The Experts below are selected from a list of 20799 Experts worldwide ranked by ideXlab platform
Hans-peter Kriegel - One of the best experts on this subject based on the ideXlab platform.
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ICDE - Efficient Query Processing in Large Traffic Networks
2008 IEEE 24th International Conference on Data Engineering, 2008Co-Authors: Hans-peter Kriegel, Peer Kröger, Peter Kunath, Matthias Renz, Schmidt TAbstract:We present an original graph embedding to speedup distance-range and k-nearest neighbor queries on static and/or dynamic objects located on a (weighted) graph. Our method is used to compute a lower and upper bounding filter distance which approximates the true shortest path distance significantly better than traditional filters. In addition, we discuss how the computation of the exact shortest path distance in the Refinement Step can be boosted by using the embedded graph.
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IGIS - Approximations for a Multi-Step Processing of Spatial Joins
Lecture Notes in Computer Science, 1994Co-Authors: Thomas Brinkhoff, Hans-peter KriegelAbstract:The basic concept for processing spatial joins consists of two Steps: First, the spatial join is performed on the minimum bounding rectangles of the objects by using a spatial access method. This Step provides a set of candidates which consists of answers (hits) and non-answers (false hits). In the second Step, the exact geometry of the candidates is transferred from secondary storage into main memory and is tested against the join predicate. This Step is called Refinement Step. It causes the main cost for computing a spatial join. In this paper, we introduce an additional filter Step in order to reduce the cost of the Refinement Step. In this filter Step more sophisticated approximations are used to identify hits as well as to filter out false hits from the set of candidates. For this purpose, we investigate various types of conservative and progressive approximations. The performance of the approximation approach is evaluated with data sets from real cartographic applications. The results show that this approach considerably reduces the total execution time of the spatial join.
Debra J. Richardson - One of the best experts on this subject based on the ideXlab platform.
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Systematic testing of software architectures in the C2 style
Lecture Notes in Computer Science, 2004Co-Authors: Henry Muccini, Marcio S. Dias, Debra J. RichardsonAbstract:The topic of software architecture (SA) based testing has recently raised some interest. Recent work on the topic has used the SA as a reference model for code conformance testing, to check if an implementation fulfills (conforms to) its specification at the SA level. In this context, on previous papers, we have analyzed: i) how suitable test cases can be selected from the SA specification and ii) how they may be refined into concrete tests executable at the code level. While the selection stage has been done systematically, the Refinement Step has been left to be done manually, based on the software engineer knowledge on how to map abstract values of the specification to the concrete values of the implementation. In this paper, we extend previous approaches, by providing a systematic way to perform the Refinement Step. We show how choosing a specific architectural style, which supports implementation and facilitates the mapping among SA-based and code-based test cases, a completely systematic SA-based testing approach can be delivered.
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FASE - Systematic Testing of Software Architectures in the C2 Style
Fundamental Approaches to Software Engineering, 2004Co-Authors: Henry Muccini, Marcio S. Dias, Debra J. RichardsonAbstract:The topic of software architecture (SA) based testing has recently raised some interest. Recent work on the topic has used the SA as a reference model for code conformance testing, to check if an implementation fulfills (conforms to) its specification at the SA level. In this context, on previous papers, we have analyzed: i) how suitable test cases can be ”selected” from the SA specification and ii) how they may be ”refined” into concrete tests executable at the code level. While the selection stage has been done systematically, the Refinement Step has been left to be done manually, based on the software engineer knowl- edge on how to map ”abstract values of the specification to the concrete values of the implementation”. In this paper, we extend previous approaches, by pro- viding a systematic way to perform the Refinement Step. We show how choos- ing a specific architectural style, which supports implementation and facilitates the mapping among SA-based and code-based test cases, a completely system- atic SA-based testing approach can be delivered.
Amr El Abbadi - One of the best experts on this subject based on the ideXlab platform.
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Fast computation of spatial selections and joins using graphics hardware
Information Systems, 2007Co-Authors: Nagender Bandi, Chengyu Sun, Divyakant Agrawal, Amr El AbbadiAbstract:Spatial database operations are typically performed in two Steps. In the filtering Step, indexes and the minimum bounding rectangles (MBRs) of the objects are used to quickly determine a set of candidate objects. In the Refinement Step, the actual geometries of the objects are retrieved and compared to the query geometry or each other. Because of the complexity of the computational geometry algorithms involved, the CPU cost of the Refinement Step is usually the dominant cost of the operation for complex geometries such as polygons. Although many run-time and pre-processing-based heuristics have been proposed to alleviate this problem, the CPU cost still remains the bottleneck. In this paper, we propose a novel approach to address this problem using the efficient rendering and searching capabilities of modern graphics hardware. This approach does not require expensive pre-processing of the data or changes to existing storage and index structures, and is applicable to both intersection and distance predicates. We evaluate this approach by comparing the performance with leading software solutions. The results show that by combining hardware and software methods, the overall computational cost can be reduced substantially for both spatial selections and joins. We integrated this hardware/software co-processing technique into a popular database to evaluate its performance in the presence of indexes, pre-processing and other proprietary optimizations. Extensive experimentation with real-world data sets show that the hardware-accelerated technique not only outperforms the run-time software solutions but also performs as well if not better than pre-processing-assisted techniques.
