SDN-Driven Adaptive Routing Reconfiguration for IoT in Smart Spaces

This research addresses the challenges of integrating Software Defined Networking (SDN) within Internet of Things (IoT) frameworks, focusing on the significant overhead of SDN signalling in multi-hop Wireless Sensor Network (WSN) architectures. This study aims to enhance SDN efficiency for dynamically reconfiguring parameters used by the Routing Protocol for Low-Power and Lossy Networks (RPL). The paper introduces a modified version of μSDN, an SDN architecture tailored for IoT environments and develops a custom Python-based simulator. This modification includes a regulatory mechanism that adjusts SDN signalling based on network topology changes. Additionally, it establishes a proactive pathway to reduce network access delays for scheduled traffic and dynamically adjusts RPL parameters to optimize energy usage according to network activity. The system operates in daytime mode, characterized by high human activity with sensor traffic, and the night/holiday mode, characterized by reduced traffic. Evaluations demonstrate that these modifications significantly reduce SDN signalling overhead and energy consumption while improving the Packet Delivery Ratio (PDR). Results confirm the system's ability to adapt RPL parameters according to day and night demands dynamically, ensuring efficient network operation across varying traffic levels. It promotes sustainable, adaptive IoT deployments in smart spaces.