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Approximating the evolution of rotating moving regions using Bezier curves

INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE 2023年第4期37卷 839-863页

作者： Duarte, Jose Dias, Paulo Moreira, Jose Univ Aveiro Inst Elect & Informat Engn Aveiro IEETA Aveiro Portugal Univ Aveiro Dept Elect Telecommun & Informat DETI Aveiro Portugal Univ Aveiro Intelligent Syst Associate Lab LASI Aveiro Portugal

The region interpolation methods proposed in the moving objects databases literature impose restrictions that can have a significant impact on the representation of the evolution of moving regions, in particular, when a rotation occurs between two observations. In this paper, we propose a data model for moving regions that allows moving segments to rotate and change their length during their evolution between two observations and uses quadratic Bezier curves to define the trajectories of their endpoints. This introduces a new class of moving regions called rotating moving regions (rmregions). We present algorithms for operations involving rmregions and we propose a strategy to allow different interpolation methods to be used in the context of moving objects databases by approximating the interpolations they create using rmregions. We demonstrate our strategy using a reference implementation and compare results obtained when using the strategy presented here and the region interpolation methods and the spatiotemporal operations proposed in the state-of-the-art. Experimental results show that our strategy can be used to complement the region interpolation methods proposed in the moving objects databases literature.

关键词： Region interpolation problem moving regions moving objects databases spatiotemporal operations interpolation methods

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Spatiotemporal coverage analysis of moving regions

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INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE 2021年第5期35卷 948-973页

作者： Heinz, Florian Gueting, Ralf Hartmut FernUniversitat Database Syst New Applicat Hagen Germany

moving objects databases are specialized for processing objects that have attributes which change over time. A moving region is a powerful data type in this context, describing a region which changes shape and position over a specified time interval. This data type is, for example, a suitable model for natural phenomena like hurricanes, clouds or forest fires. Several operations exist to process and analyze moving regions in moving objects databases. One useful operation is to determine which areas are covered for which time span during the movement of moving regions to calculate, for example, which areas are affected by a hurricane for a certain period of time. This paper presents a set of operations that can be used to analyze the spatiotemporal coverage behavior of a moving region to determine which regions are covered for shorter or longer than a given time, or which parts are covered for a specified time interval. Furthermore, the coverage duration of a single point and the average coverage duration for a given region can be determined.

关键词： moving objects databases geocomputation geographic information systems moving regions spatiotemporal coverage

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GraCT: A Grammar-based Compressed Index for Trajectory Data

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INFORMATION SCIENCES 2019年 483卷 106-135页

作者： Brisaboa, Nieves R. Gomez-Brandon, Adrian Navarro, Gonzalo Parama, Jose R. Univ A Coruna Fac Informat CITIC Campus Elvina S-N La Coruna 15071 Spain Univ Chile Dept Comp Sci Millennium Inst Fdn Res Data IMFD Beauchef 851 Santiago Chile

We introduce a compressed data structure for the storage of free trajectories of moving objects that efficiently supports various spatio-temporal queries. Our structure, dubbed GraCT, stores the absolute positions of all the objects at regular time intervals (snapshots) using a k(2)-tree, which is a space- and time-efficient region quadtree. Positions between snapshots are represented as logs of relative movements and compressed using a grammar-based compressor. The non-terminals of this grammar are enhanced with MBR information to enable fast queries. The GraCT structure of a dataset occupies less than the raw data compressed with a powerful traditional compressor. Further, instead of requiring full decompression to access the data like a traditional compressor, GraCT supports direct access to object trajectories or to their position at specific time instants, as well as spatial range and nearest-neighbor queries on time instants and/or time intervals. Compared to traditional methods for storing and indexing spatio-temporal data, GraCT requires two orders of magnitude less space, and is competitive in query times. In particular, thanks to its compressed representation, the GraCT structure may reside in main memory in situations where any classical uncompressed index must resort to disk, thereby being one or two orders of magnitude faster. (C) 2019 Elsevier Inc. All rights reserved.

关键词： Compact data structures moving objects databases

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Cost evaluation and improvement of TB-tree insertion algorithm

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JOURNAL OF COMPUTATIONAL METHODS IN SCIENCES AND ENGINEERING 2018年第2期18卷 445-458页

作者： Ji, Xianbiao Mi, Hong Yang, Fan Shao, Zheping Pan, Jiacai Xiamen Univ Dept Automat Xiamen 361005 Fujian Peoples R China Jimei Univ Sch Business Adm Xiamen 361021 Fujian Peoples R China Zhejiang Univ Sch Publ Affairs Hangzhou 310027 Zhejiang Peoples R China Jimei Univ Coll Nav Xiamen 361021 Fujian Peoples R China

This paper proposes the cost evaluation model for the existing TB-tree insertion algorithm called BASEINSERT. Factors that may affect its performance are analyzed in a detailed manner. While we search the latest node, the number of nodes being accessed is very prominent. Given this property, the paper comes up with an improved algorithm, named IMPRINSERT by adding the cache structures of root-latest-node path and right-most path, which reduce the number of nodes being accessed while searching for the latest node and right-most path close to zero. Under the bulk data setting, algorithm that inserts the data segment by segment is fairly inefficient, therefore this paper introduces a new insertion algorithm, called BULKINSERT and its cost evaluation model is proposed as well. Verified by a large number of synthesized datasets, it is proved that the cost models are reliable, both IMPRINSERT and BULKINSERT are effective and demonstrate nearly linear scalability.

