{"id":"https://openalex.org/W7162196309","doi":"https://doi.org/10.1364/jocn.605888","title":"Graph Transformers and Stabilized Reinforcement Learning for Large-Scale Dynamic Routing Modulation and Spectrum Allocation in Elastic Optical Networks","display_name":"Graph Transformers and Stabilized Reinforcement Learning for Large-Scale Dynamic Routing Modulation and Spectrum Allocation in Elastic Optical Networks","publication_year":2026,"publication_date":"2026-09-29","ids":{"openalex":"https://openalex.org/W7162196309","doi":"https://doi.org/10.1364/jocn.605888"},"language":"en","primary_location":{"id":"doi:10.1364/jocn.605888","doi":"https://doi.org/10.1364/jocn.605888","is_oa":false,"landing_page_url":"https://doi.org/10.1364/jocn.605888","pdf_url":null,"source":{"id":"https://openalex.org/S180088163","display_name":"Journal of Optical Communications and Networking","issn_l":"1943-0620","issn":["1943-0620","1943-0639"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-b","jufo-2","norway-1","poland-100","russia-white-list-1"],"host_organization":"https://openalex.org/P4310315679","host_organization_name":"Optica Publishing Group","host_organization_lineage":["https://openalex.org/P4310315679"],"host_organization_lineage_names":["Optica Publishing Group"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Optical Communications and Networking","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2605.02075","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5157983797","display_name":"Michael Doherty","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Michael Doherty","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002126652","display_name":"Alejandra Beghelli","orcid":"https://orcid.org/0000-0001-8287-5027","observed_orcids":["https://orcid.org/0000-0001-8287-5027"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Alejandra Beghelli Zapata","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5071335453","display_name":"Laura Toni","orcid":"https://orcid.org/0000-0002-8441-8791","observed_orcids":["https://orcid.org/0000-0002-8441-8791"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Laura Toni","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10847","display_name":"Advanced Optical Network Technologies","score":0.9980000257492065,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10847","display_name":"Advanced Optical Network Technologies","score":0.9980000257492065,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10714","display_name":"Software-Defined Networks and 5G","score":0.0005000000237487257,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12611","display_name":"Neural Networks and Reservoir Computing","score":0.00019999999494757503,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/elastic-optical-networks","display_name":"elastic optical networks","score":0.8379999995231628},{"id":"https://openalex.org/keywords/graph-transformer","display_name":"graph transformer","score":0.8090000152587891},{"id":"https://openalex.org/keywords/rotary-positional-encoding","display_name":"rotary positional encoding","score":0.7099999785423279},{"id":"https://openalex.org/keywords/large-scale-network-optimization","display_name":"large-scale network optimization","score":0.5320000052452087}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7581999897956848},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7372000217437744},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5766000151634216},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5651000142097473},{"id":"https://openalex.org/C199845137","wikidata":"https://www.wikidata.org/wiki/Q145490","display_name":"Network topology","level":2,"score":0.521399974822998},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.44600000977516174},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.3707999885082245},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.36880001425743103},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.36070001125335693},{"id":"https://openalex.org/C12839126","wikidata":"https://www.wikidata.org/wiki/Q5318989","display_name":"Dynamic load testing","level":2,"score":0.289000004529953},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2888999879360199},{"id":"https://openalex.org/C134579502","wikidata":"https://www.wikidata.org/wiki/Q1455619","display_name":"Frequency allocation","level":2,"score":0.2761000096797943},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.2635999917984009},{"id":"https://openalex.org/C203274722","wikidata":"https://www.wikidata.org/wiki/Q7001161","display_name":"Network performance","level":2,"score":0.2567000091075897},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.2500999867916107}],"mesh":[],"locations_count":6,"locations":[{"id":"doi:10.1364/jocn.605888","doi":"https://doi.org/10.1364/jocn.605888","is_oa":false,"landing_page_url":"https://doi.org/10.1364/jocn.605888","pdf_url":null,"source":{"id":"https://openalex.org/S180088163","display_name":"Journal of Optical Communications and Networking","issn_l":"1943-0620","issn":["1943-0620","1943-0639"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-b","jufo-2","norway-1","poland-100","russia-white-list-1"],"host_organization":"https://openalex.org/P4310315679","host_organization_name":"Optica Publishing Group","host_organization_lineage":["https://openalex.org/P4310315679"],"host_organization_lineage_names":["Optica Publishing Group"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Optical Communications and Networking","raw_type":"journal-article"},{"id":"doi:10.1364/opticaopen.32304879.v2","doi":"https://doi.org/10.1364/opticaopen.32304879.v2","is_oa":true,"landing_page_url":"https://doi.org/10.1364/opticaopen.32304879.v2","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Optica