Processing Of Location-dependent Queries Research Articles

Probabilistic location-dependent queries at different location granularities

Approaches for the processing of location-dependent queries usually assume that the location data are expressed precisely, usually using GPS locations. However, this is unrealistic because positioning methods do not have a perfect accuracy (e.g., the positioning approach used in cellular networks handles only the cell where mobile users are located). Besides, users may need to express queries based on concepts of locations other than traditional GPS locations, which we call location granules.In this paper, we focus on location granule-based query processing (i.e., processing of queries with location granules) in situations where the location data available is imprecise, which we have called probabilistic location-dependent queries. For that purpose, we exploit the concept of uncertainty location granule, which represents the location uncertainty of an object. In particular, we tackle the problem of processing probabilistic inside (range) constraints. We analyze in detail how those constraints can be processed, taking into account both the existence of location uncertainty affecting the relevant objects and the location granularity specified. An extensive experimental evaluation shows the feasibility of the proposed probabilistic query processing approach and analyzes the advantages of using index structures to speed up the query processing.

Answering Continuous Description Logic Queries

During the last years, mobile computing has been the focus of many research efforts, due mainly to the ever-growing use of mobile devices. In this context, there is a need to manage dynamic data, such as location data or other data provided by sensors. As an example, the continuous processing of location-dependent queries has been the subject of thorough research. However, there is still a need of highly expressive ways of formulating queries, augmenting in this way the systems' answer capabilities. Regarding this issue, the modeling power of Description Logics (DLs) and the inferring capabilities of their attached reasoners could fulfill this new requirement. The main problem is that DLs are inherently oriented to model static knowledge, that is, to capture the nature of the modeled objects, but not to handle changes in the property values (which requires a full ontology reclassification), as it is common in mobile computing environments (e.g., the location is expected to vary continually). In this paper, the authors present a novel approach to process continuous queries that combines 1) the DL reasoning capabilities to deal with static knowledge, with 2) the efficient data access provided by a relational database to deal with volatile knowledge. By marking at modeling time the properties that are expected to change during the lifetime of the queries, the authors'system is able to exploit both the results of the classification process provided by a DL reasoner, and the low computational costs of a database when accessing changing data (mobile environments, semantic sensors, etc.), following a two-step continuous query processing that enables us to handle continuous DL queries efficiently. Experimental results show the feasibility of the authors' approach.

A PostgreSQL extension for continuous path and range queries in indoor mobile environments

Continuous location-dependent queries are key elements for the development of location-based and context-aware services. While most work on location-dependent query processing has been mainly oriented towards outdoor environments, this paper develops an approach for the continuous processing of location-dependent queries over indoor moving objects. A prototype for handling those queries has been developed as an extension for the open-source DBMS PostgreSQL. Several algorithms for the continuous processing of path searches and range queries applied to both static and moving objects are performed on top of a hierarchical and context-dependent data model. Experimental results have been conducted to report our findings.

Probabilistic nearest neighbor queries of uncertain data via wireless data broadcast

Most existing location-dependent query processing methods are based on the client-server model. However, due to the increasing nubmer of smart mobile devices, there can be a large volume of data being processed on the server side and the server can be system performance bottleneck. This paper takes the first step towards processing probabilistic nearest neighbor queries of uncertain data objects via wireless data broadcast (BPNN). Our method leverages the key properties of Voronoi Diagrams for Uncertain Data (UV-Diagram). To preserve the good properties of UV-Diagram, according to the property of Hilbert curve, UV-Hilbert-Partition is proposed to partition the UV-Diagram into several grid cells, called Hilbert-Cells, which have good locality-preserving behavior. Then a special organizing method is proposed. For a certain UV-Diagram, the CellFrame structure, which can be located based on the coordinates of a query client, is used to efficiently minimize the broadcast cycle and keep the probabilistic nearest neighbor results. Based on the sequence of the CellFrames, a distributed index, called UVHilbert-DI, is proposed to support BPNN query processing. Finally, the efficient BPNN algorithms based on UVHilbert-DI is presented and extensive experiments have been conducted to demonstrate the performance of our approaches.

