Ph.D. Forum Abstract: Increasing Robustness in WSN Using Software Defined Network Architecture

With the advent of Internet of Things (IoT) Wireless Sensor Networks (WSN) seem to play key a role in the connectivity of smart objects. The limited resources of WSN devices and the increased demand for new and more sophisticated services call for new and more efficient architectures. The new architectures should ensure energy-efficiency, flexibility, reliability and robustness. We believe that using SDN principles in WSN will improve many important features, such as routing, robustness and reconfiguration of the networking as well as the applications. In this research, We will find ways to increase the robustness of WSN using an SDN inspired architecture and a statistical model. The initial plan is to use statistical machine learning to look for periodic interference and other periodic behaviour in typical WSN networks.