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30th International Conference on database and Expert Systems Applications (DEXA)

作者： Dan, Tangpeng Luo, Changyin Li, Yanhong Zhang, Chenyuan Cent China Normal Univ Sch Comp Wuhan Peoples R China Cent China Normal Univ Hubei Prov Key Lab Artificial Intelligence & Smar Wuhan Peoples R China Cent China Normal Univ Natl Language Resources Monitor & Res Ctr Network Wuhan Peoples R China South Cent Univ National Coll Comp Sci Wuhan Peoples R China

ISBN: (纸本)9783030276188;9783030276171

The trajectory similarity join aims to find similar trajectory pairs from two large collections of trajectories. This join targets applications such as trajectory near-duplicate detection, ridesharing recommendation and so on. Extensive works have been conducted on addressing this join. However, most of them only focus on spatial dimension without combining temporal range together. To address problem, this paper proposes a novel two-level grid index which takes both spatial and temporal range into account when processing spatial-temporal similarity join, and signature based dynamic grid warping (SDGW) approach to evaluate the spatial similarity for trajectory pairs. Some pruning approaches are developed to improve the query processing. In addition, extensive experiments are conducted to verify the efficiency and scalability of our methods.

关键词： spatial-temporal database Two-level grid index Trajectory similarity join

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spatial-temporal database Based Asynchronous Operation Approach of Fruit-Harvesting Robots 8th

Spatial-Temporal Database Based Asynchronous Operation Appro...

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8th International Conference on Intelligent Robotics and Applications (ICIRA)

作者： Zhou, Bin Gong, Liang Chen, Qianli Zhao, Yuanshen Ling, Xiao Liu, Chengliang Shanghai Jiao Tong Univ Dept Mech & Elect Engn Shanghai 200240 Peoples R China

ISBN: (纸本)9783319228730;9783319228723

Autonomous fruit-harvesting robots encounter difficulties of low fruit recognition rate and picking efficiency due to the complex unstructured operational environment. To solve this problem, an asynchronous approach has been proposed to discriminate the recognition and manipulation process. The fruit recognition task can be intensified via repetitious inspection or human-robot interaction, meanwhile a spatial-temporal database is constructed to record the recognition information which might facilitate the sequential picking manipulation. In this paper the attributes of a spatial-temporal object are firstly investigated with four elementary constituents attached. Hereby the fruit target is modeled for harvest decision-making. Secondly a three layer database management system is designed as per the modular design principles. Finally, we introduced a picking scheduling application based on this database management system. The picking schedule demonstrates that the Construction of the spatialtemporal database paves the way for the success of paradigm shift from synchronous to asynchronous manipulations of fruit-harvesting robots.

关键词： spatial-temporal database Fruit-harvesting robot Asynchronous Intelligence fusion

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A feature based method for trajectory dataset segmentation and profiling

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WORLD WIDE WEB-INTERNET AND WEB INFORMATION SYSTEMS 2017年第1期20卷 5-22页

作者： Jiang, Wei Zhu, Jie Xu, Jiajie Li, Zhixu Zhao, Pengpeng Zhao, Lei Soochow Univ Suzhou 215006 Peoples R China

The pervasiveness of location-acquisition and mobile computing techniques has generated massive spatial trajectory data, which has brought great challenges to the management and analysis of such a big data. In this paper, we focus on the sub-trajectory dataset profiling problem, and aim to extract the representative sub-trajectories from the raw trajectory as a subset, called profile, which can best describe the whole dataset. This problem is very challenging subject to finding the most representative sub-trajectories set by trading off the size and quality of the profile. To tackle this problem, we model the features of the trajectory dataset from the aspects of density, speed and the direction flow. Meanwhile we present our two-step method to select the representative trajectories based on the feature model. First, a novel trajectory segmentation algorithm is applied on a raw trajectory to identify the representative segments concerning their feature representativeness and automatically estimate the number of segments and the segment borders. Then, a sub-trajectory profiling method is performed to yield the most representative sub-trajectories in the dataset, based on a local heuristic evolution strategy. We evaluate our method based on extensive experiments by using two real-world trajectory datasets generated by over 12,000 taxicabs in Beijing and Shanghai. The results demonstrate the efficiency and effectiveness of our methods in different applications.

关键词： spatial-temporal database Trajectory Trajectory segmentation Data profiling

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TOF: A Throughput Oriented Framework for spatial Queries Processing in Multi-core Environment 20th

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20th International Conference on database Systems for Advanced Applications (DASFAA)

作者： Xue, Zhong-Bin Zhou, Xuan Wang, Shan Renmin Univ China Key Lab DEKE MOE Beijing 100872 Peoples R China Renmin Univ China Sch Informat Beijing 100872 Peoples R China

ISBN: (纸本)9783319181233;9783319181226

In this paper, we develop a Throughput Oriented Framework (TOF) for efficient processing of spatiotemporal queries in multicore environment. Traditional approaches to spatial query processing were focused on reduction of query latency. In real world, most LBS applications emphasize throughput rather than query latency. TOF is designed to achieve maximum throughput. Instead of resorting to complex indexes, TOF chooses to execute a batch queries at each run, so it can maximize data locality and parallelism on multi-core platforms. Using TOF, we designed algorithms for processing range queries and kNN queries respectively. Experimental study shows that these algorithms outperform the existing approaches significantly in terms of throughput.

