{"id":"https://openalex.org/W4401040593","doi":"https://doi.org/10.1093/comjnl/bxae064","title":"DRL-Tomo: a deep reinforcement learning-based approach to augmented data generation for network tomography","display_name":"DRL-Tomo: a deep reinforcement learning-based approach to augmented data generation for network tomography","publication_year":2024,"publication_date":"2024-07-21","ids":{"openalex":"https://openalex.org/W4401040593","doi":"https://doi.org/10.1093/comjnl/bxae064"},"language":"en","primary_location":{"id":"doi:10.1093/comjnl/bxae064","is_oa":false,"landing_page_url":"https://doi.org/10.1093/comjnl/bxae064","pdf_url":null,"source":{"id":"https://openalex.org/S44643521","display_name":"The Computer Journal","issn_l":"0010-4620","issn":["0010-4620","1460-2067"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The Computer Journal","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5065610283","display_name":"Changsheng Hou","orcid":"https://orcid.org/0000-0002-3039-4325"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changsheng Hou","raw_affiliation_strings":["College of Computer, National University of Defense Technology , No. 109 Deya Road, Kaifu District, Changsha City, Hunan Province 410073 , China","College of Computer, National University of Defense Technology, No. 109 Deya Road, Kaifu District, Changsha City, Hunan Province 410073, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer, National University of Defense Technology , No. 109 Deya Road, Kaifu District, Changsha City, Hunan Province 410073 , China","institution_ids":["https://openalex.org/I170215575"]},{"raw_affiliation_string":"College of Computer, National University of Defense Technology, No. 109 Deya Road, Kaifu District, Changsha City, Hunan Province 410073, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042450189","display_name":"Bingnan Hou","orcid":"https://orcid.org/0000-0001-5862-7883"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Bingnan Hou","raw_affiliation_strings":["College of Computer, National University of Defense Technology , No. 109 Deya Road, Kaifu District, Changsha City, Hunan Province 410073 , China","College of Computer, National University of Defense Technology, No. 109 Deya Road, Kaifu District, Changsha City, Hunan Province 410073, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer, National University of Defense Technology , No. 109 Deya Road, Kaifu District, Changsha City, Hunan Province 410073 , China","institution_ids":["https://openalex.org/I170215575"]},{"raw_affiliation_string":"College of Computer, National University of Defense Technology, No. 109 Deya Road, Kaifu District, Changsha City, Hunan Province 410073, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056607788","display_name":"Xionglve Li","orcid":"https://orcid.org/0000-0001-6650-7259"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xionglve Li","raw_affiliation_strings":["College of Computer, National University of Defense Technology , No. 109 Deya Road, Kaifu District, Changsha City, Hunan Province 410073 , China","College of Computer, National University of Defense Technology, No. 109 Deya Road, Kaifu District, Changsha City, Hunan Province 410073, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer, National University of Defense Technology , No. 109 Deya Road, Kaifu District, Changsha City, Hunan Province 410073 , China","institution_ids":["https://openalex.org/I170215575"]},{"raw_affiliation_string":"College of Computer, National University of Defense Technology, No. 109 Deya Road, Kaifu District, Changsha City, Hunan Province 410073, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044528861","display_name":"Tongqing Zhou","orcid":"https://orcid.org/0000-0002-6620-1898"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tongqing Zhou","raw_affiliation_strings":["College of Computer, National University of Defense Technology , No. 109 Deya Road, Kaifu District, Changsha City, Hunan Province 410073 , China","College of Computer, National University of Defense Technology, No. 109 Deya Road, Kaifu District, Changsha City, Hunan Province 410073, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer, National University of Defense Technology , No. 109 Deya Road, Kaifu District, Changsha City, Hunan Province 410073 , China","institution_ids":["https://openalex.org/I170215575"]},{"raw_affiliation_string":"College of Computer, National University of Defense Technology, No. 109 Deya Road, Kaifu District, Changsha City, Hunan Province 410073, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101637286","display_name":"Yingwen Chen","orcid":"https://orcid.org/0000-0002-6433-4216"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yingwen Chen","raw_affiliation_strings":["College of Computer, National