OPTIMIZING CLIENT-SERVER COMMUNICATION FOR REMOTE SPATIAL DATABASE ACCESS

Technological advances in recent years have opened ways for easier creation of spatial data. Every day, vast amounts of data are collected by both governmental institutions (e.g., USGS, NASA) and commercial entities (e.g., IKONOS). This process is driven by increased popularity and affordability across the whole spectrum of collection methods, ranging from personal GPS units to satellite systems. Many collection methods such as satellite systems produce data in raster format. Often, such raster data is analyzed by the researchers directly, while at other times such data is used to produce the final dataset in vector format. With the rapidly increasing supply of data, more applications for this data are being developed that are of interest to a wider consumer base. The increasing popularity of spatial data viewers and query tools with end users introduces a requirement for methods to allow these basic users to access this data for viewing and querying instantly and without much effort. In our work, we focus on providing remote access to vector-based spatial data, rather than raster data. We explore new ways of allowing visualization of both spatial and non-spatial data stored in a central server database on a simple client connected to this server by possibly a slow and unreliable connection. We considered usage scenarios where transferring the whole database for processing on the client was not feasible. This is due to the large volume of data stored on the server as well as a lack of computing power on the client and a slow link between the two. We focus on finding an optimal way of distributing work between the server, clients, and possibly other entities introduced into the model for query evaluation and data management. We address issues of scalability for clients that have only limited access to system resources (e.g., a Java applet). Methods to allow these clients to provide an interactive user interface, even for databases of arbitrary size, are also examined

MusA: Using Indoor Positioning and Navigation to Enhance Cultural Experiences in a museum

In recent years there has been a growing interest into the use of multimedia mobile guides in museum environments. Mobile devices have the capabilities to detect the user context and to provide pieces of information suitable to help visitors discovering and following the logical and emotional connections that develop during the visit. In this scenario, location based services (LBS) currently represent an asset, and the choice of the technology to determine users' position, combined with the definition of methods that can effectively convey information, become key issues in the design process. In this work, we present MusA (Museum Assistant), a general framework for the development of multimedia interactive guides for mobile devices. Its main feature is a vision-based indoor positioning system that allows the provision of several LBS, from way-finding to the contextualized communication of cultural contents, aimed at providing a meaningful exploration of exhibits according to visitors' personal interest and curiosity. Starting from the thorough description of the system architecture, the article presents the implementation of two mobile guides, developed to respectively address adults and children, and discusses the evaluation of the user experience and the visitors' appreciation of these application

A Taxonomy of Data Grids for Distributed Data Sharing, Management and Processing

Data Grids have been adopted as the platform for scientific communities that need to share, access, transport, process and manage large data collections distributed worldwide. They combine high-end computing technologies with high-performance networking and wide-area storage management techniques. In this paper, we discuss the key concepts behind Data Grids and compare them with other data sharing and distribution paradigms such as content delivery networks, peer-to-peer networks and distributed databases. We then provide comprehensive taxonomies that cover various aspects of architecture, data transportation, data replication and resource allocation and scheduling. Finally, we map the proposed taxonomy to various Data Grid systems not only to validate the taxonomy but also to identify areas for future exploration. Through this taxonomy, we aim to categorise existing systems to better understand their goals and their methodology. This would help evaluate their applicability for solving similar problems. This taxonomy also provides a "gap analysis" of this area through which researchers can potentially identify new issues for investigation. Finally, we hope that the proposed taxonomy and mapping also helps to provide an easy way for new practitioners to understand this complex area of research.Comment: 46 pages, 16 figures, Technical Repor

A Stochastic Model of Plausibility in Live-Virtual-Constructive Environments

Distributed live-virtual-constructive simulation promises a number of benefits for the test and evaluation community, including reduced costs, access to simulations of limited availability assets, the ability to conduct large-scale multi-service test events, and recapitalization of existing simulation investments. However, geographically distributed systems are subject to fundamental state consistency limitations that make assessing the data quality of live-virtual-constructive experiments difficult. This research presents a data quality model based on the notion of plausible interaction outcomes. This model explicitly accounts for the lack of absolute state consistency in distributed real-time systems and offers system designers a means of estimating data quality and fitness for purpose. Experiments with World of Warcraft player trace data validate the plausibility model and exceedance probability estimates. Additional experiments with synthetic data illustrate the model\u27s use in ensuring fitness for purpose of live-virtual-constructive simulations and estimating the quality of data obtained from live-virtual-constructive experiments

Geoprocessing Optimization in Grids

Geoprocessing is commonly used in solving problems across disciplines which feature geospatial data and/or phenomena. Geoprocessing requires specialized algorithms and more recently, due to large volumes of geospatial databases and complex geoprocessing operations, it has become data- and/or compute-intensive. The conventional approach, which is predominately based on centralized computing solutions, is unable to handle geoprocessing efficiently. To that end, there is a need for developing distributed geoprocessing solutions by taking advantage of existing and emerging advanced techniques and high-performance computing and communications resources. As an emerging new computing paradigm, grid computing offers a novel approach for integrating distributed computing resources and supporting collaboration across networks, making it suitable for geoprocessing. Although there have been research efforts applying grid computing in the geospatial domain, there is currently a void in the literature for a general geoprocessing optimization. In this research, a new optimization technique for geoprocessing in grid systems, Geoprocessing Optimization in Grids (GOG), is designed and developed. The objective of GOG is to reduce overall response time with a reasonable cost. To meet this objective, GOG contains a set of algorithms, including a resource selection algorithm and a parallelism processing algorithm, to speed up query execution. GOG is validated by comparing its optimization time and estimated costs of generated execution plans with two existing optimization techniques. A proof of concept based on an application in air quality control is developed to demonstrate the advantages of GOG

IT SOLUTIONS FOR THE MANAGEMENT OF GEO-BUSINESS

In the current economic and socio-demographic context, the pressure exerted over the informatic departments by the top management in order to have them offer a high volume of information in a short time, efficient for maintaining and developing the businegeo-business informatic systems, indicators cost, european integration, management of geo-spatial data, geomarketing