{"id":"https://openalex.org/W4416233446","doi":"https://doi.org/10.1109/wisee57913.2025.11229839","title":"Deep Reinforcement Learning for Routing in Uncertain DTNs with Graph Neural Networks","display_name":"Deep Reinforcement Learning for Routing in Uncertain DTNs with Graph Neural Networks","publication_year":2025,"publication_date":"2025-10-14","ids":{"openalex":"https://openalex.org/W4416233446","doi":"https://doi.org/10.1109/wisee57913.2025.11229839"},"language":"en","primary_location":{"id":"doi:10.1109/wisee57913.2025.11229839","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wisee57913.2025.11229839","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Wireless for Space and Extreme Environments (WiSEE)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://hal.science/hal-05413586","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5120650320","display_name":"Valentin Negrelli","orcid":null},"institutions":[{"id":"https://openalex.org/I2799978770","display_name":"X-Fab (Germany)","ror":"https://ror.org/030bh9196","country_code":"DE","type":"company","lineage":["https://openalex.org/I2799978770"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Valentin Negrelli","raw_affiliation_strings":["Universidad Nacional de Córdoba,Facultad de Matemática, Astronomía, Física y Computación (FAMAF),Argentina"],"affiliations":[{"raw_affiliation_string":"Universidad Nacional de Córdoba,Facultad de Matemática, Astronomía, Física y Computación (FAMAF),Argentina","institution_ids":["https://openalex.org/I2799978770"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004265236","display_name":"Renato Cherini","orcid":"https://orcid.org/0009-0004-3747-5306"},"institutions":[{"id":"https://openalex.org/I53241121","display_name":"Fundaci\u00f3n Ciencias Exactas y Naturales","ror":"https://ror.org/05rxmkq09","country_code":"AR","type":"nonprofit","lineage":["https://openalex.org/I53241121"]}],"countries":["AR"],"is_corresponding":false,"raw_author_name":"Renato Cherini","raw_affiliation_strings":["Universidad Nacional de Córdoba,Facultad de Ciencias Exactas, Físicas y Naturales (FCEFyN),Argentina"],"affiliations":[{"raw_affiliation_string":"Universidad Nacional de Córdoba,Facultad de Ciencias Exactas, Físicas y Naturales (FCEFyN),Argentina","institution_ids":["https://openalex.org/I53241121"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081269372","display_name":"Juan A. Fraire","orcid":"https://orcid.org/0000-0001-9816-6989"},"institutions":[{"id":"https://openalex.org/I151201029","display_name":"Consejo Nacional de Investigaciones Cient\u00edficas y T\u00e9cnicas","ror":"https://ror.org/03cqe8w59","country_code":"AR","type":"funder","lineage":["https://openalex.org/I151201029","https://openalex.org/I4210123736","https://openalex.org/I4387155568"]}],"countries":["AR"],"is_corresponding":false,"raw_author_name":"Juan A. Fraire","raw_affiliation_strings":["CONICET - Universidad Nacional de Córdoba,Córdoba,Argentina"],"affiliations":[{"raw_affiliation_string":"CONICET - Universidad Nacional de Córdoba,Córdoba,Argentina","institution_ids":["https://openalex.org/I151201029"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5120650320"],"corresponding_institution_ids":["https://openalex.org/I2799978770"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.41872161,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11896","display_name":"Opportunistic and Delay-Tolerant Networks","score":0.9955000281333923,"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"}},"topics":[{"id":"https://openalex.org/T11896","display_name":"Opportunistic and Delay-Tolerant Networks","score":0.9955000281333923,"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/T13553","display_name":"Age of Information Optimization","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/T10714","display_name":"Software-Defined Networks and 5G","score":0.00039999998989515007,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.70169997215271},{"id":"https://openalex.org/keywords/adaptability","display_name":"Adaptability","score":0.6567999720573425},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.6037999987602234},{"id":"https://openalex.org/keywords/markov-decision-process","display_name":"Markov