University of Defense Technology , No. 109 Deya Road, Kaifu District, Changsha City, Hunan Province 410073 , China","College of Computer, National University of Defense Technology, No. 109 Deya Road, Kaifu District, Changsha City, Hunan Province 410073, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer, National University of Defense Technology , No. 109 Deya Road, Kaifu District, Changsha City, Hunan Province 410073 , China","institution_ids":["https://openalex.org/I170215575"]},{"raw_affiliation_string":"College of Computer, National University of Defense Technology, No. 109 Deya Road, Kaifu District, Changsha City, Hunan Province 410073, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006334685","display_name":"Zhiping Cai","orcid":"https://orcid.org/0000-0001-5726-833X"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhiping Cai","raw_affiliation_strings":["College of Computer, National University of Defense Technology , No. 109 Deya Road, Kaifu District, Changsha City, Hunan Province 410073 , China","College of Computer, National University of Defense Technology, No. 109 Deya Road, Kaifu District, Changsha City, Hunan Province 410073, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer, National University of Defense Technology , No. 109 Deya Road, Kaifu District, Changsha City, Hunan Province 410073 , China","institution_ids":["https://openalex.org/I170215575"]},{"raw_affiliation_string":"College of Computer, National University of Defense Technology, No. 109 Deya Road, Kaifu District, Changsha City, Hunan Province 410073, China","institution_ids":["https://openalex.org/I170215575"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5006334685","https://openalex.org/A5042450189"],"corresponding_institution_ids":["https://openalex.org/I170215575"],"apc_list":{"value":2635,"currency":"GBP","value_usd":3232},"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.11757494,"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/T10138","display_name":"Network Traffic and Congestion Control","score":0.9987000226974487,"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/T10138","display_name":"Network Traffic and Congestion Control","score":0.9987000226974487,"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/T11598","display_name":"Internet Traffic Analysis and Secure E-voting","score":0.9973999857902527,"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"}},{"id":"https://openalex.org/T10714","display_name":"Software-Defined Networks and 5G","score":0.9970999956130981,"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/computer-science","display_name":"Computer science","score":0.7571133375167847},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.6593389511108398},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5802528858184814},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.5705514550209045},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.5128734111785889},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4990222454071045},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.45046254992485046},{"id":"https://openalex.org/keywords/synthetic-data","display_name":"Synthetic data","score":0.4433290362358093},{"id":"https://openalex.org/keywords/network-topology","display_name":"Network topology","score":0.4284886419773102},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4242214560508728},{"id":"https://openalex.org/keywords/network-tomography","display_name":"Network tomography","score":0.41932958364486694},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.12141433358192444}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7571133375167847},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6593389511108398},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5802528858184814},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.5705514550209045},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.5128734111785889},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4990222454071045},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45046254992485046},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.4433290362358093},{"id":"https://openalex.org/C199845137","wikidata":"https://www.wikidata.org/wiki/Q145490","display_name":"Network topology","level":2,"score":0.4284886419773102},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4242214560508728},{"id":"https://openalex.org/C146368544","wikidata":"https://www.wikidata.org/wiki/Q3408544","display_name":"Network tomography","level":3,"score":0.41932958364486694},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.12141433358192444},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1093/comjnl/bxae064","is_oa":false,"landing_page_url":"https://doi.org/10.1093/comjnl/bxae064","pdf_url":null,"source":{"id":"https://openalex.org/S44643521","display_name":"The