{"id":"https://openalex.org/W4390098488","doi":"https://doi.org/10.23919/wiopt58741.2023.10349881","title":"Age-of-Information Minimization for Energy Harvesting Sensor in Non-Stationary Environment","display_name":"Age-of-Information Minimization for Energy Harvesting Sensor in Non-Stationary Environment","publication_year":2023,"publication_date":"2023-08-24","ids":{"openalex":"https://openalex.org/W4390098488","doi":"https://doi.org/10.23919/wiopt58741.2023.10349881"},"language":"en","primary_location":{"id":"doi:10.23919/wiopt58741.2023.10349881","is_oa":false,"landing_page_url":"https://doi.org/10.23919/wiopt58741.2023.10349881","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 21st International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt)","raw_type":"proceedings-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/A5072036535","display_name":"Akanksha Jaiswal","orcid":"https://orcid.org/0000-0001-8997-0668"},"institutions":[{"id":"https://openalex.org/I68891433","display_name":"Indian Institute of Technology Delhi","ror":"https://ror.org/049tgcd06","country_code":"IN","type":"education","lineage":["https://openalex.org/I68891433"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Akanksha Jaiswal","raw_affiliation_strings":["Indian Institute of Technology,Department of Electrical Engineering,Delhi","Department of Electrical Engineering, Indian Institute of Technology, Delhi"],"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology,Department of Electrical Engineering,Delhi","institution_ids":[]},{"raw_affiliation_string":"Department of Electrical Engineering, Indian Institute of Technology, Delhi","institution_ids":["https://openalex.org/I68891433"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086971942","display_name":"Arpan Chattopadhyay","orcid":"https://orcid.org/0000-0002-2684-5912"},"institutions":[{"id":"https://openalex.org/I68891433","display_name":"Indian Institute of Technology Delhi","ror":"https://ror.org/049tgcd06","country_code":"IN","type":"education","lineage":["https://openalex.org/I68891433"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Arpan Chattopadhyay","raw_affiliation_strings":["Bharti School of Telecom Technology and Management, Indian Institute of Technology,Department of Electrical Engineering,Delhi","Department of Electrical Engineering, Bharti School of Telecom Technology and Management, Indian Institute of Technology, Delhi"],"affiliations":[{"raw_affiliation_string":"Bharti School of Telecom Technology and Management, Indian Institute of Technology,Department of Electrical Engineering,Delhi","institution_ids":["https://openalex.org/I68891433"]},{"raw_affiliation_string":"Department of Electrical Engineering, Bharti School of Telecom Technology and Management, Indian Institute of Technology, Delhi","institution_ids":["https://openalex.org/I68891433"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5072036535"],"corresponding_institution_ids":["https://openalex.org/I68891433"],"apc_list":null,"apc_paid":null,"fwci":0.4024,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.63871907,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13553","display_name":"Age of Information Optimization","score":1.0,"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/T13553","display_name":"Age of Information Optimization","score":1.0,"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/T11392","display_name":"Energy Harvesting in Wireless Networks","score":0.9839000105857849,"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/T10300","display_name":"Congenital Heart Disease Studies","score":0.979200005531311,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.7805845737457275},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.7277032136917114},{"id":"https://openalex.org/keywords/markov-decision-process","display_name":"Markov decision process","score":0.6424534916877747},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6256322264671326},{"id":"https://openalex.org/keywords/upper-and-lower-bounds","display_name":"Upper and lower bounds","score":0.5640168786048889},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.5277484059333801},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.5242748260498047},{"id":"https://openalex.org/keywords/wireless-sensor-network","display_name":"Wireless sensor network","score":0.49618226289749146},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.4819750189781189},{"id":"https://openalex.org/keywords/minification","display_name":"Minification","score":0.4719585180282593},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.46623843908309937},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.4465406835079193},{"id":"https://openalex.org/keywords/time-horizon","display_name":"Time horizon","score":0.42933544516563416},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3858620226383209},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3151369094848633},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21644437313079834},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.19722646474838257},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.18861833214759827},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.09284329414367676}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7805845737457275},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7277032136917114},{"id":"https://openalex.org/C106189395","wikidata":"https://www.wikidata.org/wiki/Q176789","display_name":"Markov