Large numbers of mobile objects and continuous queries about them characterize mobile object applications. Efficient and parallel evaluation of queries about mobile objects that continuously move is important for achieving acceptable... more
Large numbers of mobile objects and continuous queries about them characterize mobile object applications. Efficient and parallel evaluation of queries about mobile objects that continuously move is important for achieving acceptable response times. In such applications, the traditional approaches suffer from the need for parallel updates processing and real time querying and visualization. This results in poor performance in such critical systems. The emerging multicore and manycore microprocessing technologies have the potential to offer scalable performance improvement. How to explore the multicore resources to speed up mobile objects applications is thus a natural question but also a huge challenge for Moving Objects Applications (MOA). In this paper, we propose and evaluate a methodology to explore parallelism via multi-threading, transactional loosely coupled methodology design, and to implement it on multicore processors for Moving Objects Applications. We apply the proposed ...
In the light of rapidly growing repositories capturing the movement trajectories of people in spacetime, the need for trajectory compression becomes obvious. This paper argues for semantic trajectory compression (STC) as a means of... more
In the light of rapidly growing repositories capturing the movement trajectories of people in spacetime, the need for trajectory compression becomes obvious. This paper argues for semantic trajectory compression (STC) as a means of substantially compressing the movement trajectories in an urban environment with acceptable information loss. STC exploits that human urban movement and its large–scale use (LBS, navigation) is embedded in some geographic context, typically defined by transportation networks. STC ...
We consider spatial databases in the topological data model, ie, databases that consist of a finite number of labeled regions in the real plane. Such databases partition the plane further into elementary regions. We propose a first-order... more
We consider spatial databases in the topological data model, ie, databases that consist of a finite number of labeled regions in the real plane. Such databases partition the plane further into elementary regions. We propose a first-order language, which uses elementary-region variables and label variables, to query spatial databases. All queries expressible in this first-order logic are topological\/and they can be evaluated in polynomial time. Furthermore, the proposed language is powerful enough to distinguish between any two spatial databases ...
