6 Access Methods and Query Processing Techniques

The performance of a database management system (DBMS) is fundamentally dependent on the access methods and query processing techniques available to the system. Traditionally, relational DBMSs have relied on well-known access methods, such as the ubiquitous B +-tree, hashing with chaining, and, in som

A spatial data handling system for retrieval of images by unrestricted regions of user interest

The Intelligent Data Management (IDM) project at NASA/Goddard Space Flight Center has prototyped an Intelligent Information Fusion System (IIFS), which automatically ingests metadata from remote sensor observations into a large catalog which is directly queryable by end-users. The greatest challenge in the implementation of this catalog was supporting spatially-driven searches, where the user has a possible complex region of interest and wishes to recover those images that overlap all or simply a part of that region. A spatial data management system is described, which is capable of storing and retrieving records of image data regardless of their source. This system was designed and implemented as part of the IIFS catalog. A new data structure, called a hypercylinder, is central to the design. The hypercylinder is specifically tailored for data distributed over the surface of a sphere, such as satellite observations of the Earth or space. Operations on the hypercylinder are regulated by two expert systems. The first governs the ingest of new metadata records, and maintains the efficiency of the data structure as it grows. The second translates, plans, and executes users' spatial queries, performing incremental optimization as partial query results are returned

Efficient top K temporal spatial keyword search

Massive amount of data that are geo-tagged and associated with text information are being generated at an unprecedented scale in many emerging applications such as location based services and social networks. Due to their importance, a large body of work has focused on efficiently computing various spatial keyword queries. In this paper, we study the top-k temporal spatial keyword query which considers three important constraints during the search including time, spatial proximity and textual relevance. A novel index structure, namely SSG-tree, to efficiently insert/delete spatio-temporal web objects with high rates. Base on SSG-tree an efficient algorithm is developed to support top-k temporal spatial keyword query. We show via extensive experimentation with real spatial databases that our method has increased performance over alternate techniques

Efficient Coding Tree Unit (CTU) Decision Method for Scalable High-Efficiency Video Coding (SHVC) Encoder

High-efficiency video coding (HEVC or H.265) is the latest video compression standard developed by the joint collaborative team on video coding (JCT-VC), finalized in 2013. HEVC can achieve an average bit rate decrease of 50% in comparison with H.264/AVC while still maintaining video quality. To upgrade the HEVC used in heterogeneous access networks, the JVT-VC has been approved scalable extension of HEVC (SHVC) in July 2014. The SHVC can achieve the highest coding efficiency but requires a very high computational complexity such that its real-time application is limited. To reduce the encoding complexity of SHVC, in this chapter, we employ the temporal-spatial and inter-layer correlations between base layer (BL) and enhancement layer (EL) to predict the best quadtree of coding tree unit (CTU) for quality SHVC. Due to exist a high correlation between layers, we utilize the coded information from the CTU quadtree in BL, including inter-layer intra/residual prediction and inter-layer motion parameter prediction, to predict the CTU quadtree in EL. Therefore, we develop an efficient CTU decision method by combing temporal-spatial searching order algorithm (TSSOA) in BL and a fast inter-layer searching algorithm (FILSA) in EL to speed up the encoding process of SHVC. The simulation results show that the proposed efficient CTU decision method can achieve an average time improving ratio (TIR) about 52–78% and 47–69% for low delay (LD) and random access (RA) configurations, respectively. It is clear that the proposed method can efficiently reduce the computational complexity of SHVC encoder with negligible loss of coding efficiency with various types of video sequences

Distributed Spatial-Keyword kNN Monitoring for Location-aware Pub/Sub

Recent applications employ publish/subscribe (Pub/Sub) systems so that publishers can easily receive attentions of customers and subscribers can monitor useful information generated by publishers. Due to the prevalence of smart devices and social networking services, a large number of objects that contain both spatial and keyword information have been generated continuously, and the number of subscribers also continues to increase. This poses a challenge to Pub/Sub systems: they need to continuously extract useful information from massive objects for each subscriber in real time. In this paper, we address the problem of k nearest neighbor monitoring on a spatial-keyword data stream for a large number of subscriptions. To scale well to massive objects and subscriptions, we propose a distributed solution. Given m workers, we divide a set of subscriptions into m disjoint subsets based on a cost model so that each worker has almost the same kNN-update cost, to maintain load balancing. We allow an arbitrary approach to updating kNN of each subscription, so with a suitable in-memory index, our solution can accelerate update efficiency by pruning irrelevant subscriptions for a given new object. We conduct experiments on real datasets, and the results demonstrate the efficiency and scalability of our solution

Efficient Point Clustering for Visualization

The visualization of large spatial point data sets constitutes a problem with respect to runtime and quality. A visualization of raw data often leads to occlusion and clutter and thus a loss of information. Furthermore, particularly mobile devices have problems in displaying millions of data items. Often, thinning via sampling is not the optimal choice because users want to see distributional patterns, cardinalities and outliers. In particular for visual analytics, an aggregation of this type of data is very valuable for providing an interactive user experience. This thesis defines the problem of visual point clustering that leads to proportional circle maps. It furthermore introduces a set of quality measures that assess different aspects of resulting circle representations. The Circle Merging Quadtree constitutes a novel and efficient method to produce visual point clusterings via aggregation. It is able to outperform comparable methods in terms of runtime and also by evaluating it with the aforementioned quality measures. Moreover, the introduction of a preprocessing step leads to further substantial performance improvements and a guaranteed stability of the Circle Merging Quadtree. This thesis furthermore addresses the incorporation of miscellaneous attributes into the aggregation. It discusses means to provide statistical values for numerical and textual attributes that are suitable for side-views such as plots and data tables. The incorporation of multiple data sets or data sets that contain class attributes poses another problem for aggregation and visualization. This thesis provides methods for extending the Circle Merging Quadtree to output pie chart maps or maps that contain circle packings. For the latter variant, this thesis provides results of a user study that investigates the methods and the introduced quality criteria. In the context of providing methods for interactive data visualization, this thesis finally presents the VAT System, where VAT stands for visualization, analysis and transformation. This system constitutes an exploratory geographical information system that implements principles of visual analytics for working with spatio-temporal data. This thesis details on the user interface concept for facilitating exploratory analysis and provides the results of two user studies that assess the approach