decision process","level":3,"score":0.6424534916877747},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6256322264671326},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.5640168786048889},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.5277484059333801},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.5242748260498047},{"id":"https://openalex.org/C24590314","wikidata":"https://www.wikidata.org/wiki/Q336038","display_name":"Wireless sensor network","level":2,"score":0.49618226289749146},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4819750189781189},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.4719585180282593},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.46623843908309937},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.4465406835079193},{"id":"https://openalex.org/C28761237","wikidata":"https://www.wikidata.org/wiki/Q7805321","display_name":"Time horizon","level":2,"score":0.42933544516563416},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3858620226383209},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3151369094848633},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21644437313079834},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.19722646474838257},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.18861833214759827},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.09284329414367676},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/wiopt58741.2023.10349881","is_oa":false,"landing_page_url":"https://doi.org/10.23919/wiopt58741.2023.10349881","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 21st International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7300000190734863,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W1944301273","https://openalex.org/W1993918491","https://openalex.org/W2039522160","https://openalex.org/W2132908009","https://openalex.org/W2168405694","https://openalex.org/W2344944957","https://openalex.org/W2649848418","https://openalex.org/W2943927637","https://openalex.org/W2944580845","https://openalex.org/W2950929549","https://openalex.org/W2962999278","https://openalex.org/W2964132277","https://openalex.org/W3019450228","https://openalex.org/W3020925646","https://openalex.org/W3025093529","https://openalex.org/W3030314836","https://openalex.org/W3047528331","https://openalex.org/W3080482303","https://openalex.org/W3099984989","https://openalex.org/W3121822496","https://openalex.org/W3173628078","https://openalex.org/W3177445803","https://openalex.org/W3196809998","https://openalex.org/W3203778212","https://openalex.org/W3203829635","https://openalex.org/W4206530644","https://openalex.org/W4206547457","https://openalex.org/W4295177675","https://openalex.org/W4382239223","https://openalex.org/W6640648879","https://openalex.org/W6679661297","https://openalex.org/W6698158655","https://openalex.org/W6704438963","https://openalex.org/W6751346906","https://openalex.org/W6780394777","https://openalex.org/W6797943150"],"related_works":["https://openalex.org/W4400868993","https://openalex.org/W3096874164","https://openalex.org/W1985560493","https://openalex.org/W2937181779","https://openalex.org/W2386410636","https://openalex.org/W2357975469","https://openalex.org/W2145363145","https://openalex.org/W1626977535","https://openalex.org/W2341346307","https://openalex.org/W3168977894"],"abstract_inverted_index":{"In":[0],"this":[1,92],"paper,":[2],"we":[3,90,151,162],"consider":[4],"age-of-information":[5],"(AoI)":[6],"minimization":[7],"for":[8,66,85,134],"an":[9,97,115,153],"energy":[10,108],"harvesting":[11,109],"(EH)":[12],"source":[13,28],"that":[14],"samples":[15],"and":[16,36,39,44,61,95,106,111],"sends":[17],"the":[18,27,30,33,37,46,49,53,67,74,119,128,135,146,164],"observations":[19],"to":[20,42,48,103,118],"a":[21,56,63],"sink":[22],"node.":[23],"At":[24],"each":[25,123],"time,":[26],"observes":[29],"channel":[31,112],"quality,":[32],"available":[34],"energy,":[35],"age,":[38],"decides":[40],"whether":[41],"sample":[43],"send":[45],"observation":[47],"sink.":[50],"We":[51],"formulate":[52],"problem":[54],"as":[55],"Markov":[57],"decision":[58],"process":[59],"(MDP)":[60],"establish":[62],"threshold":[64,93],"structure":[65,94],"optimal":[68],"sampling":[69],"policy.":[70],"Next,":[71,133],"motivated":[72,144],"by":[73,145],"popular":[75,147],"sliding":[76],"window":[77],"upper":[78,116],"confidence":[79],"bound":[80,117],"reinforcement":[81,87],"learning":[82,88,159],"(SW-UCRL2)":[83],"algorithm":[84,102,154],"non-stationary":[86],"(RL),":[89],"leverage":[91],"propose":[96,152],"age-energy-channel":[98,156],"based":[99,157],"SW-UCRL2":[100],"(AEC-SW-UCRL2)":[101],"handle":[104],"unknown":[105],"time-varying":[107],"rate":[110],"statistics,":[113],"when":[114,137],"total":[120],"variation":[121,139],"of":[122,124,168],"these":[125,138,169],"quantities":[126],"over":[127],"time":[129],"horizon":[130],"is":[131],"available.":[132],"case":[136],"budgets":[140],"are":[141],"not":[142],"available,":[143],"bandit-over-RL":[148],"(BORL)":[149],"algorithm,":[150],"named":[155],"bandit-over-reinforcement":[158],"(AEC-BORL).":[160],"Finally,":[161],"demonstrate":[163],"superior":[165],"numerical":[166,173],"performance":[167],"proposed":[170],"algorithms":[171],"via":[172],"experiments.":[174]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}