Open Access

ARTICLE

Dynamic Routing Optimization Algorithm for Software Defined Networking

Nancy Abbas El-Hefnawy^1,*, Osama Abdel Raouf², Heba Askr³

1 Department of Information Systems, Tanta University, Tanta, 31511, Egypt
2 Department of Operations Research and Decision Support, Menoufia University, Shepen Alkom, Egypt
3 Department of Information Systems, University of Sadat City, AlSadat City, 048, Egypt

* Corresponding Author: Nancy Abbas El-Hefnawy. Email:

Computers, Materials & Continua 2022, 70(1), 1349-1362. https://doi.org/10.32604/cmc.2022.017787

Received 11 February 2021; Accepted 23 March 2021; Issue published 07 September 2021

Abstract

Time and space complexity is the most critical problem of the current routing optimization algorithms for Software Defined Networking (SDN). To overcome this complexity, researchers use meta-heuristic techniques inside the routing optimization algorithms in the OpenFlow (OF) based large scale SDNs. This paper proposes a hybrid meta-heuristic algorithm to optimize the dynamic routing problem for the large scale SDNs. Due to the dynamic nature of SDNs, the proposed algorithm uses a mutation operator to overcome the memory-based problem of the ant colony algorithm. Besides, it uses the box-covering method and the k-means clustering method to divide the SDN network to overcome the problem of time and space complexity. The results of the proposed algorithm compared with the results of other similar algorithms and it shows that the proposed algorithm can handle the dynamic network changing, reduce the network congestion, the delay and running times and the packet loss rates.

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