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Deployment Strategy for Multiple Controllers Based on the Aviation On-Board Software-Defined Data Link Network

Yuting Zhu1, Yanfang Fu2,*, Yang Ce3, Pan Deng1, Jianpeng Zhu1, Huankun Su1

1 China Electronics Technology Group Corporation 20th Research Institute, Xi’an, 710068, China
2 School of Computer Science and Engineering, Xi’an Technological University, Xi’an, 710021, China
3 Department of Statistics and Actuarial Science, University of Waterloo, Waterloo, ON N2L 3G1, Canada

* Corresponding Author: Yanfang Fu. Email: email

Computers, Materials & Continua 2023, 77(3), 3867-3894. https://doi.org/10.32604/cmc.2023.046772

Abstract

In light of the escalating demand and intricacy of services in contemporary terrestrial, maritime, and aerial combat operations, there is a compelling need for enhanced service quality and efficiency in airborne cluster communication networks. Software-Defined Networking (SDN) proffers a viable solution for the multifaceted task of cooperative communication transmission and management across different operational domains within complex combat contexts, due to its intrinsic ability to flexibly allocate and centrally administer network resources. This study pivots around the optimization of SDN controller deployment within airborne data link clusters. A collaborative multi-controller architecture predicated on airborne data link clusters is thus proposed. Within this architectural framework, the controller deployment issue is reframed as a two-fold problem: subdomain partitioning and central interaction node selection. We advocate a subdomain segmentation approach grounded in node value ranking (NDVR) and a central interaction node selection methodology predicated on an enhanced Artificial Fish Swarm Algorithm (AFSA). The advanced NDVR-AFSA (Node value ranking-Improved artificial fish swarm algorithm) algorithm makes use of a chaos algorithm for population initialization, boosting population diversity and circumventing premature algorithm convergence. By the integration of adaptive strategies and incorporation of the genetic algorithm’s crossover and mutation operations, the algorithm’s search range adaptability is enhanced, thereby increasing the possibility of obtaining globally optimal solutions, while concurrently augmenting cluster reliability. The simulation results verify the advantages of the NDVR-IAFSA algorithm, achieve a better load balancing effect, improve the reliability of aviation data link cluster, and significantly reduce the average propagation delay and disconnection rate, respectively, by 12.8% and 11.7%. This shows that the optimization scheme has important significance in practical application, and can meet the high requirements of modern sea, land, and air operations to aviation airborne communication networks.

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APA Style
Zhu, Y., Fu, Y., Ce, Y., Deng, P., Zhu, J. et al. (2023). Deployment strategy for multiple controllers based on the aviation on-board software-defined data link network. Computers, Materials & Continua, 77(3), 3867-3894. https://doi.org/10.32604/cmc.2023.046772
Vancouver Style
Zhu Y, Fu Y, Ce Y, Deng P, Zhu J, Su H. Deployment strategy for multiple controllers based on the aviation on-board software-defined data link network. Comput Mater Contin. 2023;77(3):3867-3894 https://doi.org/10.32604/cmc.2023.046772
IEEE Style
Y. Zhu, Y. Fu, Y. Ce, P. Deng, J. Zhu, and H. Su "Deployment Strategy for Multiple Controllers Based on the Aviation On-Board Software-Defined Data Link Network," Comput. Mater. Contin., vol. 77, no. 3, pp. 3867-3894. 2023. https://doi.org/10.32604/cmc.2023.046772



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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