{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,22]],"date-time":"2026-04-22T14:57:19Z","timestamp":1776869839252,"version":"3.51.2"},"reference-count":33,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2022,7,4]],"date-time":"2022-07-04T00:00:00Z","timestamp":1656892800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computers"],"abstract":"<jats:p>Software-Defined Networking (SDN) is a developing architecture that provides scalability, flexibility, and efficient network management. However, optimal controller placement faces many problems, which affect the performance of the overall network. To resolve the Multi-controller SDN (MC-SDN) that is deployed in the SDN environment, we propose an approach that uses a hybrid metaheuristic algorithm that improves network performance. Initially, the proposed SDN network is constructed based on graph theory, which improves the connectivity and flexibility between switches and controllers. After that, the controller selection is performed by selecting an optimal controller from multiple controllers based on controller features using the firefly optimization algorithm (FA), which improves the network performance. Finally, multi-controller placement is performed to reduce the communication latency between the switch to controllers. Here, multiple controllers are placed by considering location and distance using a hybrid metaheuristic algorithm, which includes a harmonic search algorithm and particle swarm optimization algorithm (HSA-PSO), in which the PSO algorithm is proposed to automatically update the harmonic search parameters. The simulation of multi-controller placement is carried out by the CloudsimSDN network simulator, and the simulation results demonstrate the proposed advantages in terms of propagation latency, Round Trip Time (RTT), matrix of Time Session (TS), delay, reliability, and throughput.<\/jats:p>","DOI":"10.3390\/computers11070111","type":"journal-article","created":{"date-parts":[[2022,7,4]],"date-time":"2022-07-04T11:15:05Z","timestamp":1656933305000},"page":"111","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":25,"title":["Multi-Controllers Placement Optimization in SDN by the Hybrid HSA-PSO Algorithm"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4336-167X","authenticated-orcid":false,"given":"Neamah S.","family":"Radam","sequence":"first","affiliation":[{"name":"College of Computer Science and Information Technology, University of Anbar, Ramadi 31001, Iraq"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2805-5738","authenticated-orcid":false,"given":"Sufyan T. Faraj","family":"Al-Janabi","sequence":"additional","affiliation":[{"name":"College of Computer Science and Information Technology, University of Anbar, Ramadi 31001, Iraq"}]},{"given":"Khalid Sh.","family":"Jasim","sequence":"additional","affiliation":[{"name":"College of Computer Science and Information Technology, University of Anbar, Ramadi 31001, Iraq"}]}],"member":"1968","published-online":{"date-parts":[[2022,7,4]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Qi, Y., Wang, D., Yao, W., Li, H., and Cao, Y. (2019, January 20\u201324). Towards multi-controller placement for SDN based on density peaks clustering. Proceedings of the 2019 IEEE International Conference on Communications (ICC), Shanghai, China.","DOI":"10.1109\/ICC.2019.8761814"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Mohanty, S., Priyadarshini, P., Sahoo, B., and Sethi, S. (2019, January 27\u201329). 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