Title: Particle swarm optimisation-based scalable controller placement with balancing constraints in software-defined wide area networks

Authors: Sasibhushana Rao Pappu; Kalyana Chakravarthy Chilukuri

Addresses: Department of CSE, GITAM (Deemed to be University), Visakhapatnam, India; Department of CSE, JNTUK, Kakinada, Andhra Pradesh, India ' Department of CSE, MVGR College of Engineering (Autonomous), Vizianagaram, India

Abstract: Software defined networking (SDN) is a cutting-edge networking technology that enables a traditional switch's control plane and data plane to be isolated. SDN improves network usage performance by centralising control plane management (SDN controller). However, a single controller will be unable handle these networks due to massive usage of resources in today's wide area networks. It allows the control plane to be controlled by multiple controllers by distributing switches among them. We provide a method for determining the best controller position by balancing the load imbalance between switches and controllers. The proposed strategy is based on particle swarm optimisation to determine the placement of controllers in a software defined networks, using the controller's load factor as the fitness feature. It does not however affect the current controller placement solutions (latency between controller and switch). In this article, the network topologies OS3E and Intellifiber are used. The results show that the proposed method reduces the overall latency of the network when multiple controllers are used.

Keywords: controller placement problem; CPP; software defined networking; SDN; particle swarm optimisation; PSO; load balance.

DOI: 10.1504/IJCVR.2025.148220

International Journal of Computational Vision and Robotics, 2025 Vol.15 No.5, pp.565 - 576

Received: 07 Oct 2023
Accepted: 25 Nov 2023
Published online: 01 Sep 2025 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article