Spatial Indexing for Video Databases

Spatial reasoning techniques based on 2D string systems have been successfully applied to indexing pictorial databases. We demonstrate how similar techniques may be extended to represent video sequences, and how this representation may be compressed. Query schemes for both single frame queries, and full subsequence queries are presented. The strength of these query schemes is that the query process does not require the expansion of the compressed notation during query evaluation.     

Efficient Continuous Skyline Query Processing Scheme over Large Dynamic Data Sets

Performing continuous skyline queries of dynamic data sets is now more challenging as the sizes of data sets increase and as they become more volatile due to the increase in dynamic updates. Although previous work proposed support for such queries, their efficiency was restricted to small data sets or uniformly distributed data sets. In a production database with many concurrent queries, the execution of continuous skyline queries impacts query performance due to update requirements to acquire exclusive locks, possibly blocking other query threads. Thus, the computational costs increase. In order to minimize computational requirements, we propose a method based on a multi‐layer grid structure. First, relational data object, elements of an initial data set, are processed to obtain the corresponding multi‐layer grid structure and the skyline influence regions over the data. Then, the dynamic data are processed only when they are identified within the skyline influence regions. Therefore, a large amount of computation can be pruned by adopting the proposed multi‐layer grid structure. Using a variety of datasets, the performance evaluation confirms the efficiency of the proposed method.     

Continuous Monitoring of Spatial Queries in Wireless Broadcast Environments

Wireless data broadcast is a promising technique for information dissemination that leverages the computational capabilities of the mobile devices in order to enhance the scalability of the system. Under this environment, the data are continuously broadcast by the server, interleaved with some indexing information for query processing. Clients may then tune in the broadcast channel and process their queries locally without contacting the server. Previous work on spatial query processing for wireless broadcast systems has only considered snapshot queries over static data. In this paper, we propose an air indexing framework that 1) outperforms the existing (i.e., snapshot) techniques in terms of energy consumption while achieving low access latency and 2) constitutes the first method supporting efficient processing of continuous spatial queries over moving objects.     

CBFM：支持属性删减的布鲁姆过滤器矩阵多维元素查询算法

为了提升多维元素成员查询的灵活性和准确率,提出了一种新型索引结构CBFM(cutted Bloom filter matrix)。该索引方法通过独立属性布鲁姆过滤器笛卡尔乘积构建位矩阵,支持任意属性组合的多维元素成员查询,同时支持属性组合按需删减和属性加权,极大地提升内存空间利用率,降低查询误判率。理论分析证明相比于BFM(Bloom filter matrix)索引方法,CBFM具有更高的内存利用率。仿真实验表明,在分配内存相同的情况下,CBFM方法相比于其他方法,具有最低的查询误判率,特别在内存受限场景下,CBFM相比于BFM方法,查询误判率最大降低3个数量级,极大地提升了多维元素成员查询的准确率。     

基于p-稳定分布局部敏感哈希地址的鲁棒音频检索方法

局部敏感哈希（Local-Sensitive Hashing, LSH）索引方法具有快速的优点,对数据规模具有子线性的时间复杂度。但是该方法对待检集合的选取要求苛刻,容易将带噪数据排除在待检集合之外,导致检索精度下降。针对这一缺点,本文从p-稳定分布理论出发,分析噪声对数据的局部敏感哈希地址的影响,并利用数据的哈希地址受噪声影响在原始地址附近偏移的特性,提出一种鲁棒的音频检索方法。该方法将LSH地址直接作为相似性判定的特征,并通过扩大检索范围来提高噪声鲁棒性。实验表明,所提方法在噪声鲁棒性方面优于LSH索引方法;进一步引入向量搜索算法优化后,其检索速度也可达到与LSH索引方法接近的水平。      

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.     

基于分组机制的位仲裁查询树防碰撞算法

提出了一种基于分组机制的位仲裁查询树(GBAQT, bit arbitration query tree based on grouping mechanism)算法。该算法根据标签ID自身特征分组,采用3位仲裁位来取代传统1位仲裁识别标签的方式,通过碰撞位信息得到传输数据,从而能避免一些空闲时隙。算法的性能分析和仿真结果表明,GBAQT防碰撞算法具有较少的总时隙数,系统效率和时隙利用率也明显优于其他算法。     

Embedded lattices tree: An efficient indexing scheme for content based retrieval on image databases

