TMWSNs中一种确保数据完整性的高能效时空Top-k查询协议

时空Top-k查询是TMWSNs（双层移动无线传感网）中的一类重要查询.在敌对环境中,攻击者易通过捕获TMWSNs中的关键节点来破坏时空Top-k查询的数据完整性.提出一种确保数据完整性的时空Top-k查询处理协议VIP-TQ.该协议利用虚拟化节点技术与绑定加密技术通过构建传感器节点的数据预处理方法、数据存储节点的时空Top-k查询处理方法以及Sink端的数据完整性验证方法来实现TMWSNs中时空Top-k查询的数据完整性保护.理论分析和实验结果显示,VIP-TQ能够以100%的概率侦测出不完整的时空Top-k查询结果,并具有相对已有方案更高的能效性.     

基于层次聚簇的Cube存储结构的研究

数据仓库中的维数据通常都是有层次的,基于维层次路径的聚簇能有效地在物理空间上将关联数据组织到一起,减少查询访问磁盘的次数。而现在的Cube存储结构都关注于Cube操作的计算和存储,忽视了这一特点。论文提出基于维层次聚簇的Cube存储结构HC(HierarchicallyClustered)Cube及相关算法,解决了目前存在的问题。     

存在完整性约束时最小化树模式查询的算法

树模式是查询树型结构数据如XML和LDAP的天然模型。在一个给定的数据库上进行查询,查询的效率很大程度上依赖于查询的大小。因此,在查询前删除查询中的冗余分支,使查询最小化是非常重要的。在树型结构数据库中,存在孩子必需、后代必需和子类3种完整性约束是十分普遍的。针对存在这3种完整性约束的情况,基于扩展的模拟概念提出了一种复杂度为O（n^2）的最小化树模式查询算法（n为树模式查询的节点数）。分析结果表明这个算法的效率要远高于同类算法。     

时空数据库变体最近邻查询问题探讨

最近邻查询在地理信息系统、智能交通系统、多媒体应用以及数据挖掘等领域有着广泛的应用,随着对最近邻查询问题研究的深入,其应用前景和发展空间将更为广阔。针对近几年时空数据库中提出的最近邻查询的多种变体查询问题进行了详细地介绍和分析,总结了解决这些变体最近邻查询问题的有效方法,最后对最近邻查询问题的发展方向进行了展望。     

Texture-based pattern retrieval from image databases

Recent technological advances have made it possible to process and store large amounts of image data. Perhaps the most impressive example is the accumulation of image data in scientific applications such as medical or satellite imagery. However, in order to realize their full potential, tools for efficient extraction of information and for intelligent searches in image databases need to be developed. This paper describes a new approach to image data retrieval which allows queries to be composed of local intensity patterns. The intensity pattern is converted into a feature representation of reduced dimensionality which can be used for searching similar-looking patterns in the database. This representation is obtained by filtering the pattern with a bank of scale and orientation selective filters modeled using Gabor functions. Experimental results are presented which illustrate that the proposed representation preserves the perceptual similarities, and provides a powerful tool for content-based image retrieval.     

分布式数据库中多元连接查询优化的研究

论文对分布式数据库中多元连接查询操作次序的确定问题提出了优化，通过引入收益代价比的概念，提出了一基于贪心算法的选择模型。通过该模型，可以得到理想的连接次序的选取方案。     

基于J2EE平台集群服务的分布式缓存队列模型

集群缓存足提高J2FE(Java 2 Entcrprisc Edition)应用程序可扩展性能的关键技术,但目前J2EE提供的集群技术对于集群缓存的性能处理还存在一定的不足,该文在分析、12EE集群缓存技术的应用基础上,提出一种分布式缓存队列模型,可以有效地解决集群中的可靠性、可扩展性和失败转发等问题。实验表明,采用分布式缓存队列模型能提高集群的访问效率,是一种可行的解决方案。     

通用证书定位打印系统设计

本文介绍证书打印系统实现过程中要处理的几个功能模块和为了改善系统功能要解决的几个问题。     

基于双向双区间标签实现k步可达性查询

近年来,图的可达性查询已经成为一个研究热点。传统的可达性查询算法——GRAIL在处理k步可达性查询时具有较高的查询效率,但不适合处理不同分支顶点之间的k步可达性查询。为了解决上述问题,提出了一种新的双向双区间标签索引,进而实现了RE-GRAIL算法,从而有效解决了k步可达性查询问题。最后,在5个不同特征的数据集上进行实验,并从索引构建时间、索引大小、查询时间、扩展性4个方面进行验证。 实验结果表明,与众多同类算法相比,RE-GRAIL算法具有更好的性能。     

Top-k query evaluation in sensor networks under query response time constraint

Top-k query in a wireless sensor network is to find the k sensor nodes with the highest sensing values. To evaluate the top-k query in such an energy-constrained network poses great challenges, due to the unique characteristics imposed on its sensors. Existing solutions for top-k query in the literature mainly focused on energy efficiency but little attention has been paid to the query response time and its effect on the network lifetime. In this paper we address the query response time and its effect on the network lifetime through the study of the top-k query problem in sensor networks with the response time constraint. We aim at finding an energy-efficient routing tree and evaluating top-k queries on the tree such that the network lifetime is significantly prolonged, provided that the query response time constraint is met too. To do so, we first present a cost model of energy consumption for answering top-k queries and introduce the query response time definition. We then propose a novel joint query optimization framework, which consists of finding a routing tree in the network and devising a filter-based evaluation algorithm for top-k query evaluation on the tree. We finally conduct extensive experiments by simulation to evaluate the performance of the proposed algorithms, in terms of the total energy consumption, the maximum energy consumption among nodes, the query response time, and the network lifetime. The experimental results showed that there is a non-trivial tradeoff between the query response time and the network lifetime, and the joint query optimization framework can prolong the network lifetime significantly under a specified query response time constraint.