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3rd ACM SIGspatial International Workshop on GeoStreaming (IWGS)

作者： Stenzer, Alexander Freitag, Burkhard Univ Passau Informat Management D-94030 Passau Germany

ISBN: (纸本)9781450316958

The MonArch Digital Archiving System is a metadata repository designed for the storage, management and retrieval of digital documents and digital information in general. In contrast to conventional document management systems, the MonArch System uses semantical technologies to improve content descriptions. Furthermore, GIS functionality and navigation maps allow for the geo-referencing of documents and thus for visually locating and selecting the archived content. Together, the semantical and spatial markups allow for powerful queries that are fully adaptable to the needs of a wide variety of scenarios. In a federated network of archives each repository could benefit from the accumulated but distributed information. To capitalise on this advantage, coping with the inevitable disparities of the description schemata is one of the major challenges. Therefore, a distributed query facility must be able to bridge different schemata as well as the particular domain and purpose of each repository. In this paper an approach to query relaxation in the application domain of digital preservation of built heritage is presented. The proposed method is based on similarity which in turn can be inferred from the structural properties and a type-based classification of the descriptive metadata attached to the stored objects. The resulting approach reduces signi fi cantly the otherwise necessary manual schema integration work which tends to rely on domain experts.

关键词： query relaxation spatial query processing

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spatial querying of mineral resources using PostGIS 2

Spatial querying of mineral resources using PostGIS

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2nd International Conference on Advancements in Computational Sciences (ICACS)

作者： Chaudhry, Natalia Yousaf, Muhammad Murtaza Univ Punjab Punjab Univ Coll Informat Technol Lahore Pakistan

ISBN: (纸本)9789699721014

Mineral resources are precious resources with limited reserves. For a reasonable development of national economy, intelligent usage and management of these resources is very important. GIS has been employing specialized softwares and database technology to facilitate the storage and management of spatial data related to mineral resources. spatial query processing has been gaining great popularity in this regard. Many spatial databases have been designed to allow efficient querying of spatial data. PostGIS is one of the most powerful databases to handle spatial data processing. In this paper, we investigated the competence of PostGIS for spatial querying of data related to mineral resources. The standard spatial querying methods are discussed with their application in PostGIS. The level of support provided by PostGIS in processing spatial mineral resources data is highlighted. The challenges in modeling spatial mineral data in PostGIS are also identified.

关键词： GIS spatial query processing PostGIS

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Architecting aQu ery Compiler for spatial Workloads 20

Architecting aQu ery Compiler for Spatial Workloads

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ACM SIGMOD International Conference on Management of Data (SIGMOD)

作者： Tahboub, Ruby Y. Rompf, Tiark Purdue Univ W Lafayette IN 47907 USA

ISBN: (纸本)9781450367356

Modern location-based applications rely extensively on the efficient processing of spatial data and queries. spatial query engines are commonly engineered as an extension to a relational database or a cluster-computing framework. Large parts of the spatial processing runtime is spent on evaluating spatial predicates and traversing spatial indexing structures. Typical high-level implementations of these spatial structures incur significant interpretive overhead, which increases latency and lowers throughput. A promising idea to improve the performance of spatial workloads is to leverage native code generation techniques that have become popular in relational query engines. However, architecting a spatial query compiler is challenging since spatial processing has fundamentally different execution characteristics from relational workloads in terms of data dimensionality, indexing structures, and predicate evaluation. In this paper, we discuss the underlying reasons why standard query compilation techniques are not fully effective when applied to spatial workloads, and we demonstrate how a particular style of query compilation based on techniques borrowed from partial evaluation and generative programming manages to avoid most of these difficulties by extending the scope of custom code generation into the data structures layer. We extend the LB2 main-memory query compiler, a relational engine developed in this style, with spatial data types, predicates, indexing structures, and operators. We show that the spatial extension matches the performance of specialized library code and outperforms relational and map-reduce extensions.

关键词： query Compilation Staging Code Generation spatial query processing Futamura Projections Extensible Compilers

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Distributed Mining of Popular Paths in Road Networks 14

Distributed Mining of Popular Paths in Road Networks

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14th Annual International Conference on Distributed Computing in Sensor Systems (DCOSS)

作者： Katsikouli, Panagiota Astefanoaei, Maria Sinziana Sarkar, Rik Univ Edinburgh Informat Edinburgh Midlothian Scotland Univ Lyon INRIA INSA Lyon CITI Lyon France

ISBN: (纸本)9781538654705

We consider the problem of finding large scale mobility patterns. A common challenge in mobility tracking systems is that large quantity of data is spread out spatially and temporally across many tracking sensors. We thus devise a spatial sampling and information exchange protocol that provides probabilistic guarantees on detecting prominent patterns. For this purpose, we define a general notion of significant popular paths that can capture many different types of motion. We design a summary sketch for the data at each tracking node, which can be updated efficiently, and then aggregated across devices to reconstruct the prominent paths in the global data. The algorithm is scalable, even with large number of mobile targets. It uses a hierarchic query system that automatically prioritizes important trajectories - those that are long and popular. We show further that this scheme can in fact give good results by sampling relatively few sensors and targets, and works for streaming spatial data. We prove differential privacy guarantees for the randomized algorithm. Extensive experiments on real GPS data show that the method is efficient and accurate, and is useful in predicting motion of travelers even with small samples.

