Privacy Protected Spatial Query Processing for Advanced Location Based Services

Due to the popularity of mobile devices (e.g., cell phones, PDAs, etc.), location-based services have become more and more prevalent in recent years. However, users have to reveal their location information to access location-based services with existing service infrastructures. It is possible that adversaries could collect the location information, which in turn invades user’s privacy. There are existing solutions for query processing on spatial networks and mobile user privacy protection in Euclidean space. However there is no solution for solving queries on spatial networks with privacy protection. Therefore, we aim to provide network distance spatial query solutions which can preserve user privacy by utilizing K-anonymity mechanisms. In this paper, we propose an effective location cloaking mechanism based on spatial networks and two novel query algorithms, PSNN and PSRQ, for answering nearest neighbor queries and range queries on spatial networks without revealing private information of the query initiator. We demonstrate the appeal of our technique using extensive simulation results.     

Moving Query Monitoring in Spatial Network Environments

Moving queries over mobile objects are an important type of query in moving object database systems. In recent years, there have been quite a few works in this area. Due to the high frequency in location updates and the expensive cost of continuous query processing, server computation capacity and wireless communication bandwidth are the two limiting factors for large-scale deployment of moving object database systems. Many techniques have been proposed to address the server bottleneck including one using distributed servers. To address both scalability factors, distributed query processing techniques have been considered. These schemes enable moving objects to participate in query processing to substantially reduce the demand on server computation, and wireless communications associated with location updates. Most of these techniques, however, assume an open-space environment. Since Euclidean distance is different from network distance, techniques designed specifically for an open space cannot be easily adapted for a spatial network. In this paper, we present a distributed framework which can answer moving query over moving objects in a spatial network. To illustrate the effectiveness of the proposed framework, we study two representative moving queries, namely, moving range queries and moving k-nearest-neighbor queries. Detailed algorithms and communication mechanisms are presented. The simulation studies indicate that the proposed technique can significantly reduce server workload and wireless communication cost.     

Real-time processing of range-monitoring queries in heterogeneous mobile databases

Unlike conventional range queries, a range-monitoring query is a continuous query. It requires retrieving mobile objects inside a user-defined region and providing continuous updates as the objects move into and out of the region. In this paper, we present an efficient technique for real-time processing of such queries. In our approach, each mobile object is associated with a resident domain, and when an object moves, it monitors its spatial relationship with its resident domain and the monitoring areas inside it. An object reports its location to the server when it crosses over some query boundary or moves out of its resident domain. In the first case, the server updates the affected query results accordingly, while in the second case, the server determines a new resident domain for the object. This distributive approach achieves an accurate and real-time monitoring effect with minimal mobile communication and server processing costs. Our approach also allows a mobile object to negotiate a resident domain based on its computing capability. By having a larger resident domain, a more capable object has less of a chance of moving out of it and having to request a new one. As a result, both communication and server processing costs are reduced. Our comprehensive performance study shows that the proposed technique can be highly scalable in supporting location-based services in a wireless environment that consists of a large number of mobile devices.     

时空道路网络连续最近邻查询的新方法

时空道路网络里连续最近邻查询在时空数据库查询的领域是一个新的重要课题，本文提出一个有效的方法（IE）以处理道路网络里的移动对象的k个最近邻居（k-NN）查询问题。     

Location-dependent queries in mobile contexts: distributed processing using mobile agents

With the current advances of mobile computing technology, we are witnessing an explosion in the development of applications that provide mobile users with a wide range of services. In this paper, we present a system that supports distributed processing of continuous location-dependent queries in mobile environments. The system that we propose presents the following main advantages: 1) it is a general solution for the processing of location-dependent queries in scenarios where not only the users issuing queries, but also other interesting objects can move; 2) it performs an efficient processing of these queries in a continuous way; 3) it is especially well adapted to environments where location data are distributed in a network and processing tasks can be performed in parallel, allowing a high scalability; and 4) it optimizes wireless communications. We use mobile agents to carry the processing tasks wherever they are needed. Thus, agents are in charge of tracking the location of interesting moving objects and refreshing the answer to a query efficiently. We evaluate the usefulness of the presented proposal showing that the system achieves a good precision and scales up well.     

