G-SDN: Game Theory-Based SDN Controller Load Balancing for IIoT Applications Underlying 5G

With the tremendous emergence of the Industrial Internet of Things (IIoTs) in varied industrial sectors, software-defined networking (SDN) has become a prominent paradigm to improve the scalability, latency, and response time of large-scale IIoT networks. However, despite the enhanced network performance of the IIoT networks, efficient and optimal load balancing and distribution is still one of the critical aspects of the SDN paradigm that can overburden the controllers further degrading the system performance. To address the aforementioned issue, we have utilized the game theory approach to enable the distributed, optimal, and efficient load balancing among multiple SDN controllers considering the IIoT systems over a 5G communication network. The proposed approach focuses on balancing the load state, i.e., idle or medium loaded, of the controllers with the help of employed coalition game theory to evenly and optimally distribute the load between controllers by providing them incentives fairly. For that, we have determined two Nash equilibrium using formulated strategies based on the load state of the controllers. Finally, the proposed game theory approach for load balancing is evaluated, considering various performance metrics such as overall convergence utility, packet error rate, and fairness.