{"id":"https://openalex.org/W4413823712","doi":"https://doi.org/10.1109/icccn65249.2025.11133783","title":"Edge Serverless Autoscaling managed via Proximal Policy Optimization","display_name":"Edge Serverless Autoscaling managed via Proximal Policy Optimization","publication_year":2025,"publication_date":"2025-08-04","ids":{"openalex":"https://openalex.org/W4413823712","doi":"https://doi.org/10.1109/icccn65249.2025.11133783"},"language":"en","primary_location":{"id":"doi:10.1109/icccn65249.2025.11133783","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icccn65249.2025.11133783","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 34th International Conference on Computer Communications and Networks (ICCCN)","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/A5053723295","display_name":"Mauro Femminella","orcid":"https://orcid.org/0000-0002-6695-5956"},"institutions":[{"id":"https://openalex.org/I27483092","display_name":"University of Perugia","ror":"https://ror.org/00x27da85","country_code":"IT","type":"education","lineage":["https://openalex.org/I27483092"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Mauro Femminella","raw_affiliation_strings":["University of Perugia, CNIT RU,Dept. of Engineering,Perugia,Italy"],"affiliations":[{"raw_affiliation_string":"University of Perugia, CNIT RU,Dept. of Engineering,Perugia,Italy","institution_ids":["https://openalex.org/I27483092"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070042849","display_name":"Gianluca Reali","orcid":"https://orcid.org/0000-0002-8567-5917"},"institutions":[{"id":"https://openalex.org/I27483092","display_name":"University of Perugia","ror":"https://ror.org/00x27da85","country_code":"IT","type":"education","lineage":["https://openalex.org/I27483092"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Gianluca Reali","raw_affiliation_strings":["University of Perugia, CNIT RU,Dept. of Engineering,Perugia,Italy"],"affiliations":[{"raw_affiliation_string":"University of Perugia, CNIT RU,Dept. of Engineering,Perugia,Italy","institution_ids":["https://openalex.org/I27483092"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5053723295"],"corresponding_institution_ids":["https://openalex.org/I27483092"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.31166291,"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/T10715","display_name":"Distributed and Parallel Computing Systems","score":0.9190999865531921,"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/T10715","display_name":"Distributed and Parallel Computing Systems","score":0.9190999865531921,"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":0.7157143354415894},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.5912308096885681},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.3396434485912323},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.1783788800239563}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7157143354415894},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.5912308096885681},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3396434485912323},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.1783788800239563}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icccn65249.2025.11133783","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icccn65249.2025.11133783","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 34th International Conference on Computer Communications and Networks (ICCCN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W2890276825","https://openalex.org/W2894001169","https://openalex.org/W2915771847","https://openalex.org/W2915850828","https://openalex.org/W2986344765","https://openalex.org/W3023238978","https://openalex.org/W3127529544","https://openalex.org/W3191752327","https://openalex.org/W4205552495","https://openalex.org/W4394744886","https://openalex.org/W4401943313","https://openalex.org/W4402306013","https://openalex.org/W4404734757","https://openalex.org/W4410083831"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Serverless":[0],"computing":[1],"is":[2,8,51,76],"an":[3,52],"emerging":[4],"service":[5,49],"model":[6],"that":[7],"gaining":[9],"consensus":[10],"in":[11,29,41,66],"both":[12,94],"edge":[13,42,67],"and":[14,72,97,159,178],"core":[15],"clouds.":[16],"In":[17,101],"fact,":[18],"it":[19,90],"allows":[20],"developers":[21],"focusing":[22,155],"on":[23,106,116,124,146,156],"application":[24],"codes,":[25],"breaking":[26],"down":[27],"services":[28],"multiple":[30],"functions,":[31],"without":[32],"the":[33,107,118,129,137,140,152],"burden":[34],"of":[35,82,109,139],"platform":[36],"management.":[37],"Services":[38],"are":[39,70],"run":[40],"clouds,":[43],"closer":[44],"to":[45,93,112,134,167],"end-users\u2019":[46],"devices,":[47],"when":[48],"latency":[50,56,96],"important":[53],"constraint.":[54],"However,":[55],"control":[57],"cannot":[58],"be":[59],"achieved":[60],"with":[61,165,175],"ample":[62],"resource":[63,99],"allocation,":[64],"as":[65,89,170,172],"environments":[68],"resources":[69],"limited":[71],"thus":[73],"operational":[74],"efficiency":[75],"essential.":[77],"For":[78],"these":[79],"reasons,":[80],"autoscaling":[81,115],"serverless":[83,121],"functions":[84],"has":[85],"a":[86],"central":[87],"role,":[88],"can":[91],"lead":[92],"reduced":[95],"efficient":[98],"usage.":[100],"this":[102],"work,":[103],"we":[104],"focus":[105],"usage":[108],"reinforcement":[110],"learning":[111],"drive":[113],"resource-based":[114],"OpenFaaS,":[117],"most-adopted":[119],"open-source":[120],"platform,":[122],"running":[123],"Kubernetes":[125,141],"clusters.":[126],"We":[127,150],"use":[128],"Proximal":[130],"Policy":[131],"Optimization":[132],"algorithm":[133,153],"dynamically":[135],"configure":[136],"value":[138],"Horizontal":[142],"Pod":[143],"Autoscaler,":[144],"trained":[145],"Azure":[147],"traffic":[148,168],"traces.":[149],"discuss":[151],"configuration,":[154],"state":[157],"definition":[158],"relevant":[160],"performance":[161,173],"evaluation,":[162],"including":[163],"robustness":[164],"respect":[166],"burstiness,":[169],"well":[171],"comparison":[174],"baseline":[176],"approach":[177],"heuristics.":[179]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