基于用户反馈的关系数据库关键字查询系统

关系数据库中的关键字查询问题使得用户无需掌握查询SQL语言与数据库模式相关知识就可以进行数据库查询,因此受到人们的广泛关注,许多方法和原型被提出。当前流行的关系数据库中关键字查询技术存在较慢的查询时间或者不准确的查询结果。针对这两个问题,提出了一种基于用户反馈的查询方法,根据用户输入的关键字动态地生成一个在数据库中包含关键字的属性所组成的Form表单提供给用户,用户在Form中进行选择并提交,最后,根据用户的选择和数据库模式图进行连接算法并执行SQL获得最终结果。     

能量高效的无线传感器网络时空查询处理算法

 在无线传感器网络环境中,用户经常提交的查询是时空查询,如“获得区域A在某个给定时间段内的感知数据”.由于传感器节点能量十分有限,因此,能量高效的时空查询处理是目前亟需解决的问题.首先指出了现有的时空查询处理算法能量消耗大的原因在于查询协调节点选择不合理.然后给出了理论上最优的查询协调节点的位置及其证明,并基于该理论提出了一类能量高效的传感器网络时空查询算法ECSTA.最后通过实验分析了节点密度和查询区域大小对算法能量消耗的影响.理论和实验结果表明ECSTA算法优于现有的STWin框架下的算法.     

Range and kNN Query Processing for Moving Objects in Grid Model

With the growing popularity of mobile computing devices and wireless communications, managing dynamically changing information about moving objects is becoming feasible. In this paper, we implement a system that manages such information and propose two query algorithms: a range query algorithm and a k nearest neighbor algorithm. The range query algorithm is combined with an efficient filtering technique which determines if a polyline corresponding to the trajectory of a moving object intersects with a given range. We study the performance of the system, which shows that despite the filtering step, for moderately large ranges, the range query algorithm we propose outperforms the algorithm without filtering.     

Challenging Google Search filter bubbles in social and political information: Disconforming evidence from a digital methods case study

This article engages in the debate on supposed online ‘filter bubbles’ by analysing a panel of Google users’ search results on a standardized set of socio-politically themed search queries. In general, the query results appear to be dominated by mainstream media sources, followed at a large distance by civil society and government resources. By means of mixed model regression analyses, with the prominence of different source types in the search results as dependent variables, it was tested whether search results vary across Google Search users. The results indicate that the inclusion of participants as a random effect does not explain variance when controlling for the different query keywords and the time at which the queries were ran. Hence, this study does not support the occurrence of ‘filter bubbles’ in Google Search results in the context of social and political information.     

Optimized management of large-scale data sets stored on tertiary storage systems

We focus on extending RasDaMan's multidimensional query language using a new concept called object framing. With this extension, users no longer are restricted to performing range queries in the shape of multidimensional hypercubes. It can be able to formulate range queries by indicating complex frames. Thus, object framing represents a generalization of geometric operations. A new system, optimized toward high-performance computing, extends the RasDaMan (Raster Data Management) database management system to allow flexible management of multidimensional spatiotemporal data and to reduce tertiary storage access time.     

Spatial Queries in Wireless Broadcast Systems

Owing to the advent of wireless networking and personal digital devices, information systems in the era of mobile computing are expected to be able to handle a tremendous amount of traffic and service requests from the users. Wireless data broadcast, thanks to its high scalability, is particularly suitable for meeting such a challenge. Indexing techniques have been developed for wireless data broadcast systems in order to conserve the scarce power resources in mobile clients. However, most of the previous studies do not take into account the impact of location information of users. In this paper, we address the issues of supporting spatial queries (including window queries and kNN queries) of location-dependent information via wireless data broadcast. A linear index structure based on the Hilbert curve and corresponding search algorithms are proposed to answer spatial queries on air. Experiments are conducted to evaluate the performance of the proposed indexing technique. Results show that the proposed index and its enhancement outperform existing algorithms significantly.     

移动P2P网络中能量有效连续查询研究

在移动P2P网络中一个基本应用问题是访问分布式空间数据库中的数据对象,同时节省电量.文中提出了在移动P2P网络中能量有效连续查询处理（Energy Efficient Continuous Query Processing,EECQP）算法,包括范围查询和k个最近邻居节点查询（k-nearest-neighbor queries, k-NN）.EECQP算法能够提供移动用户找到一个有质量保证的连续查询结果.EECQP算法主要的想法是允许用户与节点合作,持续保存查询结果,而不是总是从头开始处理查询,从而减少通信开销.实验结果表明所提出的EECQP算法对于范围查询和k个最近邻居节点查询在通信开销和QoS保证是能量有效和可扩展的.     

Location-Based Spatial Query Processing with Data Sharing in Wireless Broadcast Environments

Location-based spatial queries (LBSQs) refer to spatial queries whose answers rely on the location of the inquirer. Efficient processing of LBSQs is of critical importance with the ever-increasing deployment and use of mobile technologies. We show that LBSQs have certain unique characteristics that traditional spatial query processing in centralized databases does not address. For example, a significant challenge is presented by wireless broadcasting environments, which have excellent scalability but often exhibit high-latency database access. In this paper, we present a novel query processing technique that, while maintaining high scalability and accuracy, manages to reduce the latency considerably in answering location-based spatial queries. Our approach is based on peer-topeer sharing, which enables us to process queries without delay at a mobile host by using query results cached in its neighboring mobile peers. We demonstrate the feasibility of our approach through a probabilistic analysis, and we illustrate the appeal of our technique through extensive simulation results.     

