Software defined network (SDN) has shown significant advantages in numerous real-life aspects with separating the control plane from the data plane that provides programmable management for networks. However, with the increase in the network size, a single controller of SDN imposes considerable limitations on various features. Therefore, in networks with immense scalability, multiple controllers are essential. Specifying the optimal number of controllers and their deployment place is known as the controller placement problem (CPP), which affects the network's performance. In the present paper, a novel controller placement algorithm has been introduced using the advantages of nature-inspired optimization algorithms and network portioning. Firstly, the Manta Ray Foraging Optimization (MRFO) and Salp Swarm Algorithm (SSA) have been discretized to solve CPP. Three new operators comprising a two-point swap, random insert, and half points crossover operators were introduced to discretized the algorithms. Afterward, the resulting discrete MRFO and SSA algorithms were hybridized in a promoting manner. Next, the proposed discrete algorithm has been evaluated on six well-known software-defined networks with a different number of controllers. In addition, the networks have been chosen from various sizes to evaluate the scalability of the proposed algorithm. The proposed algorithm has been compared with several other state-of-the-art algorithms regarding network propagation delay and convergence rate in experiments. The findings indicated the effectiveness of the contributions and the superiority of the proposed algorithm over the competitor algorithms.

通过将控制平面与数据平面分离，从而为网络提供可编程管理，软件定义网络（SDN）在众多现实生活中已显示出显着的优势。但是，随着网络规模的增加，SDN的单个控制器对各种功能施加了相当大的限制。因此，在具有巨大可扩展性的网络中，多个控制器是必不可少的。指定控制器的最佳数量及其部署位置称为控制器放置问题（CPP），它会影响网络的性能。在本文中，利用自然启发式优化算法和网络划分的优点，提出了一种新颖的控制器放置算法。首先，Manta射线觅食优化（MRFO）和Salp Swarm算法（SSA）已离散化以解决CPP。引入了三个新运算符，包括两点交换，随机插入和半点交叉运算符，以离散化算法。然后，将得到的离散MRFO和SSA算法以促进方式进行混合。接下来，已经在具有不同数量控制器的六个著名软件定义网络上对提出的离散算法进行了评估。另外，已经从各种大小中选择了网络以评估所提出算法的可扩展性。在网络传播延迟和收敛速度方面，该算法已与其他几种最先进的算法进行了比较。