{"id":"https://openalex.org/W2897596343","doi":"https://doi.org/10.1109/percomw.2018.8480168","title":"Implementing Deep Learning and Inferencing on Fog and Edge Computing Systems","display_name":"Implementing Deep Learning and Inferencing on Fog and Edge Computing Systems","publication_year":2018,"publication_date":"2018-03-01","ids":{"openalex":"https://openalex.org/W2897596343","doi":"https://doi.org/10.1109/percomw.2018.8480168","mag":"2897596343"},"language":"en","primary_location":{"id":"doi:10.1109/percomw.2018.8480168","is_oa":false,"landing_page_url":"https://doi.org/10.1109/percomw.2018.8480168","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5025308099","display_name":"S. Dey","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Swarnava Dey","raw_affiliation_strings":["Embedded Systems and Robotics, TCS Research & Innovation, Kolkata, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Embedded Systems and Robotics, TCS Research & Innovation, Kolkata, India","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5031139197","display_name":"Arijit Mukherjee","orcid":"https://orcid.org/0000-0001-5052-4476"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Arijit Mukherjee","raw_affiliation_strings":["Embedded Systems and Robotics, TCS Research & Innovation, Kolkata, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Embedded Systems and Robotics, TCS Research & Innovation, Kolkata, India","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.7142,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.9145263,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"818","last_page":"823"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10273","display_name":"IoT and Edge/Fog Computing","score":0.9998999834060669,"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/T10273","display_name":"IoT and Edge/Fog Computing","score":0.9998999834060669,"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/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9977999925613403,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T12079","display_name":"IoT Networks and Protocols","score":0.9945999979972839,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8179129362106323},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.7846826314926147},{"id":"https://openalex.org/keywords/edge-computing","display_name":"Edge computing","score":0.7356130480766296},{"id":"https://openalex.org/keywords/edge-device","display_name":"Edge device","score":0.7093756794929504},{"id":"https://openalex.org/keywords/provisioning","display_name":"Provisioning","score":0.6783196330070496},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6372969150543213},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.5735419392585754},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5156711339950562},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49175742268562317},{"id":"https://openalex.org/keywords/analytics","display_name":"Analytics","score":0.4608805179595947},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.41420841217041016},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.41227710247039795},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3330293893814087},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.32578781247138977},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.3054490387439728},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.2365911602973938},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.15073275566101074},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.13964951038360596},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.131809800863266}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8179129362106323},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.7846826314926147},{"id":"https://openalex.org/C2778456923","wikidata":"https://www.wikidata.org/wiki/Q5337692","display_name":"Edge computing","level":3,"score":0.7356130480766296},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.7093756794929504},{"id":"https://openalex.org/C172191483","wikidata":"https://www.wikidata.org/wiki/Q1071806","display_name":"Provisioning","level":2,"score":0.6783196330070496},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6372969150543213},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.5735419392585754},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5156711339950562},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49175742268562317},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.4608805179595947},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.41420841217041016},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.41227710247039795},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3330293893814087},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.32578781247138977},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3054490387439728},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.2365911602973938},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.15073275566101074},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.13964951038360596},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.131809800863266}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/percomw.2018.8480168","is_oa":false,"landing_page_url":"https://doi.org/10.1109/percomw.2018.8480168","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Decent work and economic growth","score":0.49000000953674316,"id":"https://metadata.un.org/sdg/8"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1978796422","https://openalex.org/W1991539813","https://openalex.org/W2053882326","https://openalex.org/W2061179798","https://openalex.org/W2062118960","https://openalex.org/W2072128103","https://openalex.org/W2114623221","https://openalex.org/W2122974233","https://openalex.org/W2135099885","https://openalex.org/W2136922672","https://openalex.org/W2271840356","https://openalex.org/W2337546824","https://openalex.org/W2568772110","https://openalex.org/W2725283788","https://openalex.org/W2765234087","https://openalex.org/W2919115771","https://openalex.org/W2962883027","https://openalex.org/W3120740533","https://openalex.org/W6663893076","https://openalex.org/W6665894696","https://openalex.org/W6929462729"],"related_works":["https://openalex.org/W4322761281","https://openalex.org/W4238233472","https://openalex.org/W4313463218","https://openalex.org/W4312996489","https://openalex.org/W3111395152","https://openalex.org/W4313526662","https://openalex.org/W3106131444","https://openalex.org/W3216099748","https://openalex.org/W4205963435","https://openalex.org/W4319161913"],"abstract_inverted_index":{"The":[0],"case":[1],"for":[2,44,87,152,183],"leveraging":[3],"the":[4,11,41,67,120,123,146,163],"computing":[5,33],"resources":[6],"of":[7,13,61,73,105,125,136,148,162,168,202],"smart":[8],"devices":[9,190],"at":[10,34],"edge":[12,189],"network":[14,35],"was":[15],"conceptualized":[16],"almost":[17],"nine":[18],"years":[19],"back.":[20],"Since":[21],"then":[22],"several":[23],"concepts":[24],"like":[25],"Cloudlets,":[26],"Fog":[27,126,139],"etc.":[28,65],"were":[29],"instrumental":[30],"in":[31,37,57,100,128,138,187],"realizing":[32],"edge,":[36],"physical":[38],"proximity":[39],"to":[40,69,93,96],"data":[42,74,90],"sources":[43],"building":[45],"more":[46],"responsive,":[47],"scalable":[48],"and":[49,115,145,160,165],"available":[50],"Cloud":[51,110,113],"based":[52,109,171,191],"services.":[53],"An":[54],"essential":[55],"component":[56],"smartphone":[58],"applications,":[59],"Internet":[60],"Things(IoT),":[62],"field":[63],"robotics":[64],"is":[66,80,132,143,155,178],"ability":[68,95],"analyze":[70],"large":[71],"amount":[72],"with":[75,181,194],"reasonable":[76],"latency.":[77,118],"Deep":[78,107,172,204],"Learning":[79,108,173],"fast":[81],"becoming":[82],"a":[83,203],"de":[84],"facto":[85],"choice":[86],"performing":[88],"this":[89],"analytics":[91],"owing":[92],"its":[94],"reduce":[97],"human":[98],"interventions":[99],"such":[101],"workflows.":[102],"Major":[103],"deterrent":[104],"providing":[106],"services":[111],"are":[112],"outages":[114],"relatively":[116],"high":[117],"In":[119],"current":[121,134],"article":[122],"role":[124],"Computing":[127,142],"addressing":[129],"these":[130],"issues":[131],"discussed,":[133],"state":[135],"standardization":[137],"/":[140],"Edge":[141,170],"reviewed":[144],"importance":[147],"optimum":[149,184],"resource":[150,185,196],"provisioning":[151,186],"running":[153],"Edge-Analytics":[154],"highlighted.":[156],"A":[157],"detailed":[158],"design":[159],"evaluation":[161],"distribution":[164],"parallelization":[166],"aspects":[167],"an":[169],"framework":[174],"using":[175],"off-the-shelf":[176],"components":[177],"presented":[179],"along":[180],"strategies":[182],"constrained":[188],"on":[192],"experiments":[193],"system":[195],"(CPU,":[197],"GPU":[198],"&":[199],"RAM)":[200],"consumptions":[201],"Convolutional":[205],"Neural":[206],"Network.":[207]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":4}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
