A Novel Time-Based Switch Migration Method (TSSM) for Load Balancing in Distributed Software-Defined Networking
Thangaraj E1, Dinesh K1, Prabhakaran Paulraj2, A Barkathulla1, Margaret Flora3 & Karthik Elangovan1 Show affiliations
- Department of Computer Science and Engineering, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai, India
- Department of Electrical, Electronics, and Communications Engineering, St. Joseph University in Tanzania, Dar Es Salaam, Tanzania
- Department of Artificial Intelligence and Machine Learning, RMD Engineering College, Chennai, India
Journal of Computer Science, Volume 22, Issue 3, pp. 800–812 · doi.org/10.3844/jcssp.2026.800.812
Abstract
Switch migration is predominantly used for workload balancing in distributed Software Defined Network (SDN) controllers. The Time-Sharing Switch Migration (TSSM) technique allowed the switch's responsibility to be divided based on the time duration condition of overload, which resulted in fewer overload events, fewer ping-pong controller issues, and more efficient controllers. However, it has higher controller resource utilization during TSSM working hours, higher migration expenses, and requires more controllers to complete. Therefore, based on flow characteristics, we proposed a shortest-feasible open flow path algorithm that optimizes controller selection during the TSSM phase. The new TSSM approach maintains the benefits of TSSM while lowering controller resource consumption and migration expenses. An open network operating system is used to accomplish the suggested method for practical reasons. The testing results show that the proposed method lowers migration costs and controller resource utilization by about 33% compared with the existing system.
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E, T., K, D., Paulraj, P., Barkathulla, A., Flora, M. & Elangovan, K. (2026). A Novel Time-Based Switch Migration Method (TSSM) for Load Balancing in Distributed Software-Defined Networking. Journal of Computer Science, 22(3), 800–812. https://doi.org/10.3844/jcssp.2026.800.812
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