关键词： Multi-core Large update rates Real-time response High throughput Batch query spatial-temporal database

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ATTI: Workload-Aware Query Adaptive OcTree Based Trajectory Index

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IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS 2013年第3期E96D卷 643-654页

作者： Meng, Xiangxu Wang, Xiaodong Li, Xinye Natl Univ Def Technol Natl Lab Parallel & Distributed Proc Changsha Hunan Peoples R China

The GPS trajectory databases serve as bases for many intelligent applications that need to extract some trajectories for future processing of mining. When doing such tasks, spatio-temporal range queries based methods, which find all sub-trajectories within the given spatial extent and time interval, are commonly used. However, the history trajectory indexes of such methods suffer from two problems. First, temporal and spatial factors are not considered simutaneously, resulting in low performance when processing spatio-temporal queries. Second, the efficiency of indexes is sensitive to query size. The query performance changes dramatically as the query size changed. This paper proposes workload-aware Adaptive OcTree based Trajectory clustering Index (ATTI) aiming at optimizing trajectory storage and index performance. The contributions are three-folds. First, the distribution and time delay of the trajectory storage are introduced into the cost model of spatio-temporal range query;Second, the distribution of spatial division is dynamically adjusted based on UPS update workload;Third, the query workload adaptive mechanism is proposed based on virtual OcTree forest. A wide range of experiments are carried out over Microsoft GeoLife project dataset, and the results show that query delay of ATTI could be about 50% shorter than that of the nested index.

关键词： spatial-temporal database trajectory workload-aware adaptive

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Re-engineering of the forest stand database:case study of Bilahe Forestry Bureau,Inner Mongolia of China

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Journal of Forestry Research 2008年第3期19卷 231-234页

作者：陈文波郑蕉江西农业大学景观与环境生态研究中心南昌330045 江西农业大学计算机信息与工程学院南昌330045

The forest stand database of Bilahe Forestry Bureau, Inner Mongolia of China was taken as an example to demonstrate the whole process of building a temporal geodatabase by means of reengineering. The process was composed of establishing a conceptual data model from the initial database, constructing a logical database by means of mapping, and building a temporal geodatabase with the help of Computer-Aided Software Engineering （CASE） tool and Unified Markup Language （UML）. The results showed that as the reengineered forest stand geodatabase was dynamic, it could easily store the historical data and answer time related questions by Structured Query Language （SQL）, meanwhile, it maintains the integrity of database and eliminates the redundancy.

关键词： re-engineering spatial-temporal database CASE tool forest stand

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Efficient algorithms for similarity and skyline summary on multidimensional datasets

Efficient algorithms for similarity and skyline summary on m...

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作者： Morse, Michael David University of Michigan

学位级别：Ph.D.

Efficient management of large multidimensional datasets has attracted much attention in the database research community. Such large multidimensional datasets are common and efficient algorithms are needed for analyzing these data sets for a variety of applications. In this thesis, we focus our study on two very common classes of analysis: similarity and skyline summarization. We first focus on similarity when one of the dimensions in the multidimensional dataset is temporal. We then develop algorithms for evaluating skyline summaries effectively for both temporal and low-cardinality attribute domain datasets and propose different methods for improving the effectiveness of the skyline summary operation. This thesis begins by studying similarity measures for time-series datasets and efficient algorithms for time-series similarity evaluation. The first contribution of this thesis is a new algorithm, called the Fast Time Series Evaluation (FTSE) method, which can be used to evaluate similarity methods whose matching criteria is bounded by a specified &epsis; threshold value. We then show that FTSE can be used in a framework that can evaluate a rich range of &epsis; threshold-based scoring techniques which we call the Sequence Weighted Alignment (Swale) method. The second contribution of this thesis is the development of a new time-interval skyline operator, which continuously computes the current skyline over a data stream. We present a new algorithm called Lookout for evaluating such queries efficiently, and empirically demonstrate the scalability of this algorithm. In addition, we also examine the effect of the underlying spatial index structure when evaluating skylines. Whereas previous work on skyline computations have only considered using the R*-tree index structure, we show that for skyline computations using an underlying quadtree has significant performance benefits over an R*-tree index. Current skyline evaluation techniques follow a common paradigm that elimi

关键词： Computer Science database System Skyline Query Processing Time-Series Similarity spatial-temporal database Thesis

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