iBet uBet web content aggregator. Adding the entire web to your favor.
iBet uBet web content aggregator. Adding the entire web to your favor.



Link to original content: https://api.crossref.org/works/10.1109/ACCESS.2021.3058021
{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,10]],"date-time":"2024-09-10T10:32:14Z","timestamp":1725964334185},"reference-count":52,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"DOI":"10.13039\/501100004271","name":"Sapienza Universit di Roma","doi-asserted-by":"publisher","award":["MA21816436AA4280","RM11816426B7A216","RM11916B323CE30C","RM12017294171495"],"id":[{"id":"10.13039\/501100004271","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2021]]},"DOI":"10.1109\/access.2021.3058021","type":"journal-article","created":{"date-parts":[[2021,2,9]],"date-time":"2021-02-09T07:23:42Z","timestamp":1612855422000},"page":"25716-25757","source":"Crossref","is-referenced-by-count":30,"title":["Learning-in-the-Fog (LiFo): Deep Learning Meets Fog Computing for the Minimum-Energy Distributed Early-Exit of Inference in Delay-Critical IoT Realms"],"prefix":"10.1109","volume":"9","author":[{"ORCID":"http:\/\/orcid.org\/0000-0002-9791-7901","authenticated-orcid":false,"given":"Enzo","family":"Baccarelli","sequence":"first","affiliation":[]},{"ORCID":"http:\/\/orcid.org\/0000-0002-3164-6256","authenticated-orcid":false,"given":"Michele","family":"Scarpiniti","sequence":"additional","affiliation":[]},{"ORCID":"http:\/\/orcid.org\/0000-0002-5682-4186","authenticated-orcid":false,"given":"Alireza","family":"Momenzadeh","sequence":"additional","affiliation":[]},{"ORCID":"http:\/\/orcid.org\/0000-0001-8379-8799","authenticated-orcid":false,"given":"Sima Sarv","family":"Ahrabi","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1002\/0470022515.ch14"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1145\/1807128.1807136"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2913564"},{"key":"ref32","first-page":"1","article-title":"Quantized neural networks: Training neural networks with low precision weights and activations","volume":"18","author":"hubara","year":"2018","journal-title":"J Mach Learn Res"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/72.761724"},{"key":"ref30","author":"goodfellow","year":"2016","journal-title":"Deep Learning"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2016.06.019"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1145\/2208828.2208840"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/JSAC.2015.2478718"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1016\/j.comcom.2016.12.010"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.3390\/computation6040062"},{"key":"ref27","first-page":"1","article-title":"ECO: Harmonizing edge and cloud with ML\/DL orchestration","author":"talagala","year":"2018","journal-title":"Proc USENIX Workshop Hot Topics Edge Comput (HotEdge)"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/MNET.001.1900019"},{"key":"ref2","year":"2020","journal-title":"Cisco Global Cloud Index Forecast and Methodology"},{"key":"ref1","year":"2020","journal-title":"Fog Computing and the Internet of Things Extend the Cloud to Where the Things Are"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2019.2951766"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1007\/s10115-017-1029-1"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1145\/3037697.3037698"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/TCAD.2018.2858384"},{"key":"ref23","first-page":"1400","article-title":"MoDNN: Local distributed mobile computing system for deep neural network","author":"mao","year":"2017","journal-title":"Proc Design Autom Test Eur Conf Exhibition (DATE)"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1145\/3132211.3134459"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/SEC.2016.38"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/MCOM.001.1900411"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-39867-7_12"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/MNET.2018.1700031"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2017.2702013"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.sysarc.2019.02.009"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/TVT.2003.822025"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2020.02.041"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2018.2873343"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/COMST.2019.2904897"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1145\/2906388.2906396"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM.2018.8485905"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2019.2893250"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1145\/3267809.3267828"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1145\/3229556.3229562"},{"key":"ref4","first-page":"475","article-title":"Conditional deep learning for energy-efficient and enhanced pattern recognition","author":"panda","year":"2016","journal-title":"Proc Design Autom Test Eur Conf Exhibition (DATE)"},{"key":"ref3","author":"hanes","year":"2017","journal-title":"IoT Fundamentals-Networking Technologies Protocols and Use Cases for the Internet of Things"},{"key":"ref6","doi-asserted-by":"crossref","first-page":"954","DOI":"10.1007\/s12559-020-09734-4","article-title":"Why should we add early exits to neural networks?","volume":"12","author":"scardapane","year":"2020","journal-title":"Cognit Comput"},{"key":"ref5","first-page":"1","article-title":"Conditional computation in neural networks for faster models","author":"bengio","year":"2016","journal-title":"Proc Int Conf Learn Represent (ICLR)"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/ICDCS.2017.226"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/ICPR.2016.7900006"},{"key":"ref49","article-title":"Federated learning for Internet of Things: Recent advances, taxonomy, and open challenges","author":"khan","year":"2020","journal-title":"arXiv 2009 13012"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-10-5861-5_5"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2860249"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1016\/B978-0-12-813677-5.00001-8"},{"key":"ref48","first-page":"1097","article-title":"ImageNet classification with deep convolutional neural networks","author":"krizhevsky","year":"2012","journal-title":"Proc 25th Int Conf Neural Inf Process Syst (NIPS)"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.3390\/app11010377"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/49.737632"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/TVT.2007.900514"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/TNET.2014.2379698"},{"key":"ref43","author":"bazaraa","year":"2017","journal-title":"Nonlinear Programming Theory and Algorithms"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/9312710\/09350277.pdf?arnumber=9350277","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,27]],"date-time":"2022-01-27T12:14:46Z","timestamp":1643285686000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9350277\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"references-count":52,"URL":"https:\/\/doi.org\/10.1109\/access.2021.3058021","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021]]}}}