{"id":"https://openalex.org/W1998354386","doi":"https://doi.org/10.1145/2034832.2034858","title":"Poster","display_name":"Poster","publication_year":2011,"publication_date":"2011-09-15","ids":{"openalex":"https://openalex.org/W1998354386","doi":"https://doi.org/10.1145/2034832.2034858","mag":"1998354386"},"language":"en","primary_location":{"id":"doi:10.1145/2034832.2034858","doi":"https://doi.org/10.1145/2034832.2034858","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2034832.2034858","pdf_url":null,"source":{"id":"https://openalex.org/S4210187660","display_name":"ACM SIGMETRICS Performance Evaluation Review","issn_l":"0163-5999","issn":["0163-5999","1557-9484"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-scientific","cwts-core","norway-1","poland-70","russia-white-list-3"],"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM SIGMETRICS Performance Evaluation Review","raw_type":"journal-article"},"volume":null,"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/A5108284116","display_name":"William A. Massey","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I20089843","display_name":"Princeton University","ror":"https://ror.org/00hx57361","country_code":"US","type":"education","lineage":["https://openalex.org/I20089843"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"William A. Massey","raw_affiliation_strings":["Princeton University","Princeton University#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Princeton University","institution_ids":["https://openalex.org/I20089843"]},{"raw_affiliation_string":"Princeton University#TAB#","institution_ids":["https://openalex.org/I20089843"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011271976","display_name":"Jamol J. Pender","orcid":"https://orcid.org/0000-0002-5418-6918","observed_orcids":["https://orcid.org/0000-0002-5418-6918"]},"institutions":[{"id":"https://openalex.org/I20089843","display_name":"Princeton University","ror":"https://ror.org/00hx57361","country_code":"US","type":"education","lineage":["https://openalex.org/I20089843"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jamol Pender","raw_affiliation_strings":["Princeton University","Princeton University#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Princeton University","institution_ids":["https://openalex.org/I20089843"]},{"raw_affiliation_string":"Princeton University#TAB#","institution_ids":["https://openalex.org/I20089843"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I20089843"],"apc_list":null,"apc_paid":null,"fwci":3.2426,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.91507838,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"39","issue":"2","first_page":"74","last_page":"74"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10974","display_name":"Advanced Queuing Theory Analysis","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/1404","display_name":"Management Information Systems"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10974","display_name":"Advanced Queuing Theory Analysis","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/1404","display_name":"Management Information Systems"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11152","display_name":"Stochastic processes and statistical mechanics","score":9.999999747378752e-05,"subfield":{"id":"https://openalex.org/subfields/2610","display_name":"Mathematical Physics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11773","display_name":"Healthcare Operations and Scheduling Optimization","score":9.999999747378752e-05,"subfield":{"id":"https://openalex.org/subfields/3604","display_name":"Emergency Medical Services"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/multi-server-queues","display_name":"multi-server queues","score":0.8740000128746033},{"id":"https://openalex.org/keywords/customer-abandonment","display_name":"customer abandonment","score":0.9169999957084656},{"id":"https://openalex.org/keywords/asymptotic-scaling","display_name":"asymptotic scaling","score":0.6420000195503235},{"id":"https://openalex.org/keywords/fluid-model","display_name":"fluid model","score":0.800000011920929},{"id":"https://openalex.org/keywords/diffusion-approximation","display_name":"diffusion approximation","score":0.8920000195503235},{"id":"https://openalex.org/keywords/normal-approximation","display_name":"Gaussian approximation","score":0.6200000047683716},{"id":"https://openalex.org/keywords/hermite-polynomial-expansion","display_name":"Hermite