International Journal of Computer Techniques Volume 12 Issue 3 | Solving Problems in SDN based Cloud COMPUTING Networks using AI
Solving Problems in SDN Based Cloud Computing Networks Using AI
Dr. Vishal Vasant Deshpande
KBCNMU, Maharashtra, India
Email: vish_d@outlook.com
Abstract
Cloud Network architecture traditionally depends on hardware-based fixed infrastructure and distributed network control, limiting scalability and efficiency in cloud environments. This paper analyzes how SDN innovation can solve longstanding network management issues and introduces AI-ML techniques to optimize SDN-based Cloud Computing networks.
Keywords
Cloud networking, Software Defined Network (SDN), Artificial Intelligence, Machine Learning, SDN based Cloud Computing (SDCC), Network-as-a-Service (NaaS), 5G
Conclusion
Cloud computing’s evolution with SDN improves programmability, agility, and scalability. However, SDN controllers face workload challenges. This paper proposes an AI module to offload secondary tasks, enhancing SDN efficiency. Future research will refine AI integration and explore OpenFlow protocol advancements.
References
- Mell, P. and Grance, T. (2011). The NIST definition of cloud computing. Technical Report 800-145.
- Aaqif Afzaal Abbasi et al., “Software-defined Cloud Computing: A Systematic Review,” IEEE ACCESS, 2019.
- Cheng, Y. et al., “Software-Defined Networking Rev. 2.0,” Open Data Center Alliance, 2014.
- HP Enterprises, “HPE Distributed Cloud Networking (DCN) – quickSpecs” (https://www.hpe.com/psnow/doc/c04347351).
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