{"id":"https://openalex.org/W4414918200","doi":"https://doi.org/10.3390/network5040044","title":"Hybrid Spatio-Temporal CNN\u2013LSTM/BiLSTM Models for Blocking Prediction in Elastic Optical Networks","display_name":"Hybrid Spatio-Temporal CNN\u2013LSTM/BiLSTM Models for Blocking Prediction in Elastic Optical Networks","publication_year":2025,"publication_date":"2025-10-07","ids":{"openalex":"https://openalex.org/W4414918200","doi":"https://doi.org/10.3390/network5040044"},"language":"en","primary_location":{"id":"doi:10.3390/network5040044","is_oa":true,"landing_page_url":"https://doi.org/10.3390/network5040044","pdf_url":"https://www.mdpi.com/2673-8732/5/4/44/pdf?version=1759830481","source":{"id":"https://openalex.org/S4210214347","display_name":"Network","issn_l":"2673-8732","issn":["2673-8732"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Network","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2673-8732/5/4/44/pdf?version=1759830481","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5085973852","display_name":"Farzaneh Nourmohammadi","orcid":"https://orcid.org/0009-0003-5121-835X"},"institutions":[{"id":"https://openalex.org/I9617848","display_name":"Universitat Polit\u00e8cnica de Catalunya","ror":"https://ror.org/03mb6wj31","country_code":"ES","type":"education","lineage":["https://openalex.org/I9617848"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Farzaneh Nourmohammadi","raw_affiliation_strings":["Department of Signal Theory and Communications, Universitat Polit\u00e8cnica de Catalunya, 08034 Barcelona, Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Signal Theory and Communications, Universitat Polit\u00e8cnica de Catalunya, 08034 Barcelona, Spain","institution_ids":["https://openalex.org/I9617848"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081281333","display_name":"Jaume Comellas","orcid":"https://orcid.org/0000-0002-9129-0562"},"institutions":[{"id":"https://openalex.org/I9617848","display_name":"Universitat Polit\u00e8cnica de Catalunya","ror":"https://ror.org/03mb6wj31","country_code":"ES","type":"education","lineage":["https://openalex.org/I9617848"]}],"countries":["ES"],"is_corresponding":true,"raw_author_name":"Jaume Comellas","raw_affiliation_strings":["Department of Signal Theory and Communications, Universitat Polit\u00e8cnica de Catalunya, 08034 Barcelona, Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Signal Theory and Communications, Universitat Polit\u00e8cnica de Catalunya, 08034 Barcelona, Spain","institution_ids":["https://openalex.org/I9617848"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080242338","display_name":"Uzay Kaymak","orcid":"https://orcid.org/0000-0002-4500-9098"},"institutions":[{"id":"https://openalex.org/I83019370","display_name":"Eindhoven University of Technology","ror":"https://ror.org/02c2kyt77","country_code":"NL","type":"education","lineage":["https://openalex.org/I83019370"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Uzay Kaymak","raw_affiliation_strings":["Jheronimus Academy of Data Science, Eindhoven University of Technology, 5600 MB Eindhoven, The Netherlands"],"raw_orcid":"https://orcid.org/0000-0002-4500-9098","affiliations":[{"raw_affiliation_string":"Jheronimus Academy of Data Science, Eindhoven University of Technology, 5600 MB Eindhoven, The Netherlands","institution_ids":["https://openalex.org/I83019370"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5081281333"],"corresponding_institution_ids":["https://openalex.org/I9617848"],"apc_list":{"value":1000,"currency":"CHF","value_usd":1082},"apc_paid":{"value":1000,"currency":"CHF","value_usd":1082},"fwci":0.5734,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.72812843,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"5","issue":"4","first_page":"44","last_page":"44"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10847","display_name":"Advanced Optical Network Technologies","score":0.9977999925613403,"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":0.9977999925613403,"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/T10232","display_name":"Optical Network Technologies","score":0.9966999888420105,"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/T10767","display_name":"Advanced Photonic Communication Systems","score":0.9965999722480774,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/blocking","display_name":"Blocking (statistics)","score":0.913100004196167},{"id":"https://openalex.org/keywords/network-topology","display_name":"Network topology","score":0.535099983215332},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.4339999854564667},{"id":"https://openalex.org/keywords/topology","display_name":"Topology (electrical