A Hybrid Multi-objective Algorithm for Imbalanced Controller Placement in Software-Defined Networks

The Software-defined network (SDN) is a technique to design and manage a network that allows dynamic and programmatically functional configuration of network intending to improve the performance and monitor the system to make it comparable to the cloud computing than traditional types of network management. The SDNs comprise various switches and several controllers that lead the switches' data to a station or other controllers. One of the main challenges in the SDNs is seeking a fair number of controllers and optimal places for deploying them, known as controller placement problems. Depending on the network requirements, various criteria (e.g., installation cost, latency, load balancing, etc.) have been proposed to find the best places to install the controllers. The so-called problem that has attracted researchers' attention is formulated in the form of an optimization problem of multi-objective type. A novel multi-objective version of the Marine Predator Algorithm (MOMPA) was introduced in the current paper. The MOMPA was then hybridized with the Non-dominated Sorting Genetic Algorithm-II innovatively. Next, the proposed hybrid algorithm is discretized with mutation and crossover operators. Afterwards, the proposed hybrid discrete multi-objective algorithm was exploited to solve the controller placement problem. Henceforth, the proposed algorithm was applied to several real-world software-defined networks and was compared with some state-of-the-art algorithms regarding LC-S, LC-C, Imbalance, SP, and obtained Pareto members. The results of the comparisons demonstrated the superiority of the proposed controller placement algorithm.