Efficient continuous skyline computation

In a number of emerging streaming applications, the data values that are produced have an associated time interval for which they are valid. A useful computation over such streaming data is to produce a continuous and valid skyline summary. Previous work on skyline algorithms have only focused on evaluating skylines over static data sets, and there are no known algorithms for skyline computation in the continuous setting. In this paper, we introduce the continuous time-interval skyline operator, which continuously computes the current skyline over a data stream. We present a new algorithm called LookOut for evaluating such queries efficiently, and empirically demonstrate the scalability of this algorithm. In addition, we also examine the effect of the underlying spatial index structure when evaluating skylines. Whereas previous work on skyline computations have only considered using the R^∗-tree index structure, we show that for skyline computations using an underlying quadtree has significant performance benefits over an R^∗-tree index.     

堰塞湖应急管理三维GIS 系统开发及应用

基于Skyline与GIS技术,利用Microsoft Visual Studio2005平台的C#.Net语言进行二次开发,搭建了堰塞湖应急管理系统平台,该平台较好地与数据库及GIS系统相融合,具有信息服务（增、删、改、查等）、三维展示（空间查看、飞行、地图导航、空间信息查询、三维信息标注、3D模型加载、专题图层的管理等）、空间分析（空间距离测量、面积测量、生成横断面、生成等高线等）以及专业的淹没分析、体积估算、洪水演进、风险评价和灾情评估等功能,为堰塞湖应急管理提供了辅助决策平台.     

基于Skyline的渭河下游洪水演进模拟研究与系统实现

近年来渭河下游洪水问题日益突出。为了减少洪水灾害造成的损失,以Skyline系列软件中的Terra Explorer Pro提供的开发组件进行系统开发,即:将Delf3D软件模拟得到的渭河下游洪水演进过程数据经过处理在系统内进行三维展示,以便为渭河管理人员做出正确的防护措施提供判断依据。     

区域协方差与中值校正融合的天际线检测算法研究

天际线检测在视觉导航、地理图像标注中有着重要的作用。首先采用区域协方差算法对图像进行初分割,确定天际线检测的目标区域;接着根据分析数据集中的样本图片梯度值得到的最优梯度阈值,在初分割的天际线检测目标区域,提出一种循环梯度算法来检测出图像中各列的天际线位置坐标;最后采用中值滤波算法对检测的天际线各点坐标值进行校正,消除可能存在的天际线奇异点,检测出输入图像中的天际线。所提算法在内华达大学机器视觉实验室Web set和Baatz set数据集上进行了测试,实验结果表明:提出的算法能有效地检测出数据集中输入图像的天际线,不需要对图像的边缘信息进行提取,具有良好的有效性和时效性。     

Efficient skyline query processing in wireless sensor networks

How to process a skyline query efficiently has received considerable attention in recent years. A skyline query identifies a set of non-dominated data records in a multidimensional dataset. Whereas most previous studies have resolved this problem in a centralized environment, this work considers it in a distributed sensor network environment. An algorithm, known as Skyline Sensor Algorithm (SkySensor), is presented to efficiently retrieve skyline results from a sensor network. A cluster-based architecture is designed in SkySensor to collect all sensor readings. A pruning method is then proposed to progressively sift out the skyline results from the sensor network. SkySensor avoids the need of collecting data from all sensors in the network, which is an extremely expensive action, when searching for the skyline results. The performance study indicates that SkySensor is highly efficient, and significantly outperforms previous methods in processing skyline queries.     

无线传感器网络中一种近似Skyline 查询处理算法

由于无线传感器网络的能源有限,且在许多应用中Skyline 查询的部分结果即可满足用户需求,提出了一 种近似Skyline 查询处理算法,在满足用户查询需求的前提下最大化地节省能量.该算法仅需无线传感器网络中的部 分传感器节点回传其感知数据即可计算出Skyline 查询的一个近似结果集.由于该算法在处理查询时,每个传感器节 点只需考察自身数据信息即可决定是否回传其感知数据,而无须与其他传感器节点的感知数据进行比较,因此可以 避免大量的网内通信开销,从而节省网络能源.模拟环境下的大量实验结果表明,该算法可以根据用户的应用需求, 节能地处理传感器网络中的近似skyline 查询.     

MapReduce框架下的Skyline云资源选择算法

文中研究了MapReduce框架下的云资源选择算法 。该算法利用概率筛选的方法计算资源节点属于Skyline结果集的概率,并通过阈值过滤来降低MapReduce中的心跳频率,以达到优化网络流量的目的。     

Skyframe: a framework for skyline query processing in peer-to-peer systems

This paper looks at the processing of skyline queries on peer-to-peer (P2P) networks. We propose Skyframe, a framework for efficient skyline query processing in P2P systems, which addresses the challenges of quick response time, low network communication cost and query load balancing among peers. Skyframe consists of two querying methods: one is optimized for network communication while the other focuses on query response time. These methods are different in the way in which the query search space is defined. In particular, the first method uses a high dominating point that has a large dominating region to prune the search space to achieve a low cost in network communication. On the other hand, the second method relaxes the search space in order to allow parallel query processing to speed up query response. Skyframe achieves query load balancing by both query load conscious data space splitting/merging during the join/departure of nodes and dynamic load migration. We further show how to apply Skyframe to both the P2P systems supporting multi-dimensional indexing and the P2P systems supporting single-dimensional indexing. Finally, we have conducted extensive experiments on both real and synthetic data sets over two existing P2P systems: CAN (Ratnasamy in A scalable content-addressable network. In: Proceedings of SIGCOMM Conference, pp. 161–172, 2001) and BATON (Jagadish et al. in A balanced tree structure for peer-to-peer networks. In: Proceedings of VLDB Conference, pp. 661–672, 2005) to evaluate the effectiveness and scalability of Skyframe.     

Adversarial-knowledge dimensions in data privacy

Privacy is an important issue in data publishing. Many organizations distribute non-aggregate personal data for research, and they must take steps to ensure that an adversary cannot predict sensitive information pertaining to individuals with high confidence. This problem is further complicated by the fact that, in addition to the published data, the adversary may also have access to other resources (e.g., public records and social networks relating individuals), which we call adversarial knowledge. A robust privacy framework should allow publishing organizations to analyze data privacy by means of not only data dimensions (data that a publishing organization has), but also adversarial-knowledge dimensions (information not in the data). In this paper, we first describe a general framework for reasoning about privacy in the presence of adversarial knowledge. Within this framework, we propose a novel multidimensional approach to quantifying adversarial knowledge. This approach allows the publishing organization to investigate privacy threats and enforce privacy requirements in the presence of various types and amounts of adversarial knowledge. Our main technical contributions include a multidimensional privacy criterion that is more intuitive and flexible than previous approaches to modeling background knowledge. In addition, we identify an important congregation property of the adversarial-knowledge dimensions. Based on this property, we provide algorithms for measuring disclosure and sanitizing data that improve computational efficiency several orders of magnitude over the best known techniques.     

无人机地面站三维一体化显控软件设计

介绍了无人机地面控制系统软件的组成和工作原理,讨论了一体化显控软件的设计问题,并说明了软件在联试过程中出现的问题和处理方法。该软件利用Skyline 的三维GIS技术,以三维地图为背景设计出无人机地面一体化显控软件,能够实时显示无人机的飞行姿态、飞行轨迹、位置及参数,实现任务航线的编辑、装订与显示,发送飞行控制指令。