查询是计算机科学的基本问题，存在于目前几乎所有的计算机应用领域；特别在大数据时代，高效的查询处理与优化技术显得尤为重要。现有的聚合k最近邻查询及变体主要针对欧氏空间下的静态/移动对象，并利用几何特性修剪查找空间；但这些几何特性不适用于路网环境，且在许多实际应用（如智能交通等）中，路网下的移动对象查询处理更具有现实意义。本项目拟在现有的聚合k最近邻查询及变体处理和路网下的移动对象查询处理的研究基础上，结合路网的特性（如路网距离计算复杂、实时性等），以最小化更新代价与通讯代价为优化目标，展开一系列能满足实际应用需求的路网下连续聚合k最近邻查询及变体处理研究，重点研究路网下的连续聚合k最近邻查询、连续聚合k最近邻监控、连续灵活聚合k最近邻查询、以及连续聚合k最远邻查询；设计、实现和评价各自查询处理算法，并开发相应的展示平台；力争在相关理论与方法上取得突破，为今后的实际应用奠定坚实基础。

Query is a fundamental problem in computer science, and exists in almost all computer applications; especially in the era of big data, efficient query processing and optimization technology is particularly important. Most existing aggregate k nearest neighbor queries focus on static/moving objects in the Euclidean space, and utilize geometric characteristics to prune the search space. However, these geometric properties do not apply to the road network, and in many practical applications (e.g., intelligent transportation, etc.), the query processing for moving objects in the road network is more realistic. This project aims at studying the continuous aggregate k near neighbor query and its variants in road networks, based on the existing research on aggregate k nearest neighbor search and its variants as well as moving objects queries in road networks. It considers the properties of the road network (e.g., the complex distance computation under the road network, real time, etc.), and aims to minimize the update and communication costs. The project mainly investigates a suite of query processing problems, including continuous aggregate k nearest neighbor query, continuous aggregate k nearest neighbor monitoring, continuous flexible aggregate k nearest neighbor retrieval, and continuous aggregate k farthest neighbor search, in the context of road networks; designs, implements, and evaluates every query processing algorithm, and develops its corresponding display platform/demo; and strives to achieve a breakthrough in relevant theories and technologies in order to lay a solid foundation for future practical applications.