One of the challenges in the development of a content-based multimedia indexing and retrieval application is to achieve an efficient indexing scheme. To retrieve a particular image from a large scale image database, users can be frustrated by the long query times. Conventional indexing structures cannot usually cope with the presence of a large amount of feature vectors in high-dimensional space. This paper addresses such problems and presents a novel indexing technique, the embedded lattices tree, which is designed to bring an effective solution especially for realizing the trade off between the retrieval speed up and precision.The embedded lattices tree is based on a lattice vector quantization algorithm that divides the feature vectors progressively into smaller partitions using a finer scaling factor. The efficiency of the similarity queries is significantly improved by using the hierarchy and the good algebraic and geometric properties of the lattice. Furthermore, the dimensionality reduction that we perform on the feature vectors, translating from an upper level to a lower one of the embedded tree, reduces the complexity of measuring similarity between feature vectors. In addition, it enhances the performance on nearest neighbor queries especially for high dimensions. Our experimental results show that the retrieval speed is significantly improved and the indexing structure shows no sign of degradations when the database size is increased.     

使用区间路径处理XML查询

近年来,在XML查询处理方法中发表了一些基于节点流栈连接的高效的分枝连接算法。然而,这些算法普遍存在这样的问题:由于它们必须扫描查询中出现的每一个元素对应的节点流,当XML节点数量很大时,查询处理的输入代价很大,效率变得低下。为了解决这个问题,提出了一个新型的标记法记为区间路径,不同于节点流的区间标记法,区间路径可以把具有相同路径的节点集索引到一个集合中。继而提出了分枝点连接算法用于XML查询处理。同基于节点流栈的分枝连接算法相比,该算法有以下优势:节点集的祖先信息直接位于区间路径中;只有和查询结果相关的节点集会被扫描到,大大降低了输入代价;支持查询通配符;对于类型为根路径的查询,只需一次输入操作代价完成查询处理。实验结果表面该算法在输入代价,执行时间和延展性方面都优于基于节点流的分枝连接算法。     

Online Data Gathering for Maximizing Network Lifetime in Sensor Networks

Energy-constrained sensor networks have been deployed widely for monitoring and surveillance purposes. Data gathering in such networks is often a prevalent operation. Since sensors have significant power constraints (battery life), energy efficient methods must be employed for data gathering to prolong network lifetime. We consider an online data gathering problem in sensor networks, which is stated as follows: assume that there is a sequence of data gathering queries, which arrive one by one. To respond to each query as it arrives, the system builds a routing tree for it. Within the tree, the volume of the data transmitted by each internal node depends on not only the volume of sensed data by the node itself, but also the volume of data received from its children. The objective is to maximize the network lifetime without any knowledge of future query arrivals and generation rates. In other words, the objective is to maximize the number of data gathering queries answered until the first node in the network fails. For the problem of concern, in this paper, we first present a generic cost model of energy consumption for data gathering queries if a routing tree is used for the query evaluation. We then show the problem to be NP-complete and propose several heuristic algorithms for it. We finally conduct experiments by simulation to evaluate the performance of the proposed algorithms in terms of network lifetime delivered. The experimental results show that, among the proposed algorithms, one algorithm that takes into account both the residual energy and the volume of data at each sensor node significantly outperforms the others     

Deep multi-query video retrieval

Video retrieval methods have been developed for a single query. Multi-query video retrieval problem has not been investigated yet. In this study, an efficient and fast multi-query video retrieval framework is developed. Query videos are assumed to be related to more than one semantic. The framework supports an arbitrary number of video queries. The method is built upon using binary video hash codes. As a result, it is fast and requires a lower storage space. Database and query hash codes are generated by a deep hashing method that not only generates hash codes but also predicts query labels when they are chosen outside the database. The retrieval is based on the Pareto front multi-objective optimization method. Re-ranking performed on the retrieved videos by using non-binary deep features increases the retrieval accuracy considerably. Simulations carried out on two multi-label video databases show that the proposed method is efficient and fast in terms of retrieval accuracy and time.     

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.     

Models for motion-based video indexing and retrieval

With the rapid proliferation of multimedia applications that require video data management, it is becoming more desirable to provide proper video data indexing techniques capable of representing the rich semantics in video data. In real-time applications, the need for efficient query processing is another reason for the use of such techniques. We present models that use the object motion information in order to characterize the events to allow subsequent retrieval. Algorithms for different spatiotemporal search cases in terms of spatial and temporal translation and scale invariance have been developed using various signal and image processing techniques. We have developed a prototype video search engine, PICTURESQUE (pictorial information and content transformation unified retrieval engine for spatiotemporal queries) to verify the proposed methods. Development of such technology will enable true multimedia search engines that will enable indexing and searching of the digital video data based on its true content.     

