Towards a Scalable Dynamic Spatial Database System

With the rise of GPS-enabled smartphones and other similar mobile devices, massive amounts of location data are available. However, no scalable solutions for soft real-time spatial queries on large sets of moving objects have yet emerged. In this paper we explore and measure the limits of actual algorithms and implementations regarding different application scenarios. And finally we propose a novel distributed architecture to solve the scalability issues.Comment: (2012

Fast Nearest Neighbor Search with Keywords Using IR2-Tree

Conventional abstraction queries, like vary search and nearest neighbor retrieval, involve alone conditions on objects geometric properties. Today, many trendy applications concern novel varieties of queries that aim to go looking out objects satisfying every a abstraction predicate, and a predicate on their associated texts. As associate example, instead of considering all the restaurants, a nearest neighbor question would instead provoke the eating place that is the nearest among those whose menus contain asteak, ˆ spaghetti, brandyaˆ all at identical time. Currently, the best answer to such queries depends on the IR2-tree, which, as shown throughout this paper, contains many deficiencies that seriously impact its efficiency. motivated by this, It tend to develop a latest access methodology called the abstraction inverted index that extends the traditional inverted index to subsume f-dimensional info, and comes with algorithms that will answer nearest neighbor queries with keywords in real time. As verified by experiments, the projected techniques trounce the IR2-tree in question latent amount considerably, generally by a part of orders of magnitude

SkyDOT (Sky Database for Objects in the Time Domain): A Virtual Observatory for Variability Studies at LANL

The mining of Virtual Observatories (VOs) is becoming a powerful new method for discovery in astronomy. Here we report on the development of SkyDOT (Sky Database for Objects in the Time domain), a new Virtual Observatory, which is dedicated to the study of sky variability. The site will confederate a number of massive variability surveys and enable exploration of the time domain in astronomy. We discuss the architecture of the database and the functionality of the user interface. An important aspect of SkyDOT is that it is continuously updated in near real time so that users can access new observations in a timely manner. The site will also utilize high level machine learning tools that will allow sophisticated mining of the archive. Another key feature is the real time data stream provided by RAPTOR (RAPid Telescopes for Optical Response), a new sky monitoring experiment under construction at Los Alamos National Laboratory (LANL).Comment: to appear in SPIE proceedings vol. 4846, 11 pages, 5 figure