circuits)","score":0.42500001192092896},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.3962000012397766},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.35740000009536743},{"id":"https://openalex.org/keywords/fragmentation","display_name":"Fragmentation (computing)","score":0.34049999713897705},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.3393999934196472}],"concepts":[{"id":"https://openalex.org/C144745244","wikidata":"https://www.wikidata.org/wiki/Q4927286","display_name":"Blocking (statistics)","level":2,"score":0.913100004196167},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6845999956130981},{"id":"https://openalex.org/C199845137","wikidata":"https://www.wikidata.org/wiki/Q145490","display_name":"Network topology","level":2,"score":0.535099983215332},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.4339999854564667},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.43070000410079956},{"id":"https://openalex.org/C184720557","wikidata":"https://www.wikidata.org/wiki/Q7825049","display_name":"Topology (electrical circuits)","level":2,"score":0.42500001192092896},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3991999924182892},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.3962000012397766},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.35740000009536743},{"id":"https://openalex.org/C191015642","wikidata":"https://www.wikidata.org/wiki/Q1132459","display_name":"Fragmentation (computing)","level":2,"score":0.34049999713897705},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3393999934196472},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.31529998779296875},{"id":"https://openalex.org/C156778621","wikidata":"https://www.wikidata.org/wiki/Q1365748","display_name":"Spectrum (functional analysis)","level":2,"score":0.3109000027179718},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.30959999561309814},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.30660000443458557},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.30559998750686646},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.29750001430511475},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.2858999967575073},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.2759000062942505},{"id":"https://openalex.org/C23186085","wikidata":"https://www.wikidata.org/wiki/Q22906809","display_name":"Blocking effect","level":2,"score":0.2732999920845032},{"id":"https://openalex.org/C2780609101","wikidata":"https://www.wikidata.org/wiki/Q17156588","display_name":"Resource management (computing)","level":2,"score":0.2689000070095062},{"id":"https://openalex.org/C101336846","wikidata":"https://www.wikidata.org/wiki/Q17105111","display_name":"Optical switch","level":2,"score":0.2660999894142151},{"id":"https://openalex.org/C198352243","wikidata":"https://www.wikidata.org/wiki/Q37105","display_name":"Line (geometry)","level":2,"score":0.25929999351501465},{"id":"https://openalex.org/C74296488","wikidata":"https://www.wikidata.org/wiki/Q2527392","display_name":"End-to-end principle","level":2,"score":0.257099986076355}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3390/network5040044","is_oa":true,"landing_page_url":"https://doi.org/10.3390/network5040044","pdf_url":"https://www.mdpi.com/2673-8732/5/4/44/pdf?version=1759830481","source":{"id":"https://openalex.org/S4210214347","display_name":"Network","issn_l":"2673-8732","issn":["2673-8732"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Network","raw_type":"journal-article"},{"id":"pmh:oai:pure.tue.nl:openaire/4b4a7fac-e700-4184-9547-e96510346ef3","is_oa":true,"landing_page_url":"https://research.tue.nl/en/publications/4b4a7fac-e700-4184-9547-e96510346ef3","pdf_url":null,"source":{"id":"https://openalex.org/S4406922641","display_name":"TU/e Research Portal","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Nourmohammadi, F, Comellas, J & Kaymak, U 2025, 'Hybrid Spatio-Temporal CNN\u2013LSTM/BiLSTM Models for Blocking Prediction in Elastic Optical Networks', Network, vol. 5, no. 4, 44. https://doi.org/10.3390/network5040044","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:oai:doaj.org/article:20212fdc601b421cbc67f0468694227f","is_oa":true,"landing_page_url":"https://doaj.org/article/20212fdc601b421cbc67f0468694227f","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Network, Vol 5, Iss 4, p 44 (2025)","raw_type":"article"},{"id":"pmh:oai:upcommons.upc.edu:2117/451980","is_oa":true,"landing_page_url":"https://hdl.handle.net/2117/451980","pdf_url":null,"source":{"id":"https://openalex.org/S4377196262","display_name":"UPCommons institutional repository (Universitat Polit\u00e8cnica de Catalunya)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I9617848","host_organization_name":"Universitat