What question did this study set out to answer?

The central aim is to develop a novel adaptive load balancing algorithm for cloud data center environments that address real-time traffic management challenges.

March 31, 2026Open Access

Intelligent SDN-Based Load Balancing Approach for Cloud Computing Data Centers: A Novel Adaptive Algorithm

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Authors

MDMurali Dr. Dabbu MSMustafa ShaikhPakistan Army PBPavani Boyini

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Implication

Introduces an adaptive load balancing algorithm to improve performance in cloud data centers, indicating better traffic management and efficiency.

Key Points

The central aim is to develop a novel adaptive load balancing algorithm for cloud data center environments that address real-time traffic management challenges.
Proposed an adaptive load balancing algorithm called AFALB on Ryu SDN controller.
Monitored server loads using metrics like CPU utilization and memory usage every 100ms.
Implemented intelligent flow stickiness for session persistence and developed a predictive congestion avoidance mechanism.
Conducted tests using a Linux-based testbed with 8 physical servers and various software tools.
Achieved 94.7% load distribution fairness according to Jain's fairness index.
Improved average response time by 31.2% compared to the round-robin method.
Reduced 95th percentile latency by 42.5% versus weighted least connections.
Demonstrated 99.1% availability during server failure scenarios.

Cite This Study

Dabbu et al. (2026) studied this question.

synapsesocial.com/papers/69cb64d4e6a8c024954b8d6d https://doi.org/10.5281/zenodo.19310109

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Implication

Introduces an adaptive load balancing algorithm to improve performance in cloud data centers, indicating better traffic management and efficiency.

Intelligent SDN-Based Load Balancing Approach for Cloud Computing Data Centers: A Novel Adaptive Algorithm

Discussion

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Implication

Key Points

Cite This Study

Intelligent SDN-Based Load Balancing Approach for Cloud Computing Data Centers: A Novel Adaptive Algorithm

Discussion

Member takes

Implication

Key Points

Cite This Study

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