Open","raw_type":"posted-content"},{"id":"doi:10.1364/opticaopen.32304879","doi":"https://doi.org/10.1364/opticaopen.32304879","is_oa":true,"landing_page_url":"https://doi.org/10.1364/opticaopen.32304879","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Optica Open","raw_type":"posted-content"},{"id":"doi:10.1364/opticaopen.32304879.v1","doi":"https://doi.org/10.1364/opticaopen.32304879.v1","is_oa":true,"landing_page_url":"https://doi.org/10.1364/opticaopen.32304879.v1","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Optica Open","raw_type":"posted-content"},{"id":"pmh:oai:arXiv.org:2605.02075","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2605.02075","pdf_url":"https://arxiv.org/pdf/2605.02075","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2605.02075","doi":"https://doi.org/10.48550/arxiv.2605.02075","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.02075","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2605.02075","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2605.02075","pdf_url":"https://arxiv.org/pdf/2605.02075","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"score":0.7207000255584717,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"study_designs":[],"awards":[{"id":"https://openalex.org/G655822148","display_name":"EPSRC Centre for Doctoral Training in Connected Electronic and Photonic Systems (CEPS)","funder_award_id":"EP/S022139/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"}],"funders":[{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7162196309.pdf","grobid_xml":"https://content.openalex.org/works/W7162196309.grobid-xml"},"referenced_works_count":18,"referenced_works":["https://openalex.org/W1191599655","https://openalex.org/W2736601468","https://openalex.org/W2766453196","https://openalex.org/W2980433389","https://openalex.org/W2997347790","https://openalex.org/W3037932933","https://openalex.org/W3092203123","https://openalex.org/W3153278392","https://openalex.org/W3169622372","https://openalex.org/W3171970564","https://openalex.org/W3212637808","https://openalex.org/W4378766933","https://openalex.org/W4388979610","https://openalex.org/W4392120532","https://openalex.org/W4397048993","https://openalex.org/W4416781480","https://openalex.org/W7083693779","https://openalex.org/W7134963920"],"related_works":["https://openalex.org/W7215031610","https://openalex.org/W2951309479","https://openalex.org/W4364304802","https://openalex.org/W4317854658","https://openalex.org/W4405935197","https://openalex.org/W7128198781","https://openalex.org/W4403212590","https://openalex.org/W4312068995","https://openalex.org/W4411337877","https://openalex.org/W7128002174"],"abstract_inverted_index":{"Reinforcement":[0],"learning":[1,59],"(RL)":[2],"has":[3,22,177],"been":[4,178],"widely":[5],"applied":[6],"to":[7,33,78,112,123,143,174,183,200,240],"dynamic":[8,91,171],"routing,":[9],"modulation":[10],"and":[11,37,42,71,102,146,159,226,248],"spectrum":[12],"assignment":[13],"(RMSA)":[14],"in":[15],"optical":[16],"networks,":[17],"yet":[18],"no":[19],"prior":[20],"work":[21],"trained":[23,233],"a":[24,88],"transformer":[25,89],"model":[26],"for":[27,64,80,90,246],"this":[28,32,50,242],"task.":[29],"We":[30,48,93,180,206,235],"attribute":[31],"the":[34,57,81,108,117,127,139,169,201,212,218,221,228,232],"high":[35],"data":[36],"compute":[38],"requirements":[39],"of":[40,87,129,211,214,220,231],"transformers":[41],"potential":[43],"training":[44,86,216],"instabilities":[45],"with":[46,75,149,196],"RL.":[47],"address":[49],"gap":[51],"by":[52,121],"combining":[53],"recent":[54],"advances":[55],"from":[56,138],"machine":[58],"literature":[60],"(rotary":[61],"positional":[62],"encodings":[63],"graph-structured":[65],"data,":[66],"off-policy":[67],"invalid":[68],"action":[69],"masking,":[70],"valid":[72],"mass":[73],"regularization)":[74],"GPU-accelerated":[76],"simulation":[77],"achieve,":[79],"first":[82,109],"time,":[83],"stable":[84],"RL":[85,100,110,176],"RMSA.":[92],"demonstrate,":[94],"through":[95],"systematic":[96],"benchmarking":[97],"against":[98],"previous":[99],"methods":[101],"heuristic":[103],"algorithms,":[104],"that":[105],"ours":[106],"is":[107],"method":[111,198],"exceed":[113],"all":[114,237],"benchmarks,":[115],"increasing":[116],"supportable":[118],"traffic":[119,162,186],"load":[120,187],"up":[122,142,182],"13%.":[124],"To":[125,164],"demonstrate":[126],"scalability":[128],"our":[130,165,197,215],"approach,":[131],"we":[132],"train":[133],"on":[134],"real":[135],"network":[136],"topologies":[137],"TopologyBench":[140],"database":[141],"143":[144],"nodes":[145],"362":[147],"links,":[148],"320":[150],"x":[151],"12.5":[152],"GHz":[153],"frequency":[154],"slot":[155],"units":[156],"per":[157],"link,":[158],"100":[160],"Gbps":[161],"requests.":[163],"knowledge,":[166],"these":[167],"are":[168],"largest":[170],"RMSA":[172],"problems":[173],"which":[175],"applied.":[179],"find":[181],"4%":[184],"increased":[185],"can":[188],"be":[189],"supported":[190],"at":[191],"low":[192],"blocking":[193],"probability":[194],"(<0.1%)":[195],"compared":[199],"best":[202],"available":[203,245],"benchmark":[204],"algorithm.":[205],"present":[207],"an":[208],"ablation":[209],"study":[210],"components":[213],"algorithm,":[217],"dynamics":[219],"loss":[222],"function":[223],"during":[224],"training,":[225],"analyze":[227],"allocation":[229],"decisions":[230],"models.":[234],"make":[236],"code":[238],"used":[239],"produce":[241],"paper":[243],"openly":[244],"reproduction":[247],"future":[249],"benchmarking:":[250],"\\url{https://github.com/micdoh/XLRON}.":[251]},"counts_by_year":[],"updated_date":"2026-11-13T13:42:25.865203","created_date":"2026-05-24T00:00:00"}