Ho-Hyun Park

Multi-way Spatial Joins Using R-Trees: Methodology and Performance Evaluation

We propose a new multi-way spatial join algorithm called M-way R-tree join which synchronously traverses M R-trees. The M-way R-tree join can be considered as a generalization of the 2-way R-tree join. Although a generalization of the 2-way R-tree join has recently been studied, it did not properly take into account the optimization techniques of the original algorithm. Here, we extend these optimization techniques for M-way joins. Since the join ordering was considered to be important in the M-way join literature (e.g., relational join), we especially consider the ordering of the search space restriction and the plane sweep. Additionally, we introduce indirect predicates in the M-way join and propose a further optimization technique to improve the performance of the M-way R-tree join. Through experiments using real data, we show that our optimization techniques significantly improve the performance of the M-way spatial join.

A Distributed and Scalable Time Slot Allocation Protocol for Wireless Sensor Networks

There are performance deficiencies that hamper the deployment of Wireless Sensor Networks (WSNs) in critical monitoring applications. Such applications are characterized by considerable network load generated as a result of sensing some characteristics of the monitored system. Excessive packet collisions lead to packet losses and retransmissions, resulting in significant overhead costs and latency. In order to address this issue, we introduce a distributed and scalable scheduling access scheme that mitigates high data loss in data-intensive sensor networks and can also handle some mobility. Our approach alleviates transmission collisions by employing virtual grids that adopt Latin Squares characteristics to time slot assignments. We show that our algorithm derives conflict-free time slot allocation schedules without incurring global overhead in scheduling. Furthermore, we verify the effectiveness of our protocol by simulation experiments. The results demonstrate that our technique can efficiently handle sensor mobility with acceptable data loss, low packet delay, and low overhead.

Early separation of filter and refinement steps in spatial query optimization

The spatial query has been processed in two steps, the filter step and the refinement step, due to the large volume and high complexity of the spatial data. However, this approach has been considered only in the query execution phase after completion of the query optimization phase. This paper presents query optimization strategies which take the characteristics of spatial databases into account. The first strategy is the separation of filter and refinement steps not in the query execution phase but in the query optimization phase. As the second strategy, several refinement operations can be combined in processing a complex query, and as the third strategy several filter operations can also be combined. We call the optimization technique utilizing these strategies the early separated filter and refinement (ESFAR). This paper also presents a rule-based optimization technique for ESFAR.

A formalism of XML restructuring operations

We present a set of primitive restructuring operators that, when combined, are sufficiently powerful to convert an XML document under a source schema into an XML document under an arbitrary target schema We initially define the operators at the schema level, and then show how each operator induces a corresponding transformation on any XML document under the schema Finally, we note that our operators can be implemented in a high level language such as XQuery, and thus our approach can be used as the basis for automating the conversion of one XML document to another XML document.

Spatial query optimization utilizing early separated filter and refinement strategy

Abstract Due to the high complexity and large volume of spatial data, a spatial query is usually processed in two steps, called the filter step and the refinement step . However, the two-step processing of the spatial query has been considered locally in one spatial predicate evaluation at the query execution level. This paper presents query optimization strategies which exploit the two-step processing of a spatial query at the query optimization level. The first strategy involves the separation of filter and refinement steps not in the query execution phase but in the query optimization phase. As the second strategy, several refinement operations can be combined in processing a complex query if they were already separated, and as the third strategy several filter operations can also be combined. We call the optimization technique utilizing these strategies the Early Separated Filter And Refinement (ESFAR). This paper also presents an algebra, which is called the Intermediate Spatial Object Algebra (ISOA), and optimization rules for ESFAR. Through experiments using real data, we compare the ESFAR optimization technique with a traditional optimization technique which does not separate filter and refinement steps from the query optimization phase. The experimental results show that the ESFAR optimization technique generates more efficient query execution plans than the traditional one in many cases.

Electromagnetic penetration into 2-D multiple slotted rectangular cavity: TM-wave

Electromagnetic wave penetration into the two-dimensional (2-D) rectangular cavity with multiple slots in an infinite conducting plane with a finite thickness is investigated. The Fourier transform and the mode-matching technique are used to obtain simultaneous equations, which are solved to represent the scattered and the penetrated fields in series forms that are suitable for numerical computations.

Parallel hybrid evolutionary computation: Automatic tuning of parameters for parallel gene expression programming

Abstract A parallel hybrid framework that combines gene expression programming (GEP) as the evolutionary problem-solving methodology and alternative meta-heuristics for tuning parameter values of the parallel GEP runs is presented. The implementation of this framework is based on a client–server architecture which includes clients that use GEP to evolve candidate solutions for the problem in question, and clients that use (possibly) other meta-heuristics to tune GEP input parameters. In the implementation of this framework, a genetic algorithms methodology is used for parameter tuning. For testing the framework and its implementation, a suite of symbolic regression problems of different complexities is used. Our experimental results show that our approach provides a solution for the problem of automatically tuning two GEP input parameters, viz. , the number of genes and the length of each gene.

Logic-based interpretation of geometrically observable changes occurring in dynamic scenes

The work presented here is about employing a theory of updates to study geometrically observable changes that occur in spatial information about image sequences of a dynamic scene. The logical framework consists of a formalism for specifying the geometrical content of a scene, as well as the changes that occur in this geometry, and an algorithm for constructing a description for such changes from logical deductions. In this approach, a database state represents the available sensor data at a particular time instant. Transitions in sensor data are modeled by changes in the database and interpreted based on axioms encoding commonsense spatial reasoning. The main contribution of this work is that it provides the theoretical foundations for symbolically interpreting long sequences of sensor data transitions. For testing the framework and its implementation, the problem of interpreting rotational movements of objects in a sequence of images was used. Our experiments show that the system correctly interprets rotational movements for objects of different colors and provides satisfactory results for interpreting such movements from perceptually indistinguishable objects.

Multi-way spatial join selectivity for the ring join graph

Efficient spatial query processing is very important since the applications of the spatial DBMS (e.g. GIS, CAD/CAM, LBS) handle massive amount of data and consume much time. Many spatial queries contain the multi-way spatial join due to the fact that they compute the relationships (e.g. intersect) among the spatial data. Thus, accurate estimation of the spatial join selectivity is essential to generate an efficient spatial query execution plan that takes advantages of spatial access methods efficiently. For the multi-way spatial joins, the selectivity estimation formulae only for the two kinds of query types, tree and clique, have been developed. However, the selectivity estimation for the general query graph which contains cycles has not been developed yet. To fill this gap, we devise a formula for the multi-way spatial ring join selectivity. This is an indispensable step to compute the selectivity of the general multi-way spatial join whose join graph contains cycles. Our experiment shows that the estimated sizes of query results using our formula are close to the sizes of actual query results.

Product recommendations for cross-selling in electronic business

A system applicable in electronic commerce environments that combines the strengths of both collaborative filtering and data mining for providing better recommendations is presented. It captures the item-to-item relationship through association rule mining and then uses purchase behaviour of collaborative users for generating the recommendations. It was implemented and evaluated on a set of real datasets. Our methodology results in improved quality of recommendations measured in terms of recall and coverage metrics.