关键词： Trajectories road networks sensor networks distributed algorithm clustering spatial query processing differential privacy

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SP-Phoenix: a Massive spatial Point Data Management System based on Phoenix 20

SP-Phoenix: a Massive Spatial Point Data Management System b...

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20th IEEE International Conference on High Performance Computing and Communications (HPCC) / 16th IEEE International Conference on Smart City (SmartCity) / 4th IEEE International Conference on Data Science and Systems (DSS)

作者： Li, Longhai Liu, Wendong Zhong, Zhaoyu Huang, Chengqiang Xidian Univ Sch Comp Sci & Technol Xian 710071 Shaanxi Peoples R China Univ Exeter Coll Engn Math & Phys Sci Exeter EX4 4QF Devon England

ISBN: (纸本)9781538666142

The NoSQL database HBase has been widely used to build data management systems and data warehouse systems primarily due to its inherent advantages in scalability, fault tolerance, throughput and distributed processing ability. However, HBase does not provide direct support for storing and retrieving spatial data. We designed a data management system for massive spatial points called SP-Phoenix based on two open-source projects, Phoenix and HBase. SP-Phoenix is highly scalable, fault tolerant, and supports flexible access to its spatial data through an extended SQL language. By taking advantage of geohash-based spatial indexes, SP-Phoenix achieves several basic spatial query operations including rectangular range query, non-regular area query and k-Nearest-Neighbor(kNN) query which are all essential primitives for realizing complex spatial queries. SP-Phoenix employs the user-defined functions and server-side aggregating and sorting mechanisms offered by Phoenix to impose most spatial filtering tasks on the server side in query processing, effectively reducing the computing burden of the client. SP-Phoenix also leverages a query optimization method based on spatial distribution statistics, which further improves the efficiency of spatial query. Experimental evaluations show that SP-Phoenix deployed over a small scale cluster can sustain an I/O throughput of over hundreds of thousands of data insertions per second, while serving spatial range queries and kNN queries with response times as low as hundreds of milliseconds. The experiments demonstrate that SP-Phoenix is applicable to a wide spectrum of spatial position related applications which demand high insertion throughput and real time spatial queries.

关键词： spatial data HBase Phoenix spatial query processing

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Efficient query processing for Spatio-Temporal Databases

Efficient Query Processing for Spatio-Temporal Databases

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作者： Chen, Yun University of Michigan

学位级别：doctor

Spatio-temporal databases are required to efficiently support queries on large numbers of continuously moving objects. In this thesis we propose three techniques to address this challenge. We develop the STRIPES indexing method, which indexes predicted trajectories in a dual transformed space. Trajectories for objects in d-dimensional space are transformed into points in 2d-dimensional space and are indexed with a hierarchical grid decomposition structure. STRIPES can evaluate a range of queries including time-slice, window, and moving queries. Extensive experimental evaluation shows that STRIPES is significantly faster than leading existing predicted trajectory index (the TPR*-tree) for both updates and queries. The All Nearest Neighbor (ANN) operation is a commonly used primitive for analyzing large multi-dimensional datasets. Traditional R*-tree based methods use a pruning metriccalled MAXMAXDIST, which allows the algorithms to prune nodes in the index that need not be examined during the ANN computation. We introduce a new pruning metric called NXNDIST, and show that this metric is far more effective than MAXMAXDIST. We also propose the MBRQT index structure, and using extensive experimental evaluation show that MBRQT offers better speedup in ANN computation than the commonly used R*-tree index. In addition, we present the MBA algorithm using depth-first index traversal and bi-directional node expansion. Furthermore, we extend our method to evaluate the more general All-k-Nearest-Neighbor (AkNN) *** spatial and traditional temporal joins have been widely studied in the past, but there is very little work on the more complex problem of trajectory joins. We present a general framework called JiST, that introduces a broad class of trajectory join operations and offers a set of algorithms to efficiently evaluate these operations. We then introduce the notion of Trajectory Privacy, and show the application of the JiST framework in the context of pri

关键词： spatio-temporal databases database indexing spatial query processing location privacy moving objects database location privacy Computer Science Engineering

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Fast Web - Based Data Transmission

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Journal of China University of Geosciences 2001年第2期12卷 165-176页

作者： Wei Zukuan Department of Computer Science & Engineering, Inha University, Inchon 402 751, Korea Kim Jaehong Department of Computer Science, Youngdong University, Youngdong, Korea Bae Haeyoung Department of Computer Science & Engineering, Inha Uni Department of Computer Science Engineering Inha University Department of Computer Science Youngdong University Youngdong Korea

