随着计算机技术、网络技术和数据库技术的快速发展，如何存储和管理分布式网络中的海量数据是计算机领域的一个重要问题。分布式计算是一种通过多个计算机协同计算，从而将复杂计算转化为多个小的问题来解决的计算模式,是一种解决海量数据管理的方法。而现代科学的研究方法和测量技术普遍存在误差和噪声，使获取的数据具有不确定性。现有的针对分布式不确定数据查询处理与分析的技术主要采用集中式处理方式，无法适应分布式网络环境，为此本项目紧紧围绕分布式环境下不确定数据的表达模型、索引、查询处理与优化、数据分类与聚类等相关关键技术展开深入研究。相关研究成果将解决分布式环境下不确定数据的查询处理与分析问题，进一步拓宽不确数据的应用领域，具有重要的理论意义与实际应用价值。

With the rapid development of computer technology, network technology and database technology, how to manage and store massive data in the distributed scenarios is an important issue in the computer science. Distributed computing, as a collaborative computing across multiple computers and transforming complex calculations into small problems, is a solution to massive data management. There are widespread noises and errors in modern scientific research methods and measurement techniques, which leads to uncertain data. Most existing methods,processing uncertain data, mainly relies on centralized scenario,and can not adjust to distributed environments. To solve those issues, in this project, we will conduct depth studies on the problems of uncerain data model,index,queries processing, classification and clustering. Related research results will solve the the probelms of the queries processing and analysis in distributed environments over uncartain data, which will broden the application field of uncertain data and have an important theoretical significance and practical application value.