polynomial expansion","score":0.9869999885559082},{"id":"https://openalex.org/keywords/queue-length-distribution","display_name":"queue length distribution","score":0.7279999852180481},{"id":"https://openalex.org/keywords/call-centers","display_name":"call centers","score":0.656000018119812},{"id":"https://openalex.org/keywords/health-centers","display_name":"health centers","score":0.35199999809265137},{"id":"https://openalex.org/keywords/time-varying-arrival-rates","display_name":"time-varying arrival rates","score":0.7099999785423279},{"id":"https://openalex.org/keywords/cumulant-moments","display_name":"cumulant moments","score":0.4580000042915344},{"id":"https://openalex.org/keywords/strong-law-of-large-numbers","display_name":"strong law of large numbers","score":0.6449999809265137}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5771455764770508},{"id":"https://openalex.org/C160403385","wikidata":"https://www.wikidata.org/wiki/Q220543","display_name":"Queue","level":2,"score":0.5522657036781311},{"id":"https://openalex.org/C22684755","wikidata":"https://www.wikidata.org/wiki/Q847526","display_name":"Queueing theory","level":2,"score":0.5050960183143616},{"id":"https://openalex.org/C100906024","wikidata":"https://www.wikidata.org/wiki/Q205692","display_name":"Poisson distribution","level":2,"score":0.46908774971961975},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.4604080617427826},{"id":"https://openalex.org/C121864883","wikidata":"https://www.wikidata.org/wiki/Q677916","display_name":"Statistical physics","level":1,"score":0.3483896255493164},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.33749860525131226},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.32779502868652344},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.287935733795166},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.20257192850112915},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.1929856240749359},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.17677190899848938}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2034832.2034858","doi":"https://doi.org/10.1145/2034832.2034858","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2034832.2034858","pdf_url":null,"source":{"id":"https://openalex.org/S4210187660","display_name":"ACM SIGMETRICS Performance Evaluation Review","issn_l":"0163-5999","issn":["0163-5999","1557-9484"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-scientific","cwts-core","norway-1","poland-70","russia-white-list-3"],"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM SIGMETRICS Performance Evaluation Review","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"sustainable_development_goals_aurora":[{"id":"https://metadata.un.org/sdg/16","score":0.44999998807907104,"display_name":"Peace, justice, and strong institutions"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":1,"referenced_works":["https://openalex.org/W2144005446"],"related_works":["https://openalex.org/W2023263624","https://openalex.org/W2009254888","https://openalex.org/W2144005446","https://openalex.org/W2199820417","https://openalex.org/W2950325549","https://openalex.org/W7099990430","https://openalex.org/W1551712340","https://openalex.org/W2794780833","https://openalex.org/W1987592119","https://openalex.org/W2293280222"],"abstract_inverted_index":{"Large":[0],"scale":[1],"systems":[2,99,124,311],"such":[3],"as":[4,12,14,133,135,237,266],"customer":[5,20,28,40,57,138],"contact":[6],"centers,":[7,11,16],"like":[8,17],"telephone":[9],"call":[10,172],"well":[13,134,267],"healthcare":[15],"hospitals,":[18],"have":[19,32,68],"inflow-outflow":[21],"dynamics":[22],"with":[23,116,129,208],"many":[24,66],"common":[25],"features.":[26],"The":[27,164,176,331],"arrival":[29,352],"patterns":[30],"may":[31,80,94],"time":[33,347,384,448,510],"of":[34,55,157,201,213,228,296,321,374,418,498,530],"day":[35],"or":[36,420],"seasonal":[37],"effects.":[38],"Moreover,":[39,90,518],"population":[41],"sizes":[42],"tend":[43,262],"to":[44,70,96,152,198,253,264,340,422,471,475],"be":[45,81],"large":[46,122,158],"where":[47,449,484],"the":[48,85,98,191,199,204,209,214,254,269,287,293,314,322,372,382,392,396,403,407,416,424,437,450,466,472,476,485,489,494,499,502,506,512,516],"individual":[49],"actions":[50,58],"are":[51,61,88,142,224],"intrinsic":[52],"and":[53,59,137,160,211,242,317