A Hybrid DEWO Approach for Enhancing QoS in Software-Defined Networks through Optimized Controller Placement

The new network concepts (like SDNs) decouple the plane of control logic from the plane of hardware data. Software-Defined Networking (SDN) orchestrates networked intelligent devices in a centralized fashion. Smart devices enabled with IoT collect data in real time from devices on the network. The Smart City is an evolving IoT application where the urban environment is automatically controlled without human involvement. Smart city actuators and sensors and other rapidly proliferating IoT devices generate huge amounts of data and increase network traffic. In smart cities, the Quality of Service (QoS) can be guaranteed by Software-Defined Networking (SDN) in IoT networks, which can improve the user experience. Traditional IoT networks have latency, security, and reliability issues. These challenges are mitigated and performance is improved in SDN enabled IoTs networks. Smart city networking needs number of controllers to monitor IoT devices. Software Defined IoT Networks require several controllers. Various metaheuristic strategies are used to solve controller placement problems (CPP), but premature conversions adversely affect performance due to total controllers increased in the networks. A sophisticated Hybrid Differential Evolution and Whale Optimization (DEWO) method balances exploration and exploitation of controller positioning in IoT-SDN network. The approach achieves load balancing of switches and optimal controller placement with low latency. This method reduces link breakdowns and measures end-to-end latency. The hybrid method outperforms many existing metaheuristic algorithms over as many as 40 controllers.