Location Driven Edge Assisted Device and Solutions for Intelligent Transportation
Saravjeet Singh, Jaiteg Singh · 2020
Abstract: With the development of the internet and mobile computing, software applications are migrating toward cloud computing and are using cloud services in different forms. Huge demand for centralized cloud computing poses severe challenges like degraded spectral efficiency, high latency, poor connection, and security issues. To handle these issues, fog computing and edge computing has come into existence. One application of cloud computing is Location Based Services (LBS). Intelligent transport systems being the important application of LBS are relying on the GPS, sensors, and spatial database for convenient transport facilities. These location-based applications are highly dependent on some external system like GPS device and map APIs (cloud support) for the spatial data and location information. These applications fetch spatial data using APIs from different proprietary service providers. The dependency on the APIs and GPS devices, create challenges for effective fleet management and routing process in the dead zones. Dead zones are the areas where no cellular coverage exists. Without the cellular data, devices are unable to fetch spatial data (from the cloud) for route finding and fleet management, similarly without the GPS signal devices cannot update the current location information. Using fog and edge computing we can counter this problem. Utilizing fog and edge computing for transportation applications can prevent issues related to dead zones and performance. In this chapter, we explained our approach to use edge computing in transportation and route-finding process so as to handle the performance issues.