Soha Rawas, Agariadne Dwinggo Samala
Software-Defined Networking (SDN) enables dynamic network control but remains vulnerable to faults that degrade performance and availability. To address this, we propose a novel self-healing SDN framework inspired by biological resilience mechanisms. The architecture integrates immune system-inspired anomaly detection for rapid fault identification, a neural network for real-time topology reconfiguration, and a genetic algorithm for long-term evolutionary adaptation. Energy-aware recovery paths are selected to minimize power consumption during mitigation. Evaluated through Mininet OpenDaylight testbeds, the framework reduces fault recovery time by up to 30%, improves fault tolerance by 25%, enhances throughput by 20%, lowers latency by 15%, and decreases energy use by 20% compared to baseline methods. This integrated, autonomous approach advances the state of the art in resilient, efficient, and sustainable SDN management. © Bharati Vidyapeeth's Institute of Computer Applications and Management 2025.
Faculty of Science, Department of Mathematics and Computer science, Beirut Arab University, Beirut, Lebanon; Faculty of Engineering, Universitas Negeri Padang, West Sumatera, Padang, Indonesia
