【作者】 陈楠；

【导师】 陈刚； 董金祥；

【作者基本信息】 浙江大学 ， 计算机科学与技术， 2010， 博士

【摘要】 随着全球定位系统,传感器网络和无线通讯等技术的迅速发展,使得跟踪和记录连续运动物体的位置成为可能。各种应用领域,如交通控制,气象监测,移动计算,基于位置的服务和数字战场等,又进一步推动了时空数据库和移动对象数据库的诞生与发展。近年来,时空数据库和移动对象数据库已经成为了数据库领域一个重要的研究方向,受到了理论界和产业界共同的高度关注。其中,移动对象的索引和查询技术是时空数据库和移动对象数据库的关键性核心技术。然而,目前时空数据库和移动对象数据库尚未实现产业化和实用化,其研究有待进一步深入。而且国内在该领域的研究与国外存在较大差距,因此,对移动对象的索引和查询技术进行研究有着重要的理论意义和广阔的应用前景。本文针对现有研究的不足,对移动对象的索引和查询技术进行了研究,提高了索引的性能和智能化程度,丰富了移动对象的查询类型,能够满足移动对象在实际应用环境下的需求。本文的研究分为移动对象的空间属性管理和各种类型属性管理两个部分展开,在以下一些方面进行了创造性的工作：(1)移动对象索引的时效性研究：在分析实际应用环境的基础上,为解决移动对象索引的时效性问题,本文在移动对象建模的过程中引入“预测性生命周期”的概念,并在索引和查询的过程中进行相应的处理。同时,允许对移动对象的“预测性生命周期”进行不确定性的设置,提出了相应的概率性查询方法,较好地解决了更新频率高差别环境给移动对象查询所带来的时效性影响问题。(2)高查询性能的移动对象索引技术：本文提出了新型的移动对象索引结构By-tree和αBy-tree,能够在保证高效更新操作的同时,显著地提高查询操作的性能。同时,在这些索引结构的基础上,本文研究了时间点区域查询,时间段区域查询,KNN查询和连续性查询等多种类型的查询形式,设计和实现了高效的查询算法。实验证明了这些索引和查询算法在查询的性能上超过了现有的移动对象索引。(3)移动对象索引的自调节框架技术：针对更新操作和查询操作需求动态变化的应用环境,本文设计了具有自管理功能的移动对象索引结构及其在线自调节的框架系统SIFUQMO。该框架能够根据环境的变化,以自学习自调节的方式高效地对更新操作和查询操作的性能进行调节,以达到最佳的平稳的总体性能,并且不打断索引的服务。实验证明了该索引结构和框架系统能够有效地工作,在各种环境下的总体性能优于现有的移动对象索引结构。(4)移动对象的预测性Skyline查询技术：在对移动对象的各种空间属性和非空间属性,动态属性和静态属性进行分析和建模的基础上,本文提出了移动对象的预测性Skyline查询问题,包括了点查询,区域查询和子空间查询三种查询形式。本文还提出了针对移动对象各种类型属性的统一的索引结构,以及解决移动对象预测性Skyline查询的多种算法。实验证明了所提出的算法是高效的,并且比较了其优劣。更多还原

【Abstract】 Advances in global position system, sensor network and wireless communication technologies have made it possible to track and record the positions of moving objects which continuous move with time. Many applications, such as, traffic control, meteorology monitoring, mobile computing, location-based services and digital battle, propote the generation and development of spatial-temporal database and moving object database. In recent years, spatial-temporal database and moving object database have emerged as an active topic in database community, and received considerable attentions from both the research area and industry area. The technique of indexing and querying moving objects is the key challenge that the spatial-temporal database and moving object database face. However, the spatial-temporal database and moving object database have not achieved industrialization and been used in real life, it requries deeper research. In addition, there exists a gap between the oversea research level and that of domestic in this area. Therefore, research on the techniques of indexing and querying moving objects has important academic value and extensive applications.Motivated by this and according to the analysis of disadvantages of the exsiting work, this dissertation studies the techniques of indexing and querying moving objects, aiming at enhancing the performance and intelligentize of moving object indexes, providing new queries of moving objects, and satisfying the requirement in real circumstances of moving objects. This dissertation studies the management of spatial attributes and other kinds of attributes over moving objects, and does some innovative research work as follows:(1) Research on the timeliness of moving object index:based on the analysis of the timeliness problems and influences in the real circumstances of moving objects, and in order to deal with these timeliness problems, this dissertation inctroduces the concept of "prediction life period" to the module of moving objects, and handles it in the process of indexing and querying. In addition, this dissertation allows the "prediction life periods" to be set uncertainly, and introduces corresponding probabilistic queries. In this way, this dissertation solves the timeliness problems and influences brought by moving objects with highly variable update frequencies.(2) Moving object indexes with high query performance:this dissertation proposes new indexes of moving objects, By-tree and aBy-tree, which considerablely improve the query performance, at the same time of ensruing the efficient update performance. Based on the proposed indexes, this dissertation designs and implements efficient query algorithms of range query, KNN query and continuous query. Extensive experiments show that the proposed indexes and query algorithms outperform the exsiting work significantly.(3) Self-tuning index framework of moving objects:motivated by the dynamic circumstances in which the requirement of update operation and query operation varies with time, this dissertation proposes a self-tuning index and a online tuning framework SIFUQMO, which can strike a balance between the performance of queries and updates, thereby achieving good and smooth overall performance for different proportion of updates and queries, without breaking the index service. Extensive experiments show that it is able to work well in these dynamic applications, and its overall performance is better than that of the exsiting work in different circumstances.(4) Predictive skyline queries for moving objects:based on the analysis of the spatial attributes and non-spatial attributes, dynamic attributes and static attributes of moving objects, this dissertation defines and handles the problem of predictive skyline queries for moving objects, including point qury, range query and subspace query. This dissertation proposes a new uniform index structure which indexes all kinds of attributes, and several query algorithms to handle the problem. Extensive experiments show that these algorithms are efficient, and compare their performance.更多还原