decision process","score":0.5713000297546387},{"id":"https://openalex.org/keywords/routing","display_name":"Routing (electronic design automation)","score":0.5511000156402588},{"id":"https://openalex.org/keywords/partially-observable-markov-decision-process","display_name":"Partially observable Markov decision process","score":0.46619999408721924},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.46459999680519104},{"id":"https://openalex.org/keywords/network-topology","display_name":"Network topology","score":0.43529999256134033},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.42149999737739563}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7473999857902527},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.70169997215271},{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.6567999720573425},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.6037999987602234},{"id":"https://openalex.org/C106189395","wikidata":"https://www.wikidata.org/wiki/Q176789","display_name":"Markov decision process","level":3,"score":0.5713000297546387},{"id":"https://openalex.org/C74172769","wikidata":"https://www.wikidata.org/wiki/Q1446839","display_name":"Routing (electronic design automation)","level":2,"score":0.5511000156402588},{"id":"https://openalex.org/C17098449","wikidata":"https://www.wikidata.org/wiki/Q176814","display_name":"Partially observable Markov decision process","level":4,"score":0.46619999408721924},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.46540001034736633},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.46459999680519104},{"id":"https://openalex.org/C199845137","wikidata":"https://www.wikidata.org/wiki/Q145490","display_name":"Network topology","level":2,"score":0.43529999256134033},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.42149999737739563},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.39469999074935913},{"id":"https://openalex.org/C204948658","wikidata":"https://www.wikidata.org/wiki/Q1119410","display_name":"Static routing","level":4,"score":0.39070001244544983},{"id":"https://openalex.org/C104954878","wikidata":"https://www.wikidata.org/wiki/Q1648707","display_name":"Routing protocol","level":3,"score":0.38260000944137573},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.38100001215934753},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.36559998989105225},{"id":"https://openalex.org/C89305328","wikidata":"https://www.wikidata.org/wiki/Q1755411","display_name":"Link-state routing protocol","level":4,"score":0.3637000024318695},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35030001401901245},{"id":"https://openalex.org/C94600068","wikidata":"https://www.wikidata.org/wiki/Q7371621","display_name":"Routing domain","level":5,"score":0.3046000003814697},{"id":"https://openalex.org/C50558702","wikidata":"https://www.wikidata.org/wiki/Q5535067","display_name":"Geographic routing","level":5,"score":0.29499998688697815},{"id":"https://openalex.org/C196423136","wikidata":"https://www.wikidata.org/wiki/Q7209671","display_name":"Policy-based routing","level":5,"score":0.28619998693466187},{"id":"https://openalex.org/C184896649","wikidata":"https://www.wikidata.org/wiki/Q290066","display_name":"Routing table","level":4,"score":0.27090001106262207},{"id":"https://openalex.org/C9659607","wikidata":"https://www.wikidata.org/wiki/Q1268903","display_name":"Dynamic Source Routing","level":4,"score":0.2678999900817871},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.26750001311302185},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.2662999927997589},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2630000114440918},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.2621000111103058},{"id":"https://openalex.org/C94523657","wikidata":"https://www.wikidata.org/wiki/Q4085781","display_name":"Wireless ad hoc network","level":3,"score":0.26080000400543213},{"id":"https://openalex.org/C177818476","wikidata":"https://www.wikidata.org/wiki/Q12878103","display_name":"Hierarchical