连续服务请求下基于假位置的用户隐私增强方法

基于假位置的隐私保护方案在为用户提供准确位置服务查询结果的同时,还无需第三方和共享密钥。然而,当用户连续请求位置服务时,由于现有保护单次查询的假位置方案未考虑相邻位置集合间的时空关系,使攻击者能推断出假位置,降低用户的位置隐私保护等级。针对上述问题,采用现有假位置方案生成候选假位置,并通过连续合理性检查和单次隐私增强对其进行筛选,提出一个适用于连续请求的假位置隐私保护增强方法。安全性分析表明,所提方法能保证连续请求中形成的移动路径在时空上不可区分,有效保护连续请求中的用户位置隐私。大量实验表明,所提方法在不增加用户计算开销的同时,与采用的候选假位置生成方案相比,还能提高用户单次查询的隐私保护等级。     

Tracklet clustering for robust multiple object tracking using distance dependent Chinese restaurant processes

To contrive an accurate and efficient strategy for object detection–object track assignment problem, we present a tracklet clustering approach using distance dependent Chinese restaurant processes (ddCRPs), which employ a two-level robust object tracker. The first level is an ordinary tracklet generator that obtains short yet reliable tracklets. In the second level, we cluster the tracklets over time based on color, spatial and temporal attributes, where the nonparametric process of clustering with ddCRPs allows us to maintain an unknown number of objects. Unlike the previously proposed Chinese restaurant processes and Dirichlet process mixture models, our ddCRPs method does not require prescribed complex cluster models to be initialized and updated, and thus, we can cluster complex tracklets by only computing similarities between them. Our comparative evaluations on tracking different object types demonstrate the generality of our approach.     

基于网络Voronoi图的道路网络连续k近邻查询

道路网络中的连续查询是查找在一条路径上满足查询条件的对象。它是空间网络数据库中的一种重要查询类型。现提出了道路网络中基于k阶Voronoi图的连续k近邻查询方法，该查询方法用分枝限界的思想动态地创建局部Voronoi图，降低了查询代价。     

Spatial query processing in road networks for wireless data broadcast

Recently, wireless broadcast environments have attracted significant attention due to its high scalability to broadcast information to a large number of mobile subscribers. It is especially a promising and desirable dissemination method for the heavily loaded environment where a great number of the same type of requests are sent from the users. There have been many studies on processing spatial queries via broadcast model recently. However, not much attention is paid to the spatial queries in road networks on wireless broadcast environments. In this paper, we focus on three common types of spatial queries, namely, k nearest neighbor (kNN) queries, range queries and reverse nearest neighbor (RNN) queries in spatial networks for wireless data broadcast. Specially, we propose a novel index for spatial queries in wireless broadcast environments (ISW). With the reasonable organization and the effectively pre-computed bounds, ISW provides a powerful framework for spatial queries. Furthermore, efficient algorithms are designed to cope with kNN, range and RNN queries separately based on ISW. The search space can be obviously reduced and subsequently the client can download as less as possible data for query processing, which can conserve the energy while not significantly influence the efficiency. The detailed theory analysis of cost model and the experimental results are presented for verifying the efficiency and effectiveness of ISW and our methods.     

Improved SpaceTwist privacy protection method based on anchor optimization algorithm

With location-based services worldwide used,private location data appealed easily in query process which caused serious security problems.So the introduction of SpaceTwist incremental nearest neighbor query algorithm,proposes protection of privacy method combined with improved SpaceTwist location optimization algorithm.The anchor point authentication server added to distributed system structure,user generate a k anonymous area according to their privacy preference and actual environment,using optimization algorithm to generate the anchor point.Forwarding users use the incremental nearest neighbor query throught the anchor point and accurate.Experiments in road network environment with different data sets show that the privacy protection works well in the algorithm,and own high work efficiency.     

基于Voronoi图预划分的LBS位置隐私保护方法

为了解决服务器面临大量用户请求时匿名效率下降的问题,分别提出适用于静态用户和动态用户的协作匿名方法。首先基于Voronoi图划分全局区域,再由中心服务器组织本区域内用户实现协作匿名,由于服务器无需为每个用户单独构造匿名区,降低了服务端的负担;针对查询过程中用户提供真实位置信息带来位置隐私泄露的问题,提出了逆向增量近邻查询算法。用户以固定锚点代替真实位置,向位置服务器逐步获取兴趣点候选集并计算出想要的结果,避免位置隐私直接泄漏的同时获取精准查询结果。该算法同时解决了锚点与用户过近而带来的位置隐私被推断问题。实验表明本方法在有效保护用户位置隐私的同时,具有良好的工作效率。