{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,29]],"date-time":"2026-01-29T23:30:48Z","timestamp":1769729448032,"version":"3.49.0"},"reference-count":35,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2021,5,15]],"date-time":"2021-05-15T00:00:00Z","timestamp":1621036800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,5,15]],"date-time":"2021-05-15T00:00:00Z","timestamp":1621036800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/100000185","name":"Defense Advanced Research Projects Agency","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000185","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Computing"],"published-print":{"date-parts":[[2022,3]]},"DOI":"10.1007\/s00607-021-00953-7","type":"journal-article","created":{"date-parts":[[2021,5,15]],"date-time":"2021-05-15T03:14:22Z","timestamp":1621048462000},"page":"461-479","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Cloud-backed mobile cognition"],"prefix":"10.1007","volume":"104","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6521-7137","authenticated-orcid":false,"given":"Augusto","family":"Vega","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alper","family":"Buyuktosunoglu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Davide","family":"Callegaro","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marco","family":"Levorato","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pradip","family":"Bose","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,5,15]]},"reference":[{"key":"953_CR1","first-page":"1","volume":"2020","author":"D Callegaro","year":"2020","unstructured":"Callegaro D et al (2020) Dynamic distributed computing for infrastructure-assisted autonomous UAVs. ICC 2020:1\u20136","journal-title":"ICC"},{"key":"953_CR2","first-page":"1","volume":"2018","author":"D Callegaro","year":"2018","unstructured":"Callegaro D, Levorato M (2018) Optimal computation offloading in edge-assisted UAV systems. GLOBECOM 2018:1\u20136","journal-title":"GLOBECOM"},{"key":"953_CR3","doi-asserted-by":"publisher","first-page":"1655","DOI":"10.1109\/JPROC.2019.2921977","volume":"107","author":"J Chen","year":"2019","unstructured":"Chen J, Ran X (2019) Deep learning with edge computing: A review. Proc IEEE 107:1655\u20131674","journal-title":"Proc IEEE"},{"key":"953_CR4","doi-asserted-by":"publisher","first-page":"105","DOI":"10.1145\/2996864","volume":"59","author":"Y Chen","year":"2016","unstructured":"Chen Y et al (2016) DianNao family: Energy-efficient hardware accelerators for machine learning. Commun ACM 59:105\u2013112","journal-title":"Commun ACM"},{"key":"953_CR5","unstructured":"Cheng Y et\u00a0al (2017) A survey of model compression and acceleration for deep neural networks. arXiv:1710.09282"},{"key":"953_CR6","unstructured":"Dolcourt J (2019) We Ran 5G Speed Tests on Verizon, AT&T, EE and More: Here\u2019s What We Found. https:\/\/www.cnet.com\/features\/we-ran-5g-speed-tests-on-verizon-at-t-ee-and-more-heres-what-we-found\/"},{"key":"953_CR7","doi-asserted-by":"publisher","first-page":"92","DOI":"10.1145\/2749469.2750389","volume":"2015","author":"Z Du","year":"2015","unstructured":"Du Z et al (2015) ShiDianNao: Shifting vision processing closer to the sensor. ISCA 2015:92\u2013104","journal-title":"ISCA"},{"key":"953_CR8","unstructured":"Eliot L (2017) In-car voice commands NLP for self-driving cars. https:\/\/www.aitrends.com\/ai-insider\/car-voice-commands-nlp-self-driving-cars"},{"key":"953_CR9","first-page":"111","volume":"2018","author":"AE Eshratifar","year":"2018","unstructured":"Eshratifar AE, Pedram M (2018) Energy and performance efficient computation offloading for deep neural networks in a mobile cloud computing environment. GLSVLSI 2018:111\u2013116","journal-title":"GLSVLSI"},{"key":"953_CR10","unstructured":"Google LLC (2020) Edge TPU. https:\/\/cloud.google.com\/edge-tpu\/"},{"key":"953_CR11","unstructured":"Han S et\u00a0al (2015) Deep compression: Compressing deep neural networks with pruning, trained quantization and Huffman coding. arXiv:1510.00149"},{"key":"953_CR12","unstructured":"Howard A et\u00a0al (2017) MobileNets: Efficient convolutional neural networks for mobile vision applications. arXiv:1704.04861"},{"key":"953_CR13","unstructured":"Iandola F et\u00a0al (2016) SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and $$<$$0.5MB model size. arXiv:1602.07360"},{"key":"953_CR14","first-page":"615","volume":"2017","author":"Y Kang","year":"2017","unstructured":"Kang Y et al (2017) Neurosurgeon: Collaborative intelligence between the cloud and mobile edge. ASPLOS 2017:615\u2013629","journal-title":"ASPLOS"},{"key":"953_CR15","unstructured":"Kone\u010dn\u00fd J et\u00a0al (2016) Federated learning: Strategies for improving communication efficiency. arXiv:1610.05492"},{"key":"953_CR16","doi-asserted-by":"publisher","first-page":"117","DOI":"10.1145\/2699343.2699349","volume":"2015","author":"ND Lane","year":"2015","unstructured":"Lane ND, Georgiev P (2015) Can deep learning revolutionize mobile sensing? HotMobile 2015:117\u2013122","journal-title":"HotMobile"},{"key":"953_CR17","doi-asserted-by":"publisher","first-page":"2278","DOI":"10.1109\/5.726791","volume":"86\u201311","author":"Y LeCun","year":"1998","unstructured":"LeCun Y et al (1998) Gradient-based learning applied to document recognition. Proc IEEE 86\u201311:2278\u20132324","journal-title":"Proc IEEE"},{"key":"953_CR18","first-page":"1","volume":"2017","author":"S Li","year":"2017","unstructured":"Li