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Proceedings ArticleDOI

Distributed Real-Time Processing of Range-Monitoring Queries in Heterogeneous Mobile Databases

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TLDR
This paper presents a distributed server infrastructure as opposed to the centralized approach in MQM to achieve scalability and robustness and allows mobile objects to adjust their computing capacity to reflect their processing capability at different time.
Abstract
The emergence of location-aware services calls for new efficient real-time queries processing algorithms. In this paper, we focus specifically on real-time processing of range-monitoring queries. Ying Cai et al. introduced a technique called monitoring query management (MQM) for efficient real-time processing of range-monitoring queries in heterogeneous mobile databases. The technique involves allowing the mobile objects to monitor their movement directly against nearby queries. Mobile objects need to update their locations to the server only when they move out of the assigned resident domain. In this paper, we present a distributed server infrastructure as opposed to the centralized approach in MQM to achieve scalability and robustness. In addition, to add flexibility to MQM technique, we allow mobile objects to adjust their computing capacity to reflect their processing capability at different time.

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Journal Article

MobiEyes: Distributed processing of continuously moving queries on moving objects in a mobile system

TL;DR: This paper introduces a set of optimization techniques, such as Lazy Query Propagation, Query Grouping, and Safe Periods, to constrict the amount of computations handled by the moving objects and to enhance the performance and system utilization of Mobieyes.
Proceedings ArticleDOI

Leveraging Computation Sharing and Parallel Processing in Location-Based Services

TL;DR: This paper introduces an efficient and scalable system for monitoring continuous queries by leveraging the parallel processing capability of the Graphics Processing Unit, and proposes a view oriented approach of the location database, thereby reducing computation costs by exploiting computation sharing amongst queries requiring the same view.
Journal ArticleDOI

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

TL;DR: This paper introduces an efficient and scalable system for monitoring continuous queries by leveraging the parallel processing capability of the Graphics Processing Unit, and proposes a view oriented approach of the location database, thereby reducing computation costs by exploiting computation sharing amongst queries requiring the same view.
References
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Proceedings ArticleDOI

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TL;DR: This paper presents an efficient branch-and-bound R-tree traversal algorithm to find the nearest neighbor object to a point, and then generalizes it to finding the k nearest neighbors.
Proceedings ArticleDOI

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TL;DR: This paper proposes techniques that solve the problem by performing a single query for the whole input segment, and proposes analytical models for the expected size of the output, as well as the cost of query processing, and extend out techniques to several variations of the problem.
Proceedings ArticleDOI

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TL;DR: Experimental results show that SINA is scalable and is more efficient than other index-based spatio-temporal algorithms.
Proceedings ArticleDOI

SEA-CNN: scalable processing of continuous k-nearest neighbor queries in spatio-temporal databases

TL;DR: Comprehensive experimentation shows that SEA-CNN is highly scalable and is more efficient in terms of both I/O and CPU costs in comparison to other R-tree-based CKNN techniques.
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