Software-Defined Networking (SDN) for Adaptive Load Balancing in Data Centers

Yadav, Kusum; Rubeaai, Sarab; Abdiwi, Saja

doi:10.25673/123723

Proceedings of International Conference on Applied Innovation in IT · 2026/03/31 · Vol. 14 · Issue 1 · pp. 1229–1235

Software-Defined Networking (SDN) for Adaptive Load Balancing in Data Centers

Kusum Yadav, Sarab Al Rubeaai, Saja Kareem and Faisal Ghazi Abdiwi

📄 Download PDF DOI: 10.25673/123723

Abstract

The rapid rise of cloud services, big data applications, and microservice-based architectures has made the need for good load balancing in data center networks even greater. Static hash-based allocation is used by traditional schemes like Equal Cost Multipath (ECMP). This can lead to congestion hotspots and lower Quality of Service (QoS) when traffic changes. To overcome these constraints, this study introduces an adaptive load balancing framework based on Software-Defined Networking (SDN) that incorporates real-time telemetry, predictive path scoring, and stability-aware re-routing. The framework represents the network as a graph, defines load balancing as an optimization problem, and utilizes a hybrid cost function that combines link utilization and queue occupancy. Tests with fat-tree topologies show that the proposed scheme cuts the 99th percentile flow completion time by up to 30% and increases the overall throughput by 15% compared to ECMP and Hedera. Also, the design makes sure that the system runs smoothly by cutting down on unnecessary re-routing and keeping resource allocation balanced. These results show that adaptive SDN-driven mechanisms can greatly improve the efficiency and reliability of large data centers, making them ideal for modern high-performance computing and cloud environments.

Keywords

Software-Defined Networking (SDN) Load Balancing Data Center Networks Flow Completion Time Throughput Optimization Adaptive Algorithms ECMP Hedera.

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