On the Support of Mobility in ORDBMS

On the Support of Mobility in ORDBMS

Nikos Pelekis (Department of Statistics and Insurance Science, University of Piraeus, Piraeus, Greece), Elias Frentzos (Department of Informatics, University of Piraeus, Piraeus, Greece), Nikos Giatrakos (Department of Informatics, University of Piraeus, Piraeus, Greece) and Yannis Theodoridis (Department of Informatics, University of Piraeus, Piraeus, Greece)
Copyright: © 2014 |Pages: 27
DOI: 10.4018/ijkbo.2014010103

Abstract

Composition of space and mobility in a unified data framework results into Moving Object Databases (MOD). MOD management systems support storage and query processing of non-static spatial objects and provide essential operations for higher level analysis of movement data. The goal of this paper is to present Hermes MOD engine that supports the aforementioned functionality through appropriate data types and methods in Object-Relational DBMS (ORDBMS) environments. In particular, Hermes exploits on the extensibility interface of ORDBMS that already have extensions for static spatial data types and methods that follow the Open Geospatial Consortium (OGC) standard, and extends the ORDBMS by supporting time-varying geometries that change their position and/or extent in space and time dimensions, either discretely or continuously. It further extends the data definition and manipulation language of the ORDBMS with spatio-temporal semantics and functionality.
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Introduction

Due to the explosion of mobile devices, the positioning technologies and the low data storage cost, one of the most important assets of knowledge intensive organizations working with movement data, traffic engineering, climatology, social anthropology and zoology, studying vehicle position data, hurricane track data, human and animal movement data, respectively etc.) is the data itself. Spatial database research has focused on supporting the modeling and querying of geometries associated with objects in a database (Güting, 1994). Regarding static spatial data, the major commercial as well as open source database management systems (e.g., DB2, MySQL, Oracle, Postgis, SQL Server) already provide appropriate data management and querying mechanisms that conform to Open Geospatial Consortium (OGC) standards (Open Geospatial Consortium, 2010). On the other hand, temporal databases have focused on extending the knowledge kept in a database about the current state of the real world to include the past, in the two senses of “the past of the real world” (valid time) and “the past states of the database” (transaction time) (Tansel et al., 1993). About a decade’s effort attempts to achieve an appropriate kind of interaction between both sub-areas of database research. Spatio-temporal databases are the outcome of the aggregation of time and space into a single framework (Koubarakis, & Sellis, 2003) with up-to-date reviews of spatio-temporal models and systems proposed in the literature found in Pelekis, Theodoulidis, Kopanakis, and Theodoridis (2004) and Frentzos, Pelekis, Ntoutsi, and Theodoridis (2008), respectively. As delineated in these papers, a serious weakness of existing approaches is that each of them deals with few common characteristics found across a number of specific applications. Thus the applicability of each approach to different cases, fails on spatio-temporal behaviors not anticipated by the application used for the initial model development. For the previous reasons, the field of the MOD has emerged (Güting, 2000), and has been shown (Pelekis et al., 2004) that it presents the most desirable properties among the proposals. However, although a lot of research has been carried out in the field of MOD, the efforts are independent trying to deal with specific problems and do not pay attention into embedding the proposed solutions (i.e. query processing algorithms) on top of existing DBMS where real world organizations base on. Towards this direction, the pioneer work of Güting et al. (2000), Forlizzi, Güting, Nardelli, and Schneider (2000), Lema, Forlizzi, Güting, Nardelli, and Schneider (2003) have proposed the SECONDO system (Almeida, Güting, & Behr, 2006). However, SECONDO in contradiction to our approach is a stand-alone system, built from scratch, its design does not utilize the provided spatial extensions of existing ORDBMS, it does not conform to the OGC standards as it does not follow any predefined data model (Dieker, & Güting, 2000) and as such it is not embeddable into the DBMS infrastructure of an organization, where pure static spatial, as well as other types of data is stored.

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