Traffic Engineering Optimization in Hybrid Software‐Defined Networks: A Mixed Integer Non‐Linear Programming Model and Heuristic Algorithm

ABSTRACT In contemporary networking infrastructure, the integration of software‐defined networking (SDN) concepts with traditional networking methodologies has given rise to hybrid software‐defined networking (HSDN); as the current network infrastructure evolves, it combines the programmability of S...

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Vydáno v:International journal of network management Ročník 35; číslo 3
Hlavní autoři: Mehraban, Samiullah, Yadav, Rajesh K.
Médium: Journal Article
Jazyk:angličtina
Vydáno: Chichester Wiley Subscription Services, Inc 01.05.2025
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ISSN:1055-7148, 1099-1190
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Shrnutí:ABSTRACT In contemporary networking infrastructure, the integration of software‐defined networking (SDN) concepts with traditional networking methodologies has given rise to hybrid software‐defined networking (HSDN); as the current network infrastructure evolves, it combines the programmability of SDN with the established protocols of traditional network infrastructure. This paradigm shift introduces novel opportunities and challenges in traffic engineering (TE), necessitating innovative solutions to enhance network performance, resource utilization, and efficiency. In this study, we examined the challenges associated with TE in a hybrid SDN environment, where traditional network devices coexist alongside SDN nodes; we investigated the routing optimization of traffic engineering in a migrated hybrid network and formulated the problem as a mixed integer non‐linear programming model. We proposed a heuristic algorithm (H‐STE) that optimizes both the OSPF weight setting and the splitting ratio of SDN nodes in the hybrid environment. Extensive evaluations were conducted using real network topologies to validate our method. The results demonstrate that a 30% deployment ratio of SDN nodes significantly improves traffic engineering performance. Specifically, the Maximum Link Utilization (MLU) stabilizes at this ratio, indicating near‐optimal network efficiency. This research provides valuable insights for researchers, practitioners, and network architects navigating SDN, hybrid SDN, and traffic engineering optimization.
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ISSN:1055-7148
1099-1190
DOI:10.1002/nem.70017