S et al (2017) FitCNN: A cloud-assisted lightweight convolutional neural network framework for mobile devices. RTCSA 2017:1\u20136","journal-title":"RTCSA"},{"key":"953_CR19","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1109\/MC.2017.3001256","volume":"50","author":"S Liu","year":"2017","unstructured":"Liu S et al (2017) Computer architectures for autonomous driving. IEEE Comput 50:18\u201325","journal-title":"IEEE Comput"},{"key":"953_CR20","first-page":"142","volume":"2011","author":"A Maas","year":"2011","unstructured":"Maas A et al (2011) Learning word vectors for sentiment analysis. ACL HLT 2011:142\u2013150","journal-title":"ACL HLT"},{"key":"953_CR21","unstructured":"McMahan H et\u00a0al (2016) Communication-efficient learning of deep networks from decentralized data. arXiv:1602.05629"},{"key":"953_CR22","first-page":"151","volume":"2016","author":"S Memeti","year":"2016","unstructured":"Memeti S, Pllana S (2016) Combinatorial optimization of work distribution on heterogeneous systems. ICPPW 2016:151\u2013160","journal-title":"ICPPW"},{"key":"953_CR23","unstructured":"Newman D (2019) How AI is making sentiment analysis easy. https:\/\/www.forbes.com\/sites\/danielnewman\/2019\/11\/22\/how-ai-is-making-sentiment-analysis-easy"},{"key":"953_CR24","doi-asserted-by":"publisher","first-page":"7","DOI":"10.1145\/3372394.3372400","volume":"2019","author":"H Ouarnoughi","year":"2019","unstructured":"Ouarnoughi H et al (2019) Hierarchical platform for autonomous driving. INTESA 2019:7\u201312","journal-title":"INTESA"},{"key":"953_CR25","first-page":"1","volume":"2018","author":"C Pakha","year":"2018","unstructured":"Pakha C et al (2018) Reinventing video streaming for distributed vision analytics. HotCloud 2018:1","journal-title":"HotCloud"},{"key":"953_CR26","first-page":"6517","volume":"2017","author":"J Redmon","year":"2017","unstructured":"Redmon J, Farhadi A (2017) YOLO9000: Better, faster, stronger. CVPR 2017:6517\u20136525","journal-title":"CVPR"},{"key":"953_CR27","first-page":"15","volume-title":"The ns-3 network simulator","author":"G Riley","year":"2010","unstructured":"Riley G, Henderson T (2010) The ns-3 network simulator. Springer, Berlin Heidelberg, pp 15\u201334"},{"key":"953_CR28","first-page":"4510","volume":"2018","author":"M Sandler","year":"2018","unstructured":"Sandler M et al (2018) MobileNetV2: Inverted residuals and linear bottlenecks. CVPR 2018:4510\u20134520","journal-title":"CVPR"},{"key":"953_CR29","first-page":"167","volume":"2014","author":"K Sun","year":"2014","unstructured":"Sun K et al (2014) M2C: Energy efficient mobile cloud system for deep learning. INFOCOM 2014:167\u2013168","journal-title":"INFOCOM"},{"key":"953_CR30","doi-asserted-by":"publisher","first-page":"2295","DOI":"10.1109\/JPROC.2017.2761740","volume":"105","author":"V Sze","year":"2017","unstructured":"Sze V et al (2017) Efficient processing of deep neural networks: A tutorial and survey. Proc IEEE 105:2295\u20132329","journal-title":"Proc IEEE"},{"key":"953_CR31","unstructured":"The Wall Street Journal (2020) Alexa has a new skill: Asking when it doesn\u2019t know. https:\/\/www.wsj.com\/articles\/alexa-has-a-new-skill-asking-when-it-doesnt-know-11607732175?reflink=desktopwebshare_permalink"},{"key":"953_CR32","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1109\/MSSC.2017.2745818","volume":"9","author":"M Verhelst","year":"2017","unstructured":"Verhelst M, Moons B (2017) Embedded deep neural network processing: Algorithmic and processor techniques bring deep learning to IoT and edge devices. IEEE Solid-State Circuits Mag 9:55\u201365","journal-title":"IEEE Solid-State Circuits Mag"},{"key":"953_CR33","unstructured":"Weston J et\u00a0al (2015) Towards AI-complete question answering: A set of prerequisite toy tasks. arXiv:1502.05698"},{"key":"953_CR34","doi-asserted-by":"publisher","first-page":"1181","DOI":"10.1145\/3397271.3401160","volume":"2020","author":"H Zamani","year":"2020","unstructured":"Zamani H et al (2020) Analyzing and learning from user interactions for search clarification. SIGIR 2020:1181\u20131190","journal-title":"SIGIR"},{"key":"953_CR35","doi-asserted-by":"crossref","unstructured":"Zhang C et\u00a0al (2019) Deep learning in mobile and wireless networking: A survey. IEEE Commun Surv Tutorials 21:2224\u20132287","DOI":"10.1109\/COMST.2019.2904897"}],"container-title":["Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00607-021-00953-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00607-021-00953-7\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00607-021-00953-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,3,30]],"date-time":"2022-03-30T18:13:17Z","timestamp":1648663997000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00607-021-00953-7"}},"subtitle":["Power-efficient deep learning in the autonomous vehicle era"],"short-title":[],"issued":{"date-parts":[[2021,5,15]]},"references-count":35,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2022,3]]}},"alternative-id":["953"],"URL":"https:\/\/doi.org\/10.1007\/s00607-021-00953-7","relation":{},"ISSN":["0010-485X","1436-5057"],"issn-type":[{"value":"0010-485X","type":"print"},{"value":"1436-5057","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,5,15]]},"assertion":[{"value":"1 December 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 April 2021","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"15 May 2021","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}