Continuous Spatial Query Processing

Abstract

In the past decade, positioning system-enabled devices such as smartphones have become most prevalent. This functionality brings the increasing popularity of location-based services in business as well as daily applications such as navigation, targeted advertising, and location-based social networking. Continuous spatial queries serve as a building block for location-based services. As an example, an Uber driver may want to be kept aware of the nearest customers or service stations. Continuous spatial queries require updates to the query result as the query or data objects are moving. This poses challenges to the query efficiency, which is crucial to the user experience of a service. A large number of approaches address this efficiency issue using the concept of safe region . A safe region is a region within which arbitrary movement of an object leaves the query result unchanged. Such a region helps reduce the frequency of query result update and hence improves query efficiency. As a result, safe region-based approaches have been popular for processing various types of continuous spatial queries. Safe regions have interesting theoretical properties and are worth in-depth analysis. We provide a comparative study of safe region-based approaches. We describe how safe regions are computed for different types of continuous spatial queries, showing how they improve query efficiency. We compare the different safe region-based approaches and discuss possible further improvements.

Hybrid Index Based on 3D-Grid TPR-Tree

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Monitoring Spatial Keyword Queries Based on Resident Domains of Mobile Objects in IoT Environments

“…For continuously monitoring spatial queries, the safe zone concept [21][22][23][24][25] was proposed to reduce frequent location updating from the mobile objects to the central server. A safe zone assigned to the mobile object is the area that contains the object and does not overlap the other query regions.…”