26 research outputs found
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Space transformation for understanding group movement
We suggest a methodology for analyzing movement behaviors of individuals moving in a group. Group movement is analyzed at two levels of granularity: the group as a whole and the individuals it comprises. For analyzing the relative positions and movements of the individuals with respect to the rest of the group, we apply space transformation, in which the trajectories of the individuals are converted from geographical space to an abstract 'group space'. The group space reference system is defined by both the position of the group center, which is taken as the coordinate origin, and the direction of the group's movement. Based on the individuals' positions mapped onto the group space, we can compare the behaviors of different individuals, determine their roles and/or ranks within the groups, and, possibly, understand how group movement is organized. The utility of the methodology has been evaluated by applying it to a set of real data concerning movements of wild social animals and discussing the results with experts in animal ethology
Yellow Tree: A Distributed Main-memory Spatial Index Structure for Moving Objects
Mobile devices equipped with wireless technologies to communicate and positioning systems to locate objects of interest are common place today, providing the impetus to develop location-aware applications. At the heart of location-aware applications are moving objects or objects that continuously change location over time, such as cars in transportation networks or pedestrians or postal packages. Location-aware applications tend to support the tracking of very large numbers of such moving objects as well as many users that are interested in finding out about the locations of other moving objects. Such location-aware applications rely on support from database management systems to model, store, and query moving object data. The management of moving object data exposes the limitations of traditional (spatial) database management systems as well as their index structures designed to keep track of objects\u27 locations. Spatial index structures that have been designed for geographic objects in the past primarily assume data are foremost of static nature (e.g., land parcels, road networks, or airport locations), thus requiring a limited amount of index structure updates and reorganization over a period of time. While handling moving objects however, there is an incumbent need for continuous reorganization of spatial index structures to remain up to date with constantly and rapidly changing object locations. This research addresses some of the key issues surrounding the efficient database management of moving objects whose location update rate to the database system varies from 1 to 30 minutes. Furthermore, we address the design of a highly scaleable and efficient spatial index structure to support location tracking and querying of large amounts of moving objects. We explore the possible architectural and the data structure level changes that are required to handle large numbers of moving objects. We focus specifically on the index structures that are needed to process spatial range queries and object-based queries on constantly changing moving object data. We argue for the case of main memory spatial index structures that dynamically adapt to continuously changing moving object data and concurrently answer spatial range queries efficiently. A proof-of concept implementation called the yellow tree, which is a distributed main-memory index structure, and a simulated environment to generate moving objects is demonstrated. Using experiments conducted on simulated moving object data, we conclude that a distributed main-memory based spatial index structure is required to handle dynamic location updates and efficiently answer spatial range queries on moving objects. Future work on enhancing the query processing performance of yellow tree is also discussed
Domain Indices in Oracle 11g
Diplomová práce se zabĂ˝vá problematikou domĂ©novĂ˝ch indexĹŻ v Oracle Database 11g. Popisuje architekturu databáze a rozebĂrá dostupnĂ© moĹľnosti indexovánĂ. Jsou zde vysvÄ›tleny konkrĂ©tnĂ zpĹŻsoby implementace a pouĹľitĂ domĂ©novĂ˝ch indexĹŻ, dále rozebĂrány zpĹŻsoby indexovánĂ ÄŤasoprostorovĂ˝ch dat, pĹ™edevšĂm struktura TB-stromu, která je následnÄ› implementována v podobÄ› domĂ©novĂ©ho indexu. Spolu s domĂ©novĂ˝m indexem jsou implementovány takĂ© operátory, pomocĂ kterĂ˝ch je index následnÄ› vyuĹľĂván a testován.This thesis deals with the domain indexes in Oracle Database 11g. It describes the database architecture and discusses the available methods of indexing. There are explained concrete ways of the implementation and use of domain indexes, also discussed ways of indexing spatio-temporal data especially the TB-tree structure, which is then implemented as a domain index. Along with the domain index operators are also implemented by means of which the index is subsequently used and tested.