An adaptive edge router enabling internet of things

The vision of future networking is that not only people but also all things, services and media will be connected and integrated, creating an Internet of Everything (IoE). Internet of Things (IoT) systems aim to connect and scale billions of devices in various domains such as transportation, industry, smart home/city, medical services and energy systems. Different wireless and wired technologies link sensors and systems together, through wireless access points, gateways and routers that in turn connect to the web and cloud-based intelligence. IoT architectures make great demands on network control methods for the efficient management of massive amounts of nodes and data. Therefore, some of the cloud's management tasks should be distributed around the edges of networked systems, utilizing fog computing to control and manage e.g. network resources, quality, traffic prioritizations and security. In this work we present adaptive edge computing solutions based on regressive admission control (REAC) and fuzzy weighted queueing (FWQ) that monitor and react to network Quality of Service (QoS) changes within heterogeneous networks, and in a vehicular use case scenario utilizing IEEE 802.11p technology. These adaptive solutions are providing more stable network performance and optimizing the network path and resources.