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Netw."],"published-print":{"date-parts":[[2025,11,1]]},"abstract":"<jats:p>This work presents a metro-access network architecture designed to meet the stringent requirements of time-sensitive applications in emerging 5G and 6G networks. The proposed architecture leverages semiconductor optical amplifier-based optical add-drop multiplexers and FPGA-based controllers to enable dynamic, low-latency operation suitable for applications with critical latency and jitter demands. We introduce a control plane protocol that allows for deterministic time-slotted resource reservation, ensuring transparent optical switching and minimizing latency. We validate the architecture through a prototype implementation in a ring network topology, demonstrating latency-bounded operation. Experimental results show that the network achieves sub-microsecond reconfiguration times and stable latency performance, with transparency crossing up to six nodes and a data recovery time of 100\u00a0ns at \u221217dBm, making the architecture a potential solution for federated computing and edge cloud scenarios.<\/jats:p>","DOI":"10.1364\/jocn.564881","type":"journal-article","created":{"date-parts":[[2025,9,17]],"date-time":"2025-09-17T19:00:09Z","timestamp":1758135609000},"page":"995","update-policy":"https:\/\/doi.org\/10.1364\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Dynamic, low-latency metro-access network architecture for time-sensitive applications using SOA-based optical switching and supervisory channel FPGA control"],"prefix":"10.1364","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7637-1815","authenticated-orcid":true,"given":"Henrique","family":"Freire Santana","sequence":"first","affiliation":[{"id":[{"id":"https:\/\/ror.org\/02c2kyt77","id-type":"ROR","asserted-by":"publisher"}]}]},{"given":"Ali","family":"Mefleh","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/02c2kyt77","id-type":"ROR","asserted-by":"publisher"}]},{"name":"KPN"}]},{"given":"Nicola","family":"Calabretta","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/02c2kyt77","id-type":"ROR","asserted-by":"publisher"}]}]}],"member":"285","published-online":{"date-parts":[[2025,10,13]]},"reference":[{"key":"jocn-17-11-995-R1","doi-asserted-by":"publisher","first-page":"172","DOI":"10.1364\/JOCN.9.000172","type":"journal-article","volume":"9","author":"Chitimalla","year":"2017","journal-title":"J. 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All rights, including for text and data mining (TDM), Artificial Intelligence (AI) training, and similar technologies, are reserved.","name":"copyright","label":"Copyright"}]}}