Study of the Efficiency of Fog Computing in an Optimized LoRaWAN Cloud Architecture

Abstract

The technologies of the Internet of Things (IoT) have an increasing influence on our daily lives. The expansion of the IoT is associated with the growing number of IoT devices that are connected to the Internet. As the number of connected devices grows, the demand for speed and data volume is also greater. While most IoT network technologies use cloud computing, this solution becomes inefficient for some use-cases. For example, suppose that a company that uses an IoT network with several sensors to collect data within a production hall. The company may require sharing only selected data to the public cloud and responding faster to specific events. In the case of a large amount of data, the off-loading techniques can be utilized to reach higher efficiency. Meeting these requirements is difficult or impossible for solutions adopting cloud computing. The fog computing paradigm addresses these cases by providing data processing closer to end devices. This paper proposes three possible network architectures that adopt fog computing for LoRaWAN because LoRaWAN is already deployed in many locations and offers long-distance communication with low-power consumption. The architecture proposals are further compared in simulations to select the optimal form in terms of total service time. The resulting optimal communication architecture could be deployed to the existing LoRaWAN with minimal cost and effort of the network operator.