A Software Defined Networking architecture for the Internet-of-Things

TLDR

The rapid expansion of IoT has produced wide‑area deployments where multiple heterogeneous wireless technologies coexist, making the management of these geographically distributed, dynamic infrastructures a key technical challenge. The study aims to design techniques that concurrently provision diverse classes of IoT traffic across shared sensors and networking resources. To achieve this, the authors extend the Multinetwork Information Architecture with a layered IoT SDN controller that differentiates flow scheduling across task‑level, multi‑hop, and heterogeneous paths and optimizes resource use via Network Calculus and Genetic Algorithms. Simulations of the extended MINA SDN prototype in a large‑scale integration of electric vehicles, charging stations, smart grid infrastructure, and pilot users show that the approach can efficiently exploit IoT multinetwork capabilities.

Abstract

The growing interest in the Internet of Things (IoT) has resulted in a number of wide-area deployments of IoT subnetworks, where multiple heterogeneous wireless communication solutions coexist: from multiple access technologies such as cellular, WiFi, ZigBee, and Bluetooth, to multi-hop ad-hoc and MANET routing protocols, they all must be effectively integrated to create a seamless communication platform. Managing these open, geographically distributed, and heterogeneous networking infrastructures, especially in dynamic environments, is a key technical challenge. In order to take full advantage of the many opportunities they provide, techniques to concurrently provision the different classes of IoT traffic across a common set of sensors and networking resources must be designed. In this paper, we will design a software-defined approach for the IoT environment to dynamically achieve differentiated quality levels to different IoT tasks in very heterogeneous wireless networking scenarios. For this, we extend the Multinetwork INformation Architecture (MINA), a reflective (self-observing and adapting via an embodied Observe-Analyze-Adapt loop) middleware with a layered IoT SDN controller. The developed IoT SDN controller originally i) incorporates and supports commands to differentiate flow scheduling over task-level, multi-hop, and heterogeneous ad-hoc paths and ii) exploits Network Calculus and Genetic Algorithms to optimize the usage of currently available IoT network opportunities. We have applied the extended MINA SDN prototype in the challenging IoT scenario of wide-scale integration of electric vehicles, electric charging sites, smart grid infrastructures, and a wide set of pilot users, as targeted by the Artemis Internet of Energy and Arrowhead projects. Preliminary simulation performance results indicate that our approach and the extended MINA system can support efficient exploitation of the IoT multinetwork capabilities.