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banitalebi dehkordi, afsaneh. (1404). Multi-Controller Placement Optimization in SDNs Using Enhanced Density-Based Clustering Techniques. , (), -. doi: 10.22108/jcs.2025.142694.1149
afsaneh banitalebi dehkordi. "Multi-Controller Placement Optimization in SDNs Using Enhanced Density-Based Clustering Techniques". , , , 1404, -. doi: 10.22108/jcs.2025.142694.1149
banitalebi dehkordi, afsaneh. (1404). 'Multi-Controller Placement Optimization in SDNs Using Enhanced Density-Based Clustering Techniques', , (), pp. -. doi: 10.22108/jcs.2025.142694.1149
banitalebi dehkordi, afsaneh. Multi-Controller Placement Optimization in SDNs Using Enhanced Density-Based Clustering Techniques. , 1404; (): -. doi: 10.22108/jcs.2025.142694.1149

Multi-Controller Placement Optimization in SDNs Using Enhanced Density-Based Clustering Techniques

Journal of Computing and Security
مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 17 فروردین 1404
نوع مقاله: Research Article
شناسه دیجیتال (DOI): 10.22108/jcs.2025.142694.1149
نویسنده
afsaneh banitalebi dehkordi*
Department of Computer Engineering, Payame Noor University (PNU), P.O.Box 19395-4697, Tehran, Iran.
چکیده
One of the major challenges in large-scale Software-Defined Networks (SDN) is determining the optimal placement and number of controllers. Existing methods often face issues such as high latency, localization problems, and parameter configuration complexity. While density-based clustering algorithms like DBSCAN offer several advantages, they also encounter challenges, such as parameter tuning and noise caused by unnecessary distance computations. This paper introduces an enhanced algorithm named FIDBSCAN (Fast and Improved Density-Based Clustering with Noise) as an innovative approach to solve the controller placement problem. The algorithm accelerates the neighborhood search process by early pruning of noisy points and automatic input parameter determination, resulting in effective clustering for controller placement. The objective of this algorithm is to minimize the average propagation delays and the worst-case delay between controllers and switches.To evaluate the proposed method, experiments were conducted on real-world topologies, specifically Viatel and TW Telecom, obtained from the Internet Topology Zoo database. The results demonstrated that on the Viatel network, the proposed algorithm achieved a precision of 1.0, a recovery rate of 0.97, and an F-measure of 0.98, outperforming algorithms such as OPTICS, GDBSCAN, DBSCAN, DDSC, and ODBSCAN. Additionally, the clustering error rate of the proposed algorithm was 0.01, and it identified the optimal number of clusters (5 clusters) in both the Viatel and TW Telecom networks.
کلیدواژه‌ها
Controller Placement Problem؛ Distributed Controllers؛ SDN؛ Density Clustering Algorithm
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تعداد مشاهده مقاله: 14


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