Since web based GIS processes large size spatial geographic information on internet, we should try to improve the efficiency of spatial data query processing and transmission. This paper presents two efficient methods for this purpose: division transmission and progressive transmission methods. In division transmission method, a map can be divided into several parts, called “tiles”, and only tiles can be transmitted at the request of a client. In progressive transmission method, a map can be split into several phase views based on the significance of vertices, and a server produces a target object and then transmits it progressively when this spatial object is requested from a client. In order to achieve these methods, the algorithms, “tile division”, “priority order estimation” and the strategies for data transmission are proposed in this paper, respectively. Compared with such traditional methods as “map total transmission” and “layer transmission”, the web based GIS data transmission, proposed in this paper, is advantageous in the increase of the data transmission efficiency by a great margin.

关键词： spatial data transmission spatial query processing web based GIS geographic information system spatial database.

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GeoSPARQL query support for scientific raster array data

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COMPUTERS & GEOSCIENCES 2022年 159卷

作者： Almobydeen, Shahed Bassam Viqueira, Jose R. R. Lama, Manuel Univ Santiago De Compostela USC Ctr Singular Invest Tecnol Intelixentes CITIUS Rua Jenaro de la Fuente Dominguez Santiago De Compostela 15782 Spain

This paper presents the design of a GeoSPARQL query processing solution for scientific raster array data, called GeoLD. The solution enables the implementation of SPARQL endpoints on top of OGC standard Web Coverage processing Services (WCPS). Thus, the semantic querying of scientific raster data is supported without the need of specific raster array functions in the language. To achieve this, first Coverage to RDF mapping solutions were defined, based on the well-known W3C standard mappings for relational data. Next, the SPARQL algebra is extended with a new operator that delegates part of the GeoSPARQL query in WCPS services. query optimization replaces those parts of the SPARQL query plan that may be delegated to a WCPS service by instances of such new WCPS operator. A first prototype has been implemented by extending the ARQ SPARQL query engine of Apache Jena. Petascope was used as the WCPS implementation on top of the Rasdaman raster array database. An initial evaluation with real meteorological data shows, as it was initially expected, that the approach outperforms an existing reference relational database based GeoSPARQL implementation.

关键词： Geospatial linked data Scientific linked data Array linked data Raster linked data GeoSPARQL spatial query processing

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Ripple: An approach to locate k nearest neighbours for location-based services

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INFORMATION SYSTEMS 2022年 105卷

作者： Biswas, Pratima Dandapat, Sourav Kumar Sairam, Ashok Singh Indian Inst Technol Patna Dept Comp Sci Patna 801106 Bihar India Indian Inst Technol Guwahati Dept Math Gauhati 781039 Assam India

The increasing popularity of location-based services has led to a renewed interest in spatial query processing. In this paper, we propose Ripple , a light-weighted framework to find the nearest neighbours. The area is divided into square cells of equal size to form a grid structure. The search advances by progressively expanding the investigation region as a series of concentric squares, with the cell of query point as the centre. This is in contrast to the popular approach of increasing the search space as concentric circles. The circular search scheme explores only those square cells that intersect the circle and as a result, has a smaller search region. However, it has an added overhead of tracing the cells that intersect the circle for the same reason. In Ripple, there is no such additional overhead due to harmony in the investigation region's configuration and the underlying grid structure. We optimize the search space by exploiting the distance between the query point and the distant candidate neighbours. Extensive experiments have been performed to compare the performance of the proposed approaches using different performance measures. @2021 Published by Elsevier Ltd.

关键词： Grid-index Location-based services Nearest neighbours search spatial query processing

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Adaptive hierarchical bitmap-based index for wireless broadcast environments in an emergency

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COMPUTER SYSTEMS SCIENCE AND ENGINEERING 2016年第4期31卷 259-273页

作者： Song, Doohee Park, Kwangjin Wonkwang Univ Dept Informat & Commun Engn Chunrabuk Do 570749 South Korea

A novel method for broadcast systems that reduces access latency in receiving spatial information from the server is developed. In particular, we focus on emergency situations in which the client must reduce the query processing time. We propose an Adaptive Hierarchical Bitmap-based spatial Index (AHBI) that shortens the broadcast cycle by reducing the size of the index in the broadcast environment. The AHBI structure uses (1, m) indexing and a distributed index. This can represent the presence and absence of objects within each grid after splitting the overall map so that it is fitted to the space-filling curve. The location of objects can also be identified selectively using the AHBI, as it can support clients' selective data tuning. AHBI reduces access latency by overcoming the disadvantages of conventional HBI, thus shortening the client's query processing time. In this paper, the structure of the AHBI is evaluated and compared with existing (1, m) indexing-based techniques. The experimental results verify the effectiveness of AHBI in terms of its cost model.

关键词： wireless broadcast spatial query processing k nearest neighbors (kNN) (1, m) indexing distributed index

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