Abstract
Fog computing, an extension of the Cloud Computing paradigm where routers themselves may provide the virtualisation infrastructure, aims at achieving fluidity when distributing in-network functions, in addition to allowing fast and scalable processing, and exchange of information. In this paper we present a fog computing architecture based on a “content island” which interconnects sets of “things” to exchange and process data among themselves or with other content islands. We then present a use case that focuses on a smartphone-based forward collision warning application for a connected vehicle scenario. This application makes use of the optical sensor of smartphones to estimate the distance between the device itself and other vehicles in its field of view. The vehicle travelling directly ahead is identified relying on the information from the GPS, camera, and inter-island communication. Warnings are generated at both content islands, if the driver does not maintain a predefined safe distance towards the vehicle ahead. Experiments performed with the application show that with the developed method, we are able to estimate the distance between vehicles, and the inter-island communication has a very low overhead, resulting in improved performance. On comparing our proposed solution based on edge/fog computing with a cloud-based api, it was observed that our solution outperformed the cloud-based api, thus making us optimistic of the utility of the proposed architecture.
Highlights
Vaquero et al [1] define fog computing as “a scenario where a huge number of heterogeneous ubiquitous and decentralised devices communicate and potentially cooperate among them and with the network to perform storage and processing tasks without the intervention of third parties
The basic architecture for computing, storage and networking for the Internet of Things (IoT) was presented by Bonomi et al [2], which included some information on cloud computing and fog computing, is one of the first works in this area. [3] lays emphasis on the new dimension that IoT adds to big data and analytics owing to the participation of a massive number of distributed fog nodes
Photographs of static vehicles were acquired from a parking area using an Android device, which were later processed by the device to estimate the distance from the lens of the camera to the license plate to validate the proposed method
Summary
Vaquero et al [1] define fog computing as “a scenario where a huge number of heterogeneous (wireless and sometimes autonomous) ubiquitous and decentralised devices communicate and potentially cooperate among them and with the network to perform storage and processing tasks without the intervention of third parties. We have validated the proposed architecture based on content islands using a real application that makes use of the optical sensor available in smartphones for detecting occasions when users do not maintain an established safe distance with the vehicle ahead It requires the use of an Android device equipped with at least a back camera and a Global Positioning System (GPS) interface. Misener et al [38] proposed a solution where positional information of vehicles is exchanged to provide forward collision warning, assistance at intersections, detection of blind-spots, and aid during lane changes Another similar approach based on the use of GPS and motion sensors is described in [39].
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