Traffic is increasing day by day; for this reason, software defined network technology is used to manage network; because software defined network technology provides an overview of the network and enables advanced management. In software defined networks, load balancing is also needed to improve performance. Many approaches have been proposed for load balancing in software defined networks. These approaches can be the taxonomy; but the taxonomies presented so far are not exact. In this article, a detailed taxonomy for load balancing of software defined networks is provided. Then, the approaches that use optimization algorithms based on artificial intelligence to solve the problem of load balancing of software defined networks are explained. Finally, the methods of predicting the load balance of software defined networks and how it helps in reducing energy consumption are provided.
Imanpour, S., & Montazerolghaem, A. (2023). Taxonomy and comprehensive review of optimization techniques of load balancing in software-defined networks. Soft Computing Journal, (), -. doi: 10.22052/scj.2023.252610.1134
MLA
Somaye Imanpour; AhmadReza Montazerolghaem. "Taxonomy and comprehensive review of optimization techniques of load balancing in software-defined networks", Soft Computing Journal, , , 2023, -. doi: 10.22052/scj.2023.252610.1134
HARVARD
Imanpour, S., Montazerolghaem, A. (2023). 'Taxonomy and comprehensive review of optimization techniques of load balancing in software-defined networks', Soft Computing Journal, (), pp. -. doi: 10.22052/scj.2023.252610.1134
VANCOUVER
Imanpour, S., Montazerolghaem, A. Taxonomy and comprehensive review of optimization techniques of load balancing in software-defined networks. Soft Computing Journal, 2023; (): -. doi: 10.22052/scj.2023.252610.1134
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