关键词： TB-tree insertion algorithm cost evaluation bulk insertion moving objects databases

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A generic trajectory similarity operator in moving object databases

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EGYPTIAN INFORMATICS JOURNAL 2017年第1期18卷 29-37页

作者： Magdy, Nehal Sakr, Mahmoud A. El-Bahnasy, Khaled Ain Shams Univ Fac Comp & Informat Sci Cairo Egypt

Evaluating similarity between trajectories of moving objects is important for wide range of applications. The existing similarity measures typically define some meaning of similarity and propose algorithms for computing it. We think that the meaning of similarity is application dependant, and should only be determined by the user. Therefore, there is a need for a generic approach where users can define the meaning of similarity. In this paper, we propose a parametrized similarity operator, based on the time warped edit distance, where the meaning of similarity is generic and left for user to define. Our proposed operator is implemented in SECONDO and evaluated using both synthetic and real datasets. The results were promising and as expected. (C) 2016 Production and hosting by Elsevier B.V. on behalf of Faculty of Computers and Information, Cairo University. This is an open access article under the CC BY-NC-ND license.

关键词： Trajectory similarity moving objects databases SECONDO TWED

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Robust high-quality interpolation of regions to moving regions

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GEOINFORMATICA 2016年第3期20卷 385-413页

作者： Heinz, Florian Gueting, Ralf Hartmut Fern Univ Hagen Database Syst New Applicat Hagen Germany

With the rise of moving object databases it is possible to store and process spatial and temporal data, for example geometrical structures together with the information about how these behave over intervals of time. For simple objects like moving points the spatiotemporal development is derived from the start and end position in space and time, which is then linearly interpolated. For moving regions, especially with changing shapes, it is more challenging to obtain the necessary data to represent them. An elegant and intuitive solution is to create an algorithm, which automatically interpolates the moving region from the start and end shape over a specified time interval. Two papers on this topic have been published in the past, each focussing on different aspects of this so-called Region Interpolation Problem. This paper tries to combine the advantages and improve these approaches to provide high-quality interpolations while maintaining robustness even in border cases. This results in the implementation of a library, which can be easily integrated into existing moving objects database systems, as for example the DBMS Secondo developed at the FernUniversitat in Hagen.

关键词： Spatial databases moving objects databases moving regions Region interpolation

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Anonymization of moving objects databases by clustering and perturbation

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INFORMATION SYSTEMS 2010年第8期35卷 884-910页

作者： Abul, Osman Bonchi, Francesco Nanni, Mirco Yahoo Res Barcelona 08018 Spain TOBB Univ Econ & Technol Dept Comp Engn Ankara Turkey CNR ISTI Area Ric Pisa Pisa KDD Lab I-56124 Pisa Italy

Preserving individual privacy when publishing data is a problem that is receiving increasing attention. Thanks to its simplicity the concept of k-anonymity, introduced by Samarati and Sweeney [1], established itself as one fundamental principle for privacy preserving data publishing. According to the k-anonymity principle, each release of data must be such that each individual is indistinguishable from at least k-1 other individuals. In this article we tackle the problem of anonymization of moving objects databases. We propose a novel concept of k-anonymity based on co-localization, that exploits the inherent uncertainty of the moving object's whereabouts. Due to sampling and imprecision of the positioning systems (e.g., GPS), the trajectory of a moving object is no longer a polyline in a three-dimensional space, instead it is a cylindrical volume, where its radius delta represents the possible location imprecision: we know that the trajectory of the moving object is within this cylinder, but we do not know exactly where. If another object moves within the same cylinder they are indistinguishable from each other. This leads to the definition of (k,delta)-anonymity for moving objects databases. We first characterize the (k,delta)-anonymity problem, then we recall NWA (Never Walk Alone), a method that we introduced in [2] based on clustering and spatial perturbation. Starting from a discussion on the limits of NWA we develop a novel clustering method that, being based on EDR distance [3], has the important feature of being time-tolerant. As a consequence it perturbs trajectories both in space and time. The novel method, named W4M (Wait for Me), is empirically shown to produce higher quality anonymization than NWA, at the price of higher computational requirements. Therefore, in order to make W4M scalable to large datasets, we introduce two variants based on a novel (and computationally cheaper) time-tolerant distance function, and on chunking. All the variants of W4M(

关键词： moving objects databases Trajectories Anonymity Uncertainty Clustering

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Formalization of Network-constrained moving object queries with application to Benchmarking 7

Formalization of Network-constrained moving object queries w...

