Fog and edge computing: concepts, tools and focus areas

Abstract

Big data coupled with Internet of Things (IoT) have changed the way organisations perform business. With its panoply of sensors and smart devices, IoT generates large volumes of data that can provide meaningful insights. Cloud platforms are being widely used to perform analytics on data. With the emerging trends in fog and edge computing, data can now be processed and analysed at different layers on the network, near the source where it is generated. Not all data generated by sensors might be meaningful. Therefore, data with less value can be processed at the fog or edge layer, and discarded at source whereas data having more value are transferred to the cloud for further processing. This work highlights the main motivation for fog and edge computing with focus on related network and communication protocols. A comprehensive comparison of existing cloud, fog and edge simulators is also given in terms of parameters, configuration steps and simulation scenarios. Furthermore, several fog and edge tools are summarised and real-world use cases where these tools are being used are presented. Finally, this work provides an in-depth review of the latest fog and edge research works and proposes six main fog and edge focus areas: partitioning and offloading tasks, sustainable energy consumption, edge analytics, edge node security, edge node and data discovery, and quality of service.