Simulanteous Load Balancing of Servers and Controllers in SDN-Based IoMT

The Internet of Multimedia Things (IoMT) is an evolution of the IoT aimed at delivering multimedia streams as part of its realization. The IoMT is becoming increasingly appealing. Traditional computer network architectures are not robust enough to accommodate the rapid growth of IoMT networks. As a result, software-defined networks (SDNs) are utilized, which can centrally provide an overview of all network resources. SDNs enable advanced management by separating the control layer from the data layer. They introduce new capabilities to enhance load balancing. This research focuses on simultaneous load balancing between two key elements: servers and controllers. This approach allows us to prevent simultaneous issues in different network sections. Additionally, this approach employs long short-term memory prediction for forecasting the load on servers and controllers and a fuzzy system for distributing the load among servers and domains. Simulation results indicate that the proposed approach is highly effective in appropriately distributing load among servers in each network domain. The findings enable us to manage and optimize software-defined IoT networks more accurately using the proposed approach. This improves the quality of service provided to users and contributes to cost reduction and increased productivity.