Computer Journal","issn_l":"0010-4620","issn":["0010-4620","1460-2067"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The Computer Journal","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3624030562","display_name":null,"funder_award_id":"2023TQ0089","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"},{"id":"https://openalex.org/G4715595647","display_name":null,"funder_award_id":"62072465","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6763376774","display_name":null,"funder_award_id":"62172155","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W2044807855","https://openalex.org/W2118404561","https://openalex.org/W2145339207","https://openalex.org/W2162787146","https://openalex.org/W2314670011","https://openalex.org/W2470078708","https://openalex.org/W2584825104","https://openalex.org/W2736601468","https://openalex.org/W2803843146","https://openalex.org/W2898035736","https://openalex.org/W2963490210","https://openalex.org/W2967461022","https://openalex.org/W2995454909","https://openalex.org/W2999871808","https://openalex.org/W3008791560","https://openalex.org/W3035785974","https://openalex.org/W3100789280","https://openalex.org/W3127561923","https://openalex.org/W3131357908","https://openalex.org/W3138360843","https://openalex.org/W3162562816","https://openalex.org/W3205923723","https://openalex.org/W4289537241","https://openalex.org/W4297964528","https://openalex.org/W4385552437","https://openalex.org/W4388561725","https://openalex.org/W4392405403","https://openalex.org/W6772329618"],"related_works":["https://openalex.org/W2361733576","https://openalex.org/W2096664517","https://openalex.org/W2963067051","https://openalex.org/W2349761239","https://openalex.org/W2385058844","https://openalex.org/W2141501134","https://openalex.org/W2347547310","https://openalex.org/W2740718388","https://openalex.org/W2349785426","https://openalex.org/W2390624985"],"abstract_inverted_index":{"Abstract":[0],"Accurate":[1],"and":[2,23,111,170,189],"current":[3],"comprehension":[4],"of":[5,48,148],"network":[6,12,16,28,64,154],"status":[7],"is":[8,83,156],"crucial":[9],"for":[10],"efficient":[11],"management.":[13],"Nevertheless,":[14,104],"direct":[15],"measurement":[17,37],"strategies":[18],"entail":[19],"substantial":[20,182],"traffic":[21],"overhead":[22],"demand":[24],"intricate":[25],"coordination":[26],"among":[27],"entities,":[29],"making":[30],"them":[31],"impractical.":[32],"Network":[33],"tomography,":[34],"an":[35,122,190],"indirect":[36],"approach,":[38],"utilizes":[39],"insights":[40],"garnered":[41],"from":[42,68,90],"measured":[43,109],"parts":[44],"to":[45,96,129],"deduce":[46],"characteristics":[47],"the":[49,62,105,108,116,145],"entire":[50],"network.":[51],"Past":[52],"studies":[53],"frequently":[54],"depend":[55],"on":[56,92],"acquiring":[57],"challenging-to-access":[58],"information,":[59,94],"such":[60,81],"as":[61],"complete":[63],"topology":[65],"or":[66],"support":[67],"specialized":[69],"protocols.":[70],"Unfortunately,":[71],"these":[72],"constraints":[73],"pose":[74],"challenges":[75],"in":[76,185,194],"non-cooperative":[77],"scenarios":[78],"where":[79],"obtaining":[80],"information":[82],"difficult.":[84],"Recent":[85],"endeavors":[86],"pursue":[87],"emancipating":[88],"tomography":[89,124],"dependence":[91],"copious":[93],"striving":[95],"predict":[97],"unmeasured":[98,149],"path":[99,186,195],"performance":[100,113,147],"using":[101,158],"limited":[102],"data.":[103],"disparity":[106],"between":[107],"data":[110,138],"actual":[112],"has":[114],"hindered":[115],"accuracy.":[117],"In":[118],"response,":[119],"we":[120],"introduce":[121],"innovative":[123],"framework":[125],"named":[126],"DRL-Tomo,":[127],"designed":[128],"alleviate":[130],"potential":[131],"biases.":[132],"DRL-Tomo":[133],"initiates":[134],"by":[135],"generating":[136],"augmented":[137,160],"through":[139],"deep":[140],"reinforcement":[141],"learning,":[142],"gradually":[143],"approximating":[144],"genuine":[146],"paths.":[150],"Subsequently,":[151],"a":[152,181],"neural":[153],"model":[155],"trained":[157],"this":[159],"data,":[161],"enabling":[162],"precise":[163],"inferences.":[164],"Our":[165],"experiments,":[166],"encompassing":[167],"both":[168],"real-world":[169],"synthetic":[171],"datasets,":[172],"vividly":[173],"demonstrate":[174],"DRL-Tomo\u2019s":[175],"remarkable":[176],"enhancement.":[177],"Specifically,":[178],"it":[179],"achieves":[180],"10%\u201367%":[183],"improvement":[184],"delay":[187],"prediction":[188],"impressive":[191],"30%\u201398%":[192],"enhancement":[193],"loss":[196],"rate":[197],"prediction.":[198]},"counts_by_year":[],"updated_date":"2026-06-16T07:32:37.131356","created_date":"2025-10-10T00:00:00"}