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7th ACM SIGSPATIAL International Workshop on GeoStreaming (IWGS)

作者： Fouladgar, Mohammadhani Elmasri, Ramez Univ Texas Arlington Dept Comp Sci & Engn Arlington TX 76019 USA

ISBN: (纸本)9781450345798

In this paper, we first categorize the various types of Network-constrained moving object queries. We then propose benchmarks that can be used to compare the performance of systems and indexing schemes that are proposed for handling these types of queries. Network-constrained moving objects are objects that move in a specific network, such as vehicles that are constrained to move in a road (traffic) network. Our query categories are based on the Network-constrained moving object model presented by [4, 6, 14]. We formally define comprehensive categories of typical queries, based on whether the conditions involve space (point versus region), time ( point versus interval), and object id. The categories are based on the various combinations of these features. We describe the types of queries as Relational Calculus expressions, based on the query constraints. We focus on three main constraints: Spatial constraints, Temporal constraints, or/and moving object ID constraints. For each types of query, we identify the types of results, and give examples to clarify the query types. This work can define a benchmark for the performance of different types of systems and indexes that are designed to answer queries on Network-constrained moving objects data. Certain indexes/systems may work well for some query categories but perform poorly for other types of queries.

关键词： moving objects databases query categories constrained networks benchmarking data models

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PutMode: prediction of uncertain trajectories in moving objects databases

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APPLIED INTELLIGENCE 2010年第3期33卷 370-386页

作者： Qiao, Shaojie Tang, Changjie Jin, Huidong Long, Teng Dai, Shucheng Ku, Yungchang Chau, Michael SW JiaoTong Univ Sch Informat Sci & Technol Chengdu 610031 Peoples R China Sichuan Univ Sch Comp Sci Chengdu 610065 Peoples R China Commonwealth Sci & Ind Res Org Canberra ACT 2601 Australia Yuan Ze Univ Dept Informat Management Taipei 320 Taiwan Univ Hong Kong Sch Business Pokfulam Hong Kong Peoples R China

Objective: Prediction of moving objects with uncertain motion patterns is emerging rapidly as a new exciting paradigm and is important for law enforcement applications such as criminal tracking analysis. However, existing algorithms for prediction in spatio-temporal databases focus on discovering frequent trajectory patterns from historical data. Moreover, these methods overlook the effect of some important factors, such as speed and moving direction. This lacks generality as moving objects may follow dynamic motion patterns in real life. Methods: We propose a framework for predicating uncertain trajectories in moving objects databases. Based on Continuous Time Bayesian Networks (CTBNs), we develop a trajectory prediction algorithm, called PutMode (Prediction of uncertain trajectories in moving objects databases). It comprises three phases: (i) construction of TCTBNs (Trajectory CTBNs) which obey the Markov property and consist of states combined by three important variables including street identifier, speed, and direction;(ii) trajectory clustering for clearing up outlying trajectories;(iii) predicting the motion behaviors of moving objects in order to obtain the possible trajectories based on TCTBNs. Results: Experimental results show that PutMode can predict the possible motion curves of objects in an accurate and efficient manner in distinct trajectory data sets with an average accuracy higher than 80%. Furthermore, we illustrate the crucial role of trajectory clustering, which provides benefits on prediction time as well as prediction accuracy.

关键词： Trajectory prediction CTBN Trajectory clustering moving objects databases

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Continuous nearest-neighbor queries with location uncertainty

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VLDB JOURNAL 2015年第1期24卷 25-50页

作者： Sistla, A. Prasad Wolfson, Ouri Xu, Bo Univ Illinois Dept Comp Sci Chicago IL USA HERE Chicago IL 60606 USA

In this paper, we consider the problem of evaluating the continuous query of finding the nearest objects with respect to a given point object among a set of moving point-objects. The query returns a sequence of answer-pairs, namely pairs of the form such that is a time interval and is the set of objects that are closest to during . When there is uncertainty associated with the locations of the moving objects, is the set of all the objects that are possibly the nearest neighbors. We analyze the lower bound and the upper bound on the maximum number of answer-pairs, for the certain case and the uncertain case, respectively. Then, we consider two different types of algorithms. The first is off-line algorithms that compute a priori all the answer-pairs. The second type is on-line algorithms that at any time return the current answer-pair. We present algorithms for the certain case and the uncertain case, respectively, and analyze their complexity. We experimentally compare different algorithms using a database of 1 million objects derived from real-world GPS traces.

关键词： moving objects databases Trajectories Nearest-neighbor queries Continuous queries Uncertainty management

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