{"id":"https://openalex.org/W7160913010","doi":"https://doi.org/10.48550/arxiv.2605.09508","title":"Risk-Aware Safe Throughput Forecasting for Starlink Networks","display_name":"Risk-Aware Safe Throughput Forecasting for Starlink Networks","publication_year":2026,"publication_date":"2026-05-10","ids":{"openalex":"https://openalex.org/W7160913010","doi":"https://doi.org/10.48550/arxiv.2605.09508"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.09508","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.09508","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.09508","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5135923341","display_name":"Hongjun Xie","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xie, Hongjun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135964138","display_name":"Chao Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Chao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135929520","display_name":"Pengcheng Luo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Luo, Pengcheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059094652","display_name":"Zenghui Zhang","orcid":"https://orcid.org/0000-0002-1238-8538"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Zenghui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135912653","display_name":"Genke Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Genke","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135965711","display_name":"Xiaojuan Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Xiaojuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5135946523","display_name":"Boon-Hee Soong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Soong, Boon-Hee","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":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"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/T12042","display_name":"Satellite Communication Systems","score":0.6966000199317932,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T12042","display_name":"Satellite Communication Systems","score":0.6966000199317932,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T10138","display_name":"Network Traffic and Congestion Control","score":0.048700001090765,"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/T11896","display_name":"Opportunistic and Delay-Tolerant Networks","score":0.021700000390410423,"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/throughput","display_name":"Throughput","score":0.5885000228881836},{"id":"https://openalex.org/keywords/boundary","display_name":"Boundary (topology)","score":0.45820000767707825},{"id":"https://openalex.org/keywords/quantile","display_name":"Quantile","score":0.45730000734329224},{"id":"https://openalex.org/keywords/bandwidth","display_name":"Bandwidth (computing)","score":0.45100000500679016},{"id":"https://openalex.org/keywords/broadband","display_name":"Broadband","score":0.4487999975681305},{"id":"https://openalex.org/keywords/quantile-regression","display_name":"Quantile regression","score":0.4311999976634979},{"id":"https://openalex.org/keywords/variable","display_name":"Variable (mathematics)","score":0.3637000024318695},{"id":"https://openalex.org/keywords/bounded-function","display_name":"Bounded function","score":0.3440000116825104}],"concepts":[{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.5885000228881836},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5738000273704529},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.45820000767707825},{"id":"https://openalex.org/C118671147","wikidata":"https://www.wikidata.org/wiki/Q578714","display_name":"Quantile","level":2,"score":0.45730000734329224},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.45100000500679016},{"id":"https://openalex.org/C509933004","wikidata":"https://www.wikidata.org/wiki/Q194163","display_name":"Broadband","level":2,"score":0.4487999975681305},{"id":"https://openalex.org/C63817138","wikidata":"https://www.wikidata.org/wiki/Q3455889","display_name":"Quantile regression","level":2,"score":0.4311999976634979},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.3637000024318695},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3547999858856201},{"id":"https://openalex.org/C34388435","wikidata":"https://www.wikidata.org/wiki/Q2267362","display_name":"Bounded function","level":2,"score":0.3440000116825104},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.34130001068115234},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.32359999418258667},{"id":"https://openalex.org/C190839683","wikidata":"https://www.wikidata.org/wiki/Q2448197","display_name":"Train","level":2,"score":0.3208000063896179},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3188999891281128},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.314300000667572},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.3052000105381012},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.3034999966621399},{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.2838999927043915},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.2825999855995178},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.2816999852657318},{"id":"https://openalex.org/C2778160497","wikidata":"https://www.wikidata.org/wiki/Q869830","display_name":"Service-level agreement","level":3,"score":0.2619999945163727},{"id":"https://openalex.org/C2780378061","wikidata":"https://www.wikidata.org/wiki/Q25351891","display_name":"Service (business)","level":2,"score":0.2619999945163727},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.25429999828338623}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.09508","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.09508","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.09508","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.09508","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"display_name":"Decent work and economic growth","score":0.4566746950149536,"id":"https://metadata.un.org/sdg/8"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"As":[0],"a":[1,65,75,90,95],"representative":[2],"low":[3],"Earth":[4],"orbit":[5],"(LEO)":[6],"broadband":[7],"system,":[8],"Starlink":[9,61,124],"exhibits":[10],"highly":[11],"variable":[12],"access":[13],"throughput,":[14,48],"making":[15],"short-term":[16],"forecasting":[17,24,68,185],"essential":[18],"for":[19],"network":[20],"resource":[21],"management.":[22],"Existing":[23],"methods":[25],"mainly":[26],"optimize":[27],"symmetric":[28],"point-prediction":[29],"metrics":[30],"such":[31],"as":[32,64],"MAE":[33],"and":[34,55,108,137,146,155,166],"RMSE,":[35],"but":[36],"they":[37],"do":[38],"not":[39],"explicitly":[40],"control":[41],"the":[42,71,101,105,110,115,131,139,175],"asymmetric":[43],"risk":[44,106,132],"of":[45,97],"overestimating":[46],"future":[47],"which":[49],"can":[50,186],"cause":[51],"over-admission,":[52],"bandwidth":[53],"overbooking,":[54],"service":[56],"violations.":[57],"This":[58],"paper":[59],"formulates":[60],"throughput":[62,125],"prediction":[63,188],"risk-budgeted":[66],"safe":[67,177],"problem,":[69],"where":[70],"predictor":[72],"must":[73],"satisfy":[74],"prescribed":[76],"overestimation":[77],"budget":[78,133],"while":[79],"maintaining":[80],"competitive":[81],"accuracy.":[82],"We":[83],"propose":[84],"Budget-Guided":[85],"Coarse-to-Fine":[86],"Quantile":[87],"Selection":[88],"(BG-CFQS),":[89],"data-driven":[91],"framework":[92],"that":[93,128,174,183],"trains":[94],"family":[96],"lower-quantile":[98],"predictors,":[99],"locates":[100],"quantile":[102],"boundary":[103,111],"satisfying":[104],"budget,":[107],"refines":[109],"region":[112],"to":[113],"select":[114],"most":[116],"accurate":[117],"feasible":[118],"predictor.":[119],"Experiments":[120],"on":[121,134],"three":[122],"real-world":[123],"datasets":[126,136],"show":[127],"BG-CFQS":[129,159],"satisfies":[130],"all":[135],"achieves":[138],"lowest":[140],"average":[141],"MAE,":[142],"mean":[143],"positive":[144,148,162],"error,":[145],"tail":[147],"error":[149],"among":[150],"budget-feasible":[151],"methods.":[152],"In":[153],"high-risk":[154],"severe-risk":[156],"low-throughput":[157],"regimes,":[158],"reduces":[160],"harmful":[161],"errors":[163],"by":[164],"11.0%":[165],"12.6%,":[167],"respectively.":[168],"An":[169],"admission-control":[170],"evaluation":[171],"further":[172],"shows":[173],"proposed":[176],"forecasts":[178],"reduce":[179],"dropped":[180],"sessions,":[181],"demonstrating":[182],"risk-aware":[184],"translate":[187],"safety":[189],"into":[190],"application-level":[191],"benefits.":[192]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-13T00:00:00"}