routing","level":5,"score":0.25099998712539673}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/wisee57913.2025.11229839","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wisee57913.2025.11229839","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Wireless for Space and Extreme Environments (WiSEE)","raw_type":"proceedings-article"},{"id":"pmh:oai:HAL:hal-05413586v1","is_oa":true,"landing_page_url":"https://hal.science/hal-05413586","pdf_url":null,"source":{"id":"https://openalex.org/S4406922461","display_name":"SPIRE - Sciences Po Institutional REpository","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"WiSEE 2025 - IEEE International Conference on Wireless for Space and Extreme Environments, Oct 2025, Halifax, Canada. pp.1-6, ⟨10.1109/WiSEE57913.2025.11229839⟩","raw_type":"Conference papers"}],"best_oa_location":{"id":"pmh:oai:HAL:hal-05413586v1","is_oa":true,"landing_page_url":"https://hal.science/hal-05413586","pdf_url":null,"source":{"id":"https://openalex.org/S4406922461","display_name":"SPIRE - Sciences Po Institutional REpository","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"WiSEE 2025 - IEEE International Conference on Wireless for Space and Extreme Environments, Oct 2025, Halifax, Canada. pp.1-6, ⟨10.1109/WiSEE57913.2025.11229839⟩","raw_type":"Conference papers"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W275084143","https://openalex.org/W1488540163","https://openalex.org/W1499021164","https://openalex.org/W1557517019","https://openalex.org/W1862398452","https://openalex.org/W2022019677","https://openalex.org/W2107544712","https://openalex.org/W2145339207","https://openalex.org/W2273515758","https://openalex.org/W2568766587","https://openalex.org/W2597167070","https://openalex.org/W2730319792","https://openalex.org/W2773836826","https://openalex.org/W2787596386","https://openalex.org/W2911528412","https://openalex.org/W3047922642","https://openalex.org/W3098986442","https://openalex.org/W3179132544","https://openalex.org/W3198599901","https://openalex.org/W4210728322","https://openalex.org/W4213251304","https://openalex.org/W4366721447","https://openalex.org/W4399017885","https://openalex.org/W4401540262"],"related_works":[],"abstract_inverted_index":{"We":[0,29,102],"address":[1],"the":[2,85],"routing":[3,43,72],"optimization":[4],"problem":[5],"in":[6],"Delay/Disruption":[7],"Tolerant":[8],"Networks":[9],"under":[10,36],"uncertain":[11],"contact":[12,15],"plans,":[13],"where":[14],"time":[16],"bounds":[17],"are":[18],"known":[19],"but":[20],"link":[21,98,139],"availability":[22],"is":[23],"probabilistic":[24],"and":[25,56,107,123,141],"subject":[26],"to":[27,83,91,137],"failures.":[28],"propose":[30],"GROGU":[31,67,104,130],"(Graph-based":[32],"Routing":[33],"for":[34],"Optimizing":[35],"GNN-driven":[37],"Uncertain":[38],"DTNs),":[39],"a":[40,50,62,69],"novel":[41],"decentralized":[42],"algorithm":[44],"that":[45,129],"models":[46],"forwarding":[47],"decisions":[48],"as":[49,95],"partially":[51],"observable":[52],"Markov":[53],"decision":[54],"process":[55],"leverages":[57],"Deep":[58],"Reinforcement":[59],"Learning":[60],"with":[61],"Graph":[63,125],"Neural":[64],"Network":[65],"architecture.":[66],"learns":[68],"single,":[70],"reusable":[71],"policy":[73],"deployable":[74],"across":[75],"all":[76],"nodes,":[77],"using":[78],"Monte":[79],"Carlo-driven":[80],"simulated":[81],"experiences":[82],"maximize":[84],"successful":[86],"delivery":[87,133],"probability":[88],"while":[89],"adapting":[90],"topology":[92],"changes":[93],"such":[94],"node":[96],"or":[97],"failures":[99],"without":[100],"retraining.":[101],"evaluate":[103],"on":[105],"synthetic":[106],"realistic":[108],"satellite":[109],"network":[110],"topologies,":[111],"comparing":[112],"it":[113],"against":[114],"state-of-the-art":[115],"methods":[116],"including":[117],"RUCoP,":[118],"Lightweight":[119],"Scheduler":[120],"Sampling,":[121],"Q-learning,":[122],"Contact":[124],"Routing.":[126],"Results":[127],"show":[128],"achieves":[131],"competitive":[132],"performance,":[134],"robust":[135],"adaptability":[136],"unforeseen":[138],"outages,":[140],"fast":[142],"convergence,":[143],"albeit":[144],"at":[145],"higher":[146],"training":[147],"costs.":[148]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-11-13T00:00:00"}