Wireless Sensor Network Architecture based on Fog Computing

Abstract

Wireless Sensor Network (WSN) has been a focus for research in the last years due to the promising technology it embeds. This appears to be the most sustainable technology for environmental sensing whether it's about limited or large-scale monitoring, thanks to the ad-hoc wireless links, scalability and ease of implementation. However, main drawbacks are stemming from the limited capacity of network nodes for data storage, computing and accessing. To overcome these limitations, virtualized resources were appended allowing access to increased storage, processing and user-friendly accessibility. This came as a natural development of the common WSN architectures in the trend of modern concepts emerged with the IoT (Internet of Things) technologies proliferation. Despite the increasing usage of cloud-based WSN monitoring systems, there are still issues due to the drawbacks of cloud computing such as latency and storage costs. This paper discusses the improvements made to a cloud-based WSN architecture by adding a layer of computing at the edge of the network, a method that follows the novel model of analysing and acting on IoT data, entitled Fog Computing. Comparative analytics were performed to prove the improvements achieved through edge of the network computing.