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SIGMOD Conference - Hardware acceleration for spatial selections and joins
Proceedings of the 2003 ACM SIGMOD international conference on on Management of data - SIGMOD '03, 2003Co-Authors: Chengyu Sun, Divyakant Agrawal, Amr El AbbadiAbstract:Spatial database operations are typically performed in two Steps. In the filtering Step, indexes and the minimum bounding rectangles (MBRs) of the objects are used to quickly determine a set of candidate objects, and in the Refinement Step, the actual geometries of the objects are retrieved and compared to the query geometry or each other. Because of the complexity of the computational geometry algorithms involved, the CPU cost of the Refinement Step is usually the dominant cost of the operation for complex geometries such as polygons. In this paper, we propose a novel approach to address this problem using efficient rendering and searching capabilities of modern graphics hardware. This approach does not require expensive pre-processing of the data or changes to existing storage and index structures, and it applies to both intersection and distance predicates. Our experiments with real world datasets show that by combining hardware and software methods, the overall computational cost can be reduced substantially for both spatial selections and joins.
Elke A. Rundensteiner - One of the best experts on this subject based on the ideXlab platform.
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Symbolic Intersect Detection: A Method for Improving Spatial Intersect Joins
Geoinformatica, 1998Co-Authors: Yun-wu Huang, Matt Jones, Elke A. RundensteinerAbstract:Due to the increasing popularity of spatial databases, researchers have focused their efforts on improving the query processing performance of the most expensive spatial database operation: the spatial join. While most previous work focused on optimizing the filter Step, it has been discovered recently that, for typical GIS data sets, the Refinement Step of spatial join processing actually requires a longer processing time than the filter Step. Furthermore, two-thirds of the time in processing the Refinement Step is devoted to the computation of polygon intersections. To address this issue, we therefore introduce a novel approach to spatial join optimization that drastically reduces the time of the Refinement Step. We propose a new approach called Symbolic Intersect Detection (SID) for early detection of true hits. Our SID optimization eliminates most of the expensive polygon intersect computations required by a spatial join by exploiting the symbolic topological relationships between the two candidate polygons and their overlapping minimum bounding rectangle. One important feature of our SID optimization is that it is complementary to the state-of-the-art methods in spatial join processing and therefore can be utilized by these techniques to further optimize their performance. In this paper, we also develop an analytical cost model that characterizes SID’s effectiveness under various conditions. Based on real map data, we furthermore conduct an experimental evaluation comparing the performance of the spatial joins with SID against the state-of-the-art approach. Our experimental results show that SID can effectively identify more than 80% of the true hits with negligible overhead. Consequently, with SID, the time needed for resolving polygon intersect in the Refinement Step is improved by over 50% over known techniques, as predicted by our analytical model.
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SSD - Improving Spatial Intersect Joins Using Symbolic Intersect Detection
Advances in Spatial Databases, 1997Co-Authors: Yun-wu Huang, Matthew C. Jones, Elke A. RundensteinerAbstract:We introduce a novel technique to drastically reduce the computation required by the Refinement Step during spatial intersect join processing. This technique, called Symbolic Intersect Detection (SID), detects most of the true hits during a spatial intersect join by scrutinizing symbolic topological relationships between candidate polygon pairs. SID boosts performance by detecting true hits early during the Refinement Step, thus avoiding expensive polygon intersect computations that would otherwise be required to detect the true hits. Our experimental evaluation with real GIS map data demonstrates that SID can identify more than 80% of the true hits with only minimal overhead. Consequently, SID outperforms known techniques for resolving polygon intersection during the Refinement Step by more than 50%. Most state-of-the-art methods in spatial join processing can benefit from SID's performance gains because the SID approach integrates easily into the established two-phase spatial join process.
Henry Muccini - One of the best experts on this subject based on the ideXlab platform.
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Systematic testing of software architectures in the C2 style
Lecture Notes in Computer Science, 2004Co-Authors: Henry Muccini, Marcio S. Dias, Debra J. RichardsonAbstract:The topic of software architecture (SA) based testing has recently raised some interest. Recent work on the topic has used the SA as a reference model for code conformance testing, to check if an implementation fulfills (conforms to) its specification at the SA level. In this context, on previous papers, we have analyzed: i) how suitable test cases can be selected from the SA specification and ii) how they may be refined into concrete tests executable at the code level. While the selection stage has been done systematically, the Refinement Step has been left to be done manually, based on the software engineer knowledge on how to map abstract values of the specification to the concrete values of the implementation. In this paper, we extend previous approaches, by providing a systematic way to perform the Refinement Step. We show how choosing a specific architectural style, which supports implementation and facilitates the mapping among SA-based and code-based test cases, a completely systematic SA-based testing approach can be delivered.
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FASE - Systematic Testing of Software Architectures in the C2 Style
Fundamental Approaches to Software Engineering, 2004Co-Authors: Henry Muccini, Marcio S. Dias, Debra J. RichardsonAbstract:The topic of software architecture (SA) based testing has recently raised some interest. Recent work on the topic has used the SA as a reference model for code conformance testing, to check if an implementation fulfills (conforms to) its specification at the SA level. In this context, on previous papers, we have analyzed: i) how suitable test cases can be ”selected” from the SA specification and ii) how they may be ”refined” into concrete tests executable at the code level. While the selection stage has been done systematically, the Refinement Step has been left to be done manually, based on the software engineer knowl- edge on how to map ”abstract values of the specification to the concrete values of the implementation”. In this paper, we extend previous approaches, by pro- viding a systematic way to perform the Refinement Step. We show how choos- ing a specific architectural style, which supports implementation and facilitates the mapping among SA-based and code-based test cases, a completely system- atic SA-based testing approach can be delivered.
