{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,23]],"date-time":"2026-03-23T09:21:30Z","timestamp":1774257690216,"version":"3.50.1"},"reference-count":57,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"3","license":[{"start":{"date-parts":[[2020,3,1]],"date-time":"2020-03-01T00:00:00Z","timestamp":1583020800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2020,3,1]],"date-time":"2020-03-01T00:00:00Z","timestamp":1583020800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,3,1]],"date-time":"2020-03-01T00:00:00Z","timestamp":1583020800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61950410603"],"award-info":[{"award-number":["61950410603"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Singapore NRF National Satellite of Excellence, Design Science and Technology for Secure Critical Infra-Structure NSoE","award":["DeST-SCI2019-0007"],"award-info":[{"award-number":["DeST-SCI2019-0007"]}]},{"name":"A*STAR-NTU-SUTD Joint Research Grant Call on Artificial Intelligence for the Future of Manufacturing RGANS 1906","award":["WASP\/NTU M4082187 (4080)"],"award-info":[{"award-number":["WASP\/NTU M4082187 (4080)"]}]},{"DOI":"10.13039\/501100001459","name":"Ministry of Education - Singapore","doi-asserted-by":"publisher","award":["2017-T1-002-007 RG122\/17"],"award-info":[{"award-number":["2017-T1-002-007 RG122\/17"]}],"id":[{"id":"10.13039\/501100001459","id-type":"DOI","asserted-by":"publisher"}]},{"name":"MOE Tier 2","award":["MOE2014-T2-2-015 ARC4\/15"],"award-info":[{"award-number":["MOE2014-T2-2-015 ARC4\/15"]}]},{"name":"Singapore NRF","award":["2015-NRF-ISF001-2277"],"award-info":[{"award-number":["2015-NRF-ISF001-2277"]}]},{"name":"Singapore EMA Energy Resilience","award":["NRF2017 EWT-EP003-041"],"award-info":[{"award-number":["NRF2017 EWT-EP003-041"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Internet Things J."],"published-print":{"date-parts":[[2020,3]]},"DOI":"10.1109\/jiot.2019.2961958","type":"journal-article","created":{"date-parts":[[2019,12,25]],"date-time":"2019-12-25T01:57:50Z","timestamp":1577239070000},"page":"1974-1993","source":"Crossref","is-referenced-by-count":120,"title":["Distributed Dynamic Resource Management and Pricing in the IoT Systems With Blockchain-as-a-Service and UAV-Enabled Mobile Edge Computing"],"prefix":"10.1109","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4430-5928","authenticated-orcid":false,"given":"Alia","family":"Asheralieva","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7442-7416","authenticated-orcid":false,"given":"Dusit","family":"Niyato","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/COMST.2019.2926625"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.1998.712192"},{"key":"ref33","author":"osborne","year":"1994","journal-title":"A Course in Game Theory"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TWC.2017.2705039"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TWC.2018.2815628"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1145\/2479942.2479946"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1145\/1143844.1143932"},{"key":"ref36","doi-asserted-by":"crossref","first-page":"359","DOI":"10.1561\/2200000049","article-title":"Bayesian reinforcement learning: A survey","volume":"8","author":"ghavamzadeh","year":"2016","journal-title":"Found Trends Mach Learn"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1137\/S0363012902407107"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1007\/978-94-010-0189-2_25"},{"key":"ref28","author":"nakamoto","year":"2008","journal-title":"Bitcoin A Peer-to-Peer Electronic Cash System"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TVT.2018.2866365"},{"key":"ref29","article-title":"PolyShard: Coded sharding achieves linearly scaling efficiency and security simultaneously","author":"li","year":"2018","journal-title":"arXiv preprint arXiv 1809 10361"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2019.2948144"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2019.2921217"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/WTS.2017.7943523"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2018.2871706"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2017.2740569"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/ICC.2018.8422632"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/MCOM.2018.1701095"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/TWC.2018.2885266"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/ICC.2018.8422743"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2014.09.003"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1561\/2000000039"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1109\/JSAC.2018.2844979"},{"key":"ref56","article-title":"Train faster, generalize better: Stability of stochastic gradient descent","author":"hardt","year":"2015","journal-title":"arXiv preprint arXiv 1509 01240"},{"key":"ref55","first-page":"1064","article-title":"The asymptotic convergence-rate of Q-learning","author":"szepesv\u00e1ri","year":"1998","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref54","article-title":"Essays in revealed preference theory and behavioral economics","author":"imai","year":"2016"},{"key":"ref53","year":"2016"},{"key":"ref52","year":"2019","journal-title":"OPNET simulation and development tool"},{"key":"ref10","year":"2019","journal-title":"Amazon Blockchain"},{"key":"ref11","year":"2019","journal-title":"Ali-Baba Cloud BaaS"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2018.2871020"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2018.2875544"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/COMST.2019.2894727"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TETCI.2019.2892733"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2019.2923702"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TVT.2019.2934027"},{"key":"ref17","article-title":"A tutorial on UAVs for wireless networks: Applications, challenges, and open problems","author":"mozaffari","year":"2018","journal-title":"arXiv preprint arXiv 1803 00680"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/ICUFN.2017.7993751"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ICC.2018.8422547"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2017.2779263"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2018.2879679"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2017.2709784"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2896108"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/MCOM.2017.1700117"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TVT.2019.2894944"},{"key":"ref49","first-page":"2829","article-title":"Continuous deep q-learning with model-based acceleration","author":"gu","year":"2011","journal-title":"Proc ACM ICML"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2019.2918296"},{"key":"ref46","article-title":"Zoneout: Regularizing RNNs by randomly preserving hidden activations","author":"krueger","year":"2016","journal-title":"arXiv preprint arXiv 1606 01305"},{"key":"ref45","first-page":"1929","article-title":"Dropout: A simple way to prevent neural networks from overfitting","volume":"15","author":"srivastava","year":"2014","journal-title":"J Mach Learn Res"},{"key":"ref48","first-page":"3223","article-title":"Deep Q-learning from demonstrations","author":"hester","year":"2018","journal-title":"Proc AAAI Conf Artif Intell"},{"key":"ref47","first-page":"646","article-title":"Deep networks with stochastic depth","author":"huang","year":"2016","journal-title":"Proc Eur Conf Comput Vis"},{"key":"ref42","article-title":"Learning and policy search in stochastic dynamical systems with Bayesian neural networks","author":"depeweg","year":"2016","journal-title":"arXiv preprint arXiv 1605 09090"},{"key":"ref41","article-title":"Uncertainty in deep learning","author":"gal","year":"2016"},{"key":"ref44","first-page":"1303","article-title":"Stochastic variational inference","volume":"14","author":"hofman","year":"2013","journal-title":"J Mach Learn Res"},{"key":"ref43","first-page":"5574","article-title":"What uncertainties do we need in Bayesian deep learning for computer vision?","author":"kendall","year":"2017","journal-title":"Proc Adv Neural Inf Process Syst"}],"container-title":["IEEE Internet of Things Journal"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6488907\/9034528\/08941139.pdf?arnumber=8941139","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,4,27]],"date-time":"2022-04-27T17:26:07Z","timestamp":1651080367000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8941139\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,3]]},"references-count":57,"journal-issue":{"issue":"3"},"URL":"https:\/\/doi.org\/10.1109\/jiot.2019.2961958","relation":{},"ISSN":["2327-4662","2372-2541"],"issn-type":[{"value":"2327-4662","type":"electronic"},{"value":"2372-2541","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,3]]}}}