Benchmarking and Data Generation in Moving Objects Databases

Encyclopedia of Database Technologies and Applications ◽

10.4018/978-1-59140-560-3.ch005 ◽

2005 ◽

pp. 23-28 ◽

Cited By ~ 1

Author(s):

Theodoros Tzouramanis

Keyword(s):

Mobile Communication ◽

Moving Objects ◽

Query Languages ◽

Location Information ◽

Navigation Systems ◽

Data Generation ◽

Access Methods ◽

Future Projections ◽

Storage And Retrieval ◽

Moving Objects Databases

Moving objects databases (MODs) provide the framework for the efficient storage and retrieval of the changing position of continuously moving objects. This includes the current and past locations of moving objects and the support of spatial queries that refer to historical location information and future projections as well. Nowadays, new spatiotemporal applications that require tracking and recording the trajectories of moving objects online are emerging. Digital battlefields, traffic supervision, mobile communication, navigation systems, and geographic information systems (GIS) are among these applications. Towards this goal, during recent years many efforts have focused on MOD formalism, data models, query languages, visualization, and access methods (Guting et al., 2000; Saltenis & Jensen, 2002; Sistla, Wolfson, Chamberlain, & Dao, 1997). However, little work has appeared on benchmarking.

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Access methods in moving objects databases

Journal of Computer Applications ◽

10.3724/sp.j.1087.2010.01064 ◽

2010 ◽

Vol 30 (4) ◽

pp. 1064-1067 ◽

Cited By ~ 2

Author(s):

Hui XIAO ◽

Qing-quan LI

Keyword(s):

Moving Objects ◽

Access Methods ◽

Moving Objects Databases

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Anonymization of moving objects databases by clustering and perturbation

Information Systems ◽

10.1016/j.is.2010.05.003 ◽

2010 ◽

Vol 35 (8) ◽

pp. 884-910 ◽

Cited By ~ 74

Author(s):

Osman Abul ◽

Francesco Bonchi ◽

Mirco Nanni

Keyword(s):

Moving Objects ◽

Moving Objects Databases

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iCAMS2: Developing a Mobile Communication Tool Using Location Information and Schedule Information with J2ME

Lecture Notes in Computer Science - Human-Computer Interaction with Mobile Devices and Services ◽

10.1007/978-3-540-45233-1_36 ◽

2003 ◽

pp. 400-404 ◽

Cited By ~ 3

Author(s):

Yasuto Nakanishi ◽

Shouichi Kumazawa ◽

Takayuki Tsuji ◽

Katsuya Hakozaki

Keyword(s):

Mobile Communication ◽

Location Information ◽

Communication Tool

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Distributed temporary pseudonyms: A new approach for protecting location information in mobile communication networks

Computer Security — ESORICS 98 - Lecture Notes in Computer Science ◽

10.1007/bfb0055871 ◽

1998 ◽

pp. 295-312 ◽

Cited By ~ 14

Author(s):

Dogan Kesdogan ◽

Peter Reichl ◽

Klaus JunghÄrtchen

Keyword(s):

Communication Networks ◽

Mobile Communication ◽

Location Information ◽

New Approach ◽

Mobile Communication Networks

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DocBase

Innovations in Database Design, Web Applications, and Information Systems Management ◽

10.4018/978-1-4666-2044-5.ch014 ◽

2013 ◽

pp. 365-393

Author(s):

Arijit Sengupta ◽

Ramesh Venkataraman

Keyword(s):

Query Processing ◽

Query Language ◽

Formal Model ◽

Query Languages ◽

Prototype System ◽

Storage And Retrieval ◽

Visual Query Formulation ◽

Visual Query ◽

Nested Relations ◽

Entity Relationship

This chapter introduces a complete storage and retrieval architecture for a database environment for XML documents. DocBase, a prototype system based on this architecture, uses a flexible storage and indexing technique to allow highly expressive queries without the necessity of mapping documents to other database formats. DocBase is an integration of several techniques that include (i) a formal model called Heterogeneous Nested Relations (HNR), (ii) a conceptual model XER (Extensible Entity Relationship), (ii) formal query languages (Document Algebra and Calculus), (iii) a practical query language (Document SQL or DSQL), (iv) a visual query formulation method with QBT (Query By Templates), and (v) the DocBase query processing architecture. This paper focuses on the overall architecture of DocBase including implementation details, describes the details of the query-processing framework, and presents results from various performance tests. The paper summarizes experimental and usability analyses to demonstrate its feasibility as a general architecture for native as well as embedded document manipulation methods.

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Spatial and Spatiotemporal Data Types as a Foundation for Representing Space-Time Data in GIS

Advances in Geospatial Technologies - Handbook of Research on Geographic Information Systems Applications and Advancements ◽

10.4018/978-1-5225-0937-0.ch001 ◽

2017 ◽

pp. 1-28 ◽

Cited By ~ 1

Author(s):

Markus Schneider

Keyword(s):

Spatial Data ◽

Geographical Information Systems ◽

Moving Objects ◽

Spatial Databases ◽

Query Languages ◽

Geographical Information ◽

Spatiotemporal Data ◽

Data Types ◽

Time Data ◽

Use Of Data

A data type comprises a set of homogeneous values together with a collection of operations defined on them. This chapter emphasizes the importance of crisp spatial data types, fuzzy spatial data types, and spatiotemporal data types for representing static, vague, and time-varying geometries in Geographical Information Systems (GIS). These data types provide a fundamental abstraction for modeling the geometric structure of crisp spatial, fuzzy spatial, and moving objects in space and time as well as their relationships, properties, and operations. The goal of this chapter is to provide an overview and description of these data types and their operations that have been proposed in research and can be found in GIS, spatial databases, moving objects databases, and other spatial software tools. The use of data types, operations, and predicates will be illustrated by their embedding into query languages.

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