Authors :
Aishwarya K. P.; Bhoomika V.; Hamsini G. R.; K. S. Sharadhi
Volume/Issue :
Volume 11 - 2026, Issue 9 - September
Google Scholar :
https://tinyurl.com/58cky5jy
DOI :
https://doi.org/10.38124/ijisrt/26sep807
Note : A published paper may take 4-5
working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and
ResearchGate.
Abstract :
This paper presents AdaptiveNet SDN, a software-defined networking simulation framework designed to maintain
communication when links, nodes, or groups of adjacent links fail. The system combines a multi-objective adaptive routing
algorithm with a self-healing controller, heartbeat-based failure detection, bandwidth-aware admission control, and real
UDP packet forwarding among virtual mesh nodes. Routing cost considers latency, reliability, energy use, and deadline miss
probability, while an exponentially weighted moving average adjusts routing priorities according to observed network
conditions. An eight-percent path retention rule reduces unnecessary route changes during small metric fluctuations. The
framework was evaluated on six-node and twelve-node topologies using repeated failure experiments and a Dijkstra latencybased baseline. Across the current eighteen-condition experiment sweep, the twelve-node topology achieved complete
recovery for single link, two independent link, and sequential failure scenarios for both algorithms. Node and correlated
storm failures exposed the limits of topology redundancy. The experiments did not establish a statistically distinguishable
advantage for adaptive routing on service recovery time or packet loss, which is reported as a limitation rather than hidden.
The main contribution is therefore an integrated platform for studying adaptive routing and self-healing behavior under
controlled network failures.
Keywords :
Software-Defined Networking; Adaptive Routing; Self-Healing; Quality of Service; Fault Recovery; Dijkstra; UDP Mesh; Failure Detection.
References :
- D. Turlykozhayeva, A. Akhmetali, S. Akhtanov, A. Bolysbay, N. Ussipov, and Y. Shabdan, “Routing algorithm for software defined network based on box-covering algorithm,” 2023 10th International Conference on Wireless Networks and Mobile Communications (WINCOM), 2023, doi: 10.1109/WINCOM59760.2023.10322960.
- I. E. Kamarudin, M. I. U. Ong, M. A. Ameedeen, and A. Zabidi, “QSroute: A QoS aware routing scheme for Software Defined Networking,” 2023 IEEE 8th International Conference on Software Engineering and Computer Systems (ICSECS), 2023, pp. 388-391, doi: 10.1109/ICSECS58457.2023.10256362.
- P. Gururama Senthilvel, T. Thirupurasundari D R, R. Kumar K, H. Kumar Palani, and K. Sundravadivelu, “Enhancing wireless mesh network performance through AI-based routing algorithms,” 2023 International Conference on Communication, Security and Artificial Intelligence (ICCSAI), 2023, pp. 931-935, doi: 10.1109/ICCSAI59793.2023.10421320.
- D. De Lima, F. Vogt, A. Teixeira da Silva, F. Rodriguez Cesen, and C. Esteve Rothenberg, “RESISTING: A new fast-reroute mechanism with packet distribution on P4-programmable switches,” 2024 IEEE Conference on Network Function Virtualization and Software Defined Networks (NFV-SDN), 2024, doi: 10.1109/NFV-SDN61811.2024.10807507.
- P. Ravi Tammanashastri, S. M. Rajagopal, and S. Shivadutt Bananjee, “Comparative analysis of Bellman-Ford and Dijkstra algorithms in Software Defined Networking,” 2024 5th International Conference on Data Intelligence and Cognitive Informatics (ICDICI), 2024, doi: 10.1109/ICDICI62993.2024.10810921.
This paper presents AdaptiveNet SDN, a software-defined networking simulation framework designed to maintain
communication when links, nodes, or groups of adjacent links fail. The system combines a multi-objective adaptive routing
algorithm with a self-healing controller, heartbeat-based failure detection, bandwidth-aware admission control, and real
UDP packet forwarding among virtual mesh nodes. Routing cost considers latency, reliability, energy use, and deadline miss
probability, while an exponentially weighted moving average adjusts routing priorities according to observed network
conditions. An eight-percent path retention rule reduces unnecessary route changes during small metric fluctuations. The
framework was evaluated on six-node and twelve-node topologies using repeated failure experiments and a Dijkstra latencybased baseline. Across the current eighteen-condition experiment sweep, the twelve-node topology achieved complete
recovery for single link, two independent link, and sequential failure scenarios for both algorithms. Node and correlated
storm failures exposed the limits of topology redundancy. The experiments did not establish a statistically distinguishable
advantage for adaptive routing on service recovery time or packet loss, which is reported as a limitation rather than hidden.
The main contribution is therefore an integrated platform for studying adaptive routing and self-healing behavior under
controlled network failures.
Keywords :
Software-Defined Networking; Adaptive Routing; Self-Healing; Quality of Service; Fault Recovery; Dijkstra; UDP Mesh; Failure Detection.