Large Scale Indexing of Geofences

Abstract

The modern smart phone and car concepts provide a fertile ground for new location-aware applications, ranging from traffic management to social services. While the functionality is partly implemented at the mobile terminal, there is a rising need for efficient backend processing of high-volume, high update rate location streams. It is in this environment that geofencing, the detection of objects traversing virtual fences, is becoming a universal primitive required by an ever-growing number of applications.To satisfy the functionality and performance requirements of large-scale geofencing applications, we present in this work a backend system for indexing massive quantities of mobile objects and geofences. Our system runs on a cluster of servers, achieving a throughput of location updates that scales linearly with number of machines. The key ingredients to achieve a high performance are a specialized spatial index, a dynamic caching mechanism, and a load-sharing principle that reduces communication overhead to a minimum and enables a shared-nothing architecture. The throughput of the spatial index as well as the performance of the overall system are demonstrated by experiments using simulations of large-scale geofencing applications.

Infrastructure-Assisted Geofencing: Proactive Location-Based Services with Thin Mobile Clients and Smart Servers

“…Nowadays, Geofencing is associated with two main technical challenges: Reducing the energy consumption at the mobile device within the mobile-based solution [19], [20], [21], [22] and allowing the matching process within the centralized solution to scale [23], [24], [25]. The high energy consumption is mainly caused by the positioning modules and is tackled by selecting an appropriate positioning technique based on the needed accuracy [19], [20], the current environment [21] or by adapting the location update frequency according to the speed towards a geofence [22].…”