,371,511],"independent":[54],"other":[56,477],"there":[60],"multiple":[62],"service":[63,79,108,123,136,235,362],"agents,":[64],"so":[65,524],"customers":[67,76,93],"access":[69],"services":[71],"in":[72,78,106,239,337,388,406,440],"parallel.":[73],"Finally,":[74,203],"arriving":[75],"engaging":[77],"delayed":[82],"if":[83,100],"all":[84],"available":[86],"agents":[87],"busy.":[89],"these":[91,149,247,260,277],"waiting":[92],"decide":[95],"leave":[97],"they":[101],"feel":[102],"that":[103,141,170,185,284,312,334,443,461],"their":[104],"delay":[105],"receiving":[107],"is":[109,125,186,217,272,285,292,376,401,431,436,445,493],"excessively":[110],"long.":[111],"A":[112],"fundamental":[113],"Markov":[114],"process,":[115],"dynamic":[117],"rates,":[118],"queueing":[119,323,408,533],"model":[120,184,193,206,216,504,514],"for":[121,148,233,302,325,395,505,515],"a":[126,167,173,181,219,225,229,281,297,303,326,346,361,447,453,527],"multiserver":[127],"queue":[128,256,397,434],"non-homogeneous":[130],"Poisson":[131],"arrivals":[132],"abandonment":[139,367],"times":[140],"exponentially":[143],"distributed.":[144],"An":[145],"asymptotic":[146,231],"scaling":[147],"queues":[150],"leads":[151],"both":[153,532],"functional":[154],"strong":[155],"law":[156],"numbers":[159],"central":[161],"limit":[162,179],"theorems.":[163],"first":[165],"yields":[166,180,520],"dynamical":[168,220,310],"system":[169,409],"we":[171,335],"fluid":[174,192,205,503],"model.":[175],"second":[177],"scaled":[178],"diffusion":[182,513],"process":[183,324],"Gaussian":[187,215,251,304,439,479,539],"under":[188],"conditions":[189],"involving":[190],"not":[194,263],"lingering":[195,270],"too":[196],"closely":[197],"number":[200,373,405,417,425],"servers.":[202],"coupled":[207],"mean":[210,404,507],"covariance":[212],"also":[218,446,459,492],"system.":[221],"These":[222],"results":[223,248],"special":[226,294],"case":[227,295],"general":[230,298],"theory":[232],"Markovian":[234],"networks":[236],"derived":[238],"Mandelbaum,":[240],"Massey,":[241],"Reiman":[243],"[1].":[244],"In":[245],"practice,":[246],"yield":[249],"useful":[250],"approximations":[252,480],"transient":[255],"length":[257,398,435],"distribution.":[258],"However,":[259],"estimates":[261],"work":[265],"when":[268,402,432],"effect":[271],"significant.":[273],"We":[274,307,380],"can":[275],"improve":[276],"methods":[278],"by":[279],"introducing":[280],"new":[282],"technique":[283],"called":[286],"Gaussian-skewness":[288],"approximation":[289,343],"(GSA).":[290],"It":[291],"Hermite":[299],"polynomial":[300],"expansion":[301],"random":[305],"variable.":[306],"then":[308],"obtain":[309],"approximate":[313],"mean,":[315],"variance":[316],"higher":[318],"cumulant":[319],"moments":[320],"more":[327,470],"accurate,":[328],"non-Gaussian":[329],"estimation.":[330],"numerical":[332],"example":[333],"consider":[336],"this":[338,428,444,509],"paper,":[339],"illustrate":[341],"our":[342,433],"methods,":[344],"has":[345,410],"interval":[348],"(0,":[349],"20],":[350],"an":[351,521],"rate":[353,363,368],"function":[354],"\u03bb(t)":[355],"=":[356,365,369,378,386],"20":[357],"+":[358],"10":[359],"sin(t),":[360],"?":[364],"1.0,":[366],"0.5,":[370],"servers":[375],"c":[377],"20.":[379],"highlight":[381],"specific":[383],"t":[385],"4.25":[387],"Figure":[389,457],"1":[390,458],"since":[391],"simulated":[393],"histogram":[394],"distribution":[399,469],"here":[400,536],"gone":[411],"from":[412],"being":[413],"greater":[414],"than":[415,537],"servers,":[419],"overloaded,":[421],"equaling":[423],"exactly":[426],"at":[427,488,508],"time.":[429],"This":[430],"least":[438],"appearance.":[441],"Note":[442],"skewness":[451],"attains":[452],"locally":[454],"maximal":[455],"value.":[456],"illustrates":[460],"GSA":[462,519],"(solid":[463],"curve)":[464],"skews":[465],"its":[467],"density":[468,523],"left":[473,497],"compared":[474],"two":[478],"(both":[481],"dotted":[482],"lines":[483],"smaller":[486],"one":[487,496],"peak,":[490,500],"which":[491],"largest":[495],"uses":[501],"variance).":[517],"asymmetric":[522],"it":[525],"does":[526],"better":[528],"job":[529],"fitting":[531],"distributional":[534],"tails":[535],"any":[538],"method.":[540]},"counts_by_year":[{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":4},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":5}],"updated_date":"2026-09-25T08:18:29.962427","created_date":"2016-06-24T00:00:00"}