Abstract
Software Defined Networking (SDN) is one of the most recent Internet technology that manages the large scale network. SDN decouples the control plane from data plane, which simplifies the logic of network devices and reduces the cost of the network infrastructure. The control plane is the key component of a network which ensures smooth management and operation of the entire network. Distributed SDN controllers have been proposed to solve the scalability and a single point of failure problem. It is a critical issue for the switch to find the optimal controller among the distributed controllers. In this paper we propose a novel scheme for controller selection in distributed SDN environments. The proposed scheme decides optimal controller from distributed controllers by applying the Artificial Bee Colony (ABC) algorithm for meta-heuristic search and Apriori algorithm for effective association rule mining between switch and controller. Computer simulation reveals that the proposed scheme consistently outperforms the scheme employing only ABC and Apriori algorithms separately in terms of response time, arrival rate, number of messages, and accuracy.
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Acknowledgments
This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2022R1I1A1A01053800).
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Kim, K.T. (2023). Optimal Controller Selection Scheme Using Artificial Bee Colony and Apriori Algorithms in SDN. In: Uden, L., Ting, IH. (eds) Knowledge Management in Organisations. KMO 2023. Communications in Computer and Information Science, vol 1825. Springer, Cham. https://doi.org/10.1007/978-3-031-34045-1_28
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