A Semantic Service Discovery Network for Large‐Scale Ubiquitous Computing Environments

This paper presents an efficient semantic service discovery scheme called UbiSearch for a large‐scale ubiquitous computing environment. A semantic service discovery network in the semantic vector space is proposed where services that are semantically close to each other are mapped to nearby positions so that the similar services are registered in a cluster of resolvers. Using this mapping technique, the search space for a query is efficiently confined within a minimized cluster region while maintaining high accuracy in comparison to the centralized scheme. The proposed semantic service discovery network provides a number of novel features to evenly distribute service indexes to the resolvers and reduce the number of resolvers to visit. Our simulation study shows that UbiSearch provides good semantic searchability as compared to the centralized indexing system. At the same time, it supports scalable semantic queries with low communication overhead, balanced load distribution among resolvers for service registration and query processing, and personalized semantic matching.     

Energy-efficient skyline query optimization in wireless sensor networks

With the deployment of wireless sensor networks (WSNs) for environmental monitoring and event surveillance, WSNs can be treated as virtual databases to respond to user queries. It thus becomes more urgent that such databases are able to support complicated queries like skyline queries. Skyline query which is one of popular queries for multi-criteria decision making has received much attention in the past several years. In this paper we study skyline query optimization and maintenance in WSNs. Specifically, we first consider skyline query evaluation on a snapshot dataset, by devising two algorithms for finding skyline points progressively without examining the entire dataset. Two key strategies are adopted: One is to partition the dataset into several disjoint subsets and produce the skyline points in each subset progressively. Another is to employ a global filter that consists of some skyline points in the processed subsets to filter out unlikely skyline points from the rest of unexamined subsets. We then consider the query maintenance issue by proposing an algorithm for incremental maintenance of the skyline in a streaming dataset. A novel maintenance mechanism is proposed, which is able to identify which skyline points from past skylines to be the global filter and determine when the global filter is broadcast. We finally conduct extensive experiments by simulations to evaluate the performance of the proposed algorithms on both synthetic and real sensing datasets, and the experimental results demonstrate that the proposed algorithms significantly outperform existing algorithms in terms of network lifetime prolongation.     

Effective Management of High Rate Spatio-Temporal Queries in Wireless Sensor Networks

Handling high rate queries have always posed a challenge in wireless sensor networks (WSNs) owing to their resource constrained nature. This paper proposes a scheme that performs centralized and distributed optimization to improve the scalability of the high rate spatio-temporal queries in WSNs. Queries are optimized centrally based on multiple criteria such as spatial topological relationships, temporal and attribute correlations. An energy efficient load balanced clustered tree routing based on minimum bounding rectangle spatial indexing scheme is employed to aid the in-network optimization of queries. Two algorithms have been proposed to carry out a centralized and distributed optimization that works adaptively on queries switching between optimal and sub-optimal modes to handle multiple concurrent queries reliably. Simulation results show that the proposed scheme is highly scalable for large scale spatio-temporal queries and also has the added advantage of minimizing the energy consumption due to query and data transmission.     

基于有向无环图的区间覆盖率求解算法

给定一个有向无环图,回答可达性查询是图的基本操作之一.虽然很多方法使用树区间来加速可达查询的处理速度,但并不明确使用多少个区间比较合适.本文提出一种快速计算区间覆盖率的算法,该方法通过使用有效的剪枝策略来支持高效的覆盖率计算.基于所得到的区间覆盖率,可针对不同数据图确定合适的区间个数,以便在加速查询处理的同时,降低索引...     

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.     

On Searching Continuous k Nearest Neighbors in Wireless Data Broadcast Systems

A continuous nearest neighbor (CNN) search, which retrieves the nearest neighbors corresponding to every point in a given query line segment, is important for location-based services such as vehicular navigation and tourist guides. It is infeasible to answer a CNN search by issuing a traditional nearest neighbor query at every point of the line segment due to the large number of queries generated and the overhead on bandwidth. Algorithms have been proposed recently to support CNN search in the traditional client- server systems but not in the environment of wireless data broadcast, where uplink communication channels from mobile devices to the server are not available. In this paper, we develop a generalized search algorithm for continuous k-nearest neighbors based on Hilbert Curve Index in wireless data broadcast systems. A performance evaluation is conducted to compare the proposed search algorithms with an algorithm based on R-tree Air Index. The result shows that the Hilbert Curve Index-based algorithm is more energy efficient than the R-tree-based algorithm.     

高维数据空间索引的研究

讨论了高维数据空间索引的基本结构，建树算法以及典型的查询方式，重点对几种有代表性的索引方法，如K－D－Tree,R-Tree,R-Tree,X-Tree,TV-Tree,Hillert R-Tree在节点形状，重叠，插入原则，分裂原则，再插入等方面进行了比较研究。