Polit\u00e8cnica de Catalunya","host_organization_lineage":["https://openalex.org/I9617848"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"}],"best_oa_location":{"id":"doi:10.3390/network5040044","is_oa":true,"landing_page_url":"https://doi.org/10.3390/network5040044","pdf_url":"https://www.mdpi.com/2673-8732/5/4/44/pdf?version=1759830481","source":{"id":"https://openalex.org/S4210214347","display_name":"Network","issn_l":"2673-8732","issn":["2673-8732"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Network","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320334830","display_name":"Ag\u00e8ncia de Gesti\u00f3 d'Ajuts Universitaris i de Recerca","ror":"https://ror.org/01n4pqe45"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4414918200.pdf","grobid_xml":"https://content.openalex.org/works/W4414918200.grobid-xml"},"referenced_works_count":38,"referenced_works":["https://openalex.org/W2567615407","https://openalex.org/W2612472936","https://openalex.org/W2765858976","https://openalex.org/W2891029091","https://openalex.org/W2897637597","https://openalex.org/W2918911532","https://openalex.org/W2951309479","https://openalex.org/W2963432161","https://openalex.org/W2973918713","https://openalex.org/W2974008464","https://openalex.org/W3088014635","https://openalex.org/W3110378470","https://openalex.org/W3186612513","https://openalex.org/W3205871783","https://openalex.org/W3214410399","https://openalex.org/W4210496140","https://openalex.org/W4225632037","https://openalex.org/W4281756641","https://openalex.org/W4285147517","https://openalex.org/W4289537641","https://openalex.org/W4312300168","https://openalex.org/W4313886879","https://openalex.org/W4318473551","https://openalex.org/W4321484183","https://openalex.org/W4366607620","https://openalex.org/W4385079001","https://openalex.org/W4390481609","https://openalex.org/W4392241988","https://openalex.org/W4398249516","https://openalex.org/W4401609679","https://openalex.org/W4401722033","https://openalex.org/W4402125483","https://openalex.org/W4402126220","https://openalex.org/W4403680460","https://openalex.org/W4405938215","https://openalex.org/W4406785116","https://openalex.org/W4407215300","https://openalex.org/W4408919802"],"related_works":[],"abstract_inverted_index":{"Elastic":[0],"optical":[1],"networks":[2],"(EONs)":[3],"must":[4],"allocate":[5],"resources":[6],"dynamically":[7],"to":[8,31,60,95],"accommodate":[9],"heterogeneous,":[10],"high-bandwidth":[11],"demands.":[12],"However,":[13],"the":[14,27,110,137,149,156],"continuous":[15],"setup":[16],"and":[17,29,39,58,114,128,169],"teardown":[18],"of":[19],"connections":[20],"with":[21,77],"different":[22],"bit":[23],"rates":[24],"can":[25],"fragment":[26],"spectrum":[28,71],"lead":[30],"blocking.":[32],"The":[33,133,145],"blocking":[34,62,98,153],"predictors":[35],"enable":[36],"proactive":[37],"defragmentation":[38],"resource":[40],"reallocation":[41],"within":[42],"network":[43],"controllers.":[44],"In":[45],"this":[46],"paper,":[47],"we":[48],"propose":[49],"two":[50],"novel":[51],"deep":[52],"learning":[53,172],"models":[54,140],"(based":[55],"on":[56,109],"CNN\u2013BiLSTM":[57,146],"CNN\u2013LSTM)":[59],"predict":[61],"in":[63,152],"EONs":[64],"by":[65],"combining":[66],"spatial":[67],"feature":[68],"extraction":[69],"from":[70],"snapshots":[72],"using":[73],"2D":[74,123],"convolutional":[75],"layers":[76],"temporal":[78],"sequence":[79],"modeling.":[80],"This":[81],"hybrid":[82],"spatio-temporal":[83],"design":[84],"learns":[85],"how":[86],"local":[87],"fragmentation":[88],"patterns":[89],"evolve":[90],"over":[91],"time,":[92],"allowing":[93],"it":[94,116,164],"detect":[96],"impending":[97],"scenarios":[99],"more":[100],"accurately":[101],"than":[102],"conventional":[103],"methods.":[104],"We":[105],"evaluate":[106],"our":[107],"model":[108,147,158],"simulated":[111],"NSFNET":[112],"topology":[113],"compare":[115],"against":[117],"multiple":[118],"baselines,":[119],"namely":[120],"1D":[121],"CNN,":[122,124],"k-nearest":[125],"neighbors":[126],"(KNN),":[127],"support":[129],"vector":[130],"machines":[131],"(SVMs).":[132],"results":[134],"show":[135],"that":[136],"proposed":[138],"CNN\u2013BiLSTM/LSTM":[139],"consistently":[141],"achieve":[142],"higher":[143],"performance.":[144],"achieved":[148],"highest":[150],"accuracy":[151],"prediction,":[154],"while":[155],"CNN\u2013LSTM":[157],"shows":[159],"slightly":[160],"lower":[161,167],"accuracy;":[162],"however,":[163],"has":[165],"much":[166],"complexity":[168],"a":[170],"faster":[171],"time.":[173]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-05-26T13:28:51.108037","created_date":"2025-10-08T00:00:00"}