a meaningful way, reflecting the semantics of the database being broadcast. We define, for the first time, a cost model called the Semantic Ordering Model for identifying the optimal organization of database items over the broadcast channel. Experimental results are also delineated to illustrate the feasibility of our cost model, using relational and object-oriented databases as examples.     

The CQL continuous query language: semantic foundations and query execution

CQL, a continuous query language, is supported by the STREAM prototype data stream management system (DSMS) at Stanford. CQL is an expressive SQL-based declarative language for registering continuous queries against streams and stored relations. We begin by presenting an abstract semantics that relies only on “black-box” mappings among streams and relations. From these mappings we define a precise and general interpretation for continuous queries. CQL is an instantiation of our abstract semantics using SQL to map from relations to relations, window specifications derived from SQL-99 to map from streams to relations, and three new operators to map from relations to streams. Most of the CQL language is operational in the STREAM system. We present the structure of CQL's query execution plans as well as details of the most important components: operators, interoperator queues, synopses, and sharing of components among multiple operators and queries. Examples throughout the paper are drawn from the Linear Road benchmark recently proposed for DSMSs. We also curate a public repository of data stream applications that includes a wide variety of queries expressed in CQL. The relative ease of capturing these applications in CQL is one indicator that the language contains an appropriate set of constructs for data stream processing. Edited by M. Franklin     

移动数据库中数据广播与数据更新并发执行的数据一致性维护

移动数据库系统中数据更新与数据广播并发处理,导致移动客户读取的数据可能不一致。文章分析了并发处理中的数据冲突并提出了基于ECA原则的并发控制策略。     

基于移动Agent的查询区域管理

介绍了一种移动计算环境下基于移动Agent的查询请求处理方法一基于区域管理的查询管理模式（ZQTM），并在此基础上提出了在该模式下的查询区域管理方法及移动查询结果的特殊获取方法。     

数字图书馆中查询结果的自动分类算法的设计

文章针对数字图书馆查询时返回过多的结果提出了对查询结果进行自动分类的算法,以便提高查询的速度和准确性。     

移动实时环境下一种改进的广播调度算法

在网络带宽不对称的移动实时环境中,数据广播是一种有效的数据访问方式。针对这种网络特性,分析了现今已经存在的某些广播调度算法。针对UFO算法,分别提出了SBS算法和CRS算法,它们从服务器、移动客户端两个方面进行了改进。两种算法可以根据给定的数据项访问概率分布,自动生成广播调度。通过理论分析和实验结果表明,该算法不会产生事务重启,并且可以有效减少数据的访问时间,使用户访问数据广播的平均等待时间最小。