Context-aware modelling of continuous location-dependent queries in indoor environments

Emerging and continuing advances in ambient systems and localization techniques have brought novel opportunities to develop context-aware navigation services in indoor environments. Diverse kinds of services delivered to the users can be provided by enabling real-time integration of contextual dimensions. In particular, continuous location-dependent queries can be considered as key elements for the development of different categories of context-aware services. However, most work on location-dependent query processing has been mainly oriented towards outdoor environments. This paper introduces a generic architecture for continuous location-dependent and navigation-related queries in indoor environments. A multi-level model of space is designed by taking into account contextual information and the hierarchical layout of an indoor environment. The semantics of a query language for continuous location-dependent queries are introduced, along with some motivating sample queries.

Leveraging computation sharing and parallel processing in location-dependent query processing

A variety of research exists for the processing of continuous queries in large, mobile environments. Each method tries, in its own way, to address the computational bottleneck of constantly processing so many queries. In this paper, we introduce an efficient and scalable system for monitoring continuous queries by leveraging the parallel processing capability of the Graphics Processing Unit. We examine a naive CPU-based solution for continuous range-monitoring queries, and we then extend this system using the GPU. Additionally, with mobile communication devices becoming commodity, location-based services will become ubiquitous. To cope with the very high intensity of location-based queries, we propose a view oriented approach of the location database, thereby reducing computation costs by exploiting computation sharing amongst queries requiring the same view. Our studies show that by exploiting the parallel processing power of the GPU, we are able to significantly scale the number of mobile objects, while maintaining an acceptable level of performance.

Location-dependent query processing

The continuous development of wireless networks and mobile devices has motivated an intense research in mobile data services. Some of these services provide the user with context-aware information. Specifically, location-based services and location-dependent queries have attracted a lot of interest. In this article, the existing literature in the field of location-dependent query processing is reviewed. The technological context (mobile computing) and support middleware (such as moving object databases and data stream technology) are described, location-based services and location-dependent queries are defined and classified, and different query processing approaches are reviewed and compared.

Location-Dependent Query Processing Under Soft Real-Time Constraints

In recent years, mobile devices and applications achieved an increasing development. In database field, this development required methods to consider new query types like location-dependent queries (i.e. the query results depend on the query issuer location). Although several researches addressed problems related to location-dependent query processing, a few works considered timing requirements that may be associated with queries (i.e., the query results must be delivered to mobile clients on time). The main objective of this paper is to propose a solution for location-dependent query processing under soft real-time constraints. Hence, we propose methods to take into account client location-dependency and to maximize the percentage of queries respecting their deadlines. We validate our proposal by implementing a prototype based on Oracle DBMS. Performance evaluation results show that the proposed solution optimizes the percentage of queries meeting their deadlines and the communication cost.

A framework of web data integrated LBS middleware

In this paper, we propose a flexible location-based service (LBS) middleware framework to make the development and deployment of new location based applications much easier. Considering the World Wide Web as a huge data source of location-relative information, we integrate the common used web data extraction techniques into the middleware framework, exposing a unified web data interface for the upper applications to make them more attractive. Besides, the framework also emphasizes some common LBS issues, including posisitioning, location modeling, location-dependent query processing, privacy and secure management.

Location-dependent queries in mobile contexts: distributed processing using mobile agents

With the current advances of mobile computing technology, we are witnessing an explosion in the development of applications that provide mobile users with a wide range of services. In this paper, we present a system that supports distributed processing of continuous location-dependent queries in mobile environments. The system that we propose presents the following main advantages: 1) it is a general solution for the processing of location-dependent queries in scenarios where not only the users issuing queries, but also other interesting objects can move; 2) it performs an efficient processing of these queries in a continuous way; 3) it is especially well adapted to environments where location data are distributed in a network and processing tasks can be performed in parallel, allowing a high scalability; and 4) it optimizes wireless communications. We use mobile agents to carry the processing tasks wherever they are needed. Thus, agents are in charge of tracking the location of interesting moving objects and refreshing the answer to a query efficiently. We evaluate the usefulness of the presented proposal showing that the system achieves a good precision and scales up well

On the design of a location and query management strategy for mobile and wireless environments

The rapid development of wireless digital communication technology led to a new computing environment known as mobile or nomadic computing. Mobile computing no longer requires users to confine to wired network premises, but rather it enables users to access information regardless of their location. Mobility of mobile users poses a new class of problems in the fields of networking, operating systems, and databases. Location management and location dependent query processing are major challenges in mobile computing. Location management addresses the issue of continuously keeping track of the location of each user. This article presents the architecture for the location and query management based on distributed databases and distributed object management standards. The architecture is implemented using the common object request broker architecture (CORBA) and mobile IP standards.