Locator: A Cloud-Fog-Enabled Framework for Facilitating Efficient Location based Services

Abstract

The key aspect of the intelligent transportation system (ITS) is efficient mobility analytics to understand the movement behaviours of citizens. However, any location-aware analytics is time and computation intensive. In this work, we propose a mobility and delay-aware cloud-fog enabled framework, named LOCATOR for efficient location-based service provisioning. LOCATOR helps to minimize the service-waiting time and service-provisioning time of location-based services such as food delivery, medical emergency by deploying an optimal matching algorithm in the MapReduce paradigm. The framework is implemented and evaluated on the Google Cloud Platform (GCP) using real-life mobility datasets. LOCATOR has shown significant improvements in execution time compared to the baseline methods.