{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,18]],"date-time":"2026-04-18T00:58:22Z","timestamp":1776473902656,"version":"3.51.2"},"reference-count":50,"publisher":"Wiley","issue":"4","license":[{"start":{"date-parts":[[2021,12,3]],"date-time":"2021-12-03T00:00:00Z","timestamp":1638489600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Trans Emerging Tel Tech"],"published-print":{"date-parts":[[2022,4]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Intelligent fog cyber\u2010physical social systems (iFog CPSS) is a novel smart city project that uses intrinsic processes to automate microservices such as edge\u2010to\u2010fog or fog\u2010to\u2010cloud monitoring of complex real\u2010time activities. This article presents a dynamic cyber\u2010physical architecture that leverages iFog layers to map location\u2010based services (LBS) on a spine\u2010leaf datacenter clos topology. Individual edge clusters are connected to the edge\u2010fog layer, which communicates with iFog gateways for processing streams' requests. Use\u2010case application of artificial intelligence (AI) in vehicular ad\u2010hoc networks (VANETs) is introduced for data stream provisioning. In the validation study, a secure docker\u2010based iFog CPS experiment is carried out using traffic trace files from C++ modeller. iFog spine\u2010leaf architecture for fog\u2010computing and cloud\u2010computing are compared using two key metrics. For traffic workload utilization, the results show that 83.33% of the traffic workload is utilized at the Fog layer while 16.67% is consumed in the cloud layer. For latency profile, the results indicate that Fog and cloud streams had 20.31% and 77.69%, respectively. In terms of iFog VANET spine\u2010leaf congestion control, three distinct algorithms are studied, namely the proposed linear routing algorithm (LRA), LEACH, and collection tree protocol (CTP). In each case, the resource utilization for VANET gave 34.45%, 32.18%, and 33.37%, respectively. Latency response gave 11.76%, 82.35%, and 5.89%, respectively. Also, the throughput scenario offered 19.61%, 39.22%, and 41.17%, respectively. Consequently, the iFog scenario offers satisfactory LBS provisioning for VANETs clusters.<\/jats:p>","DOI":"10.1002\/ett.4407","type":"journal-article","created":{"date-parts":[[2021,12,3]],"date-time":"2021-12-03T11:38:08Z","timestamp":1638531488000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Cyber\u2010physical network architecture for data stream provisioning in complex ecosystems"],"prefix":"10.1002","volume":"33","author":[{"given":"Kennedy Chinedu","family":"Okafor","sequence":"first","affiliation":[{"name":"Department of Mechatronics Engineering Federal University of Technology  Owerri Nigeria"}]},{"given":"Michael Chukwudi","family":"Ndinechi","sequence":"additional","affiliation":[{"name":"Department of Electrical and Electronic Engineering Federal University of Technology  Owerri Nigeria"}]},{"given":"Sanjay","family":"Misra","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Communication Ostfold University College  Halden Norway"}]}],"member":"311","published-online":{"date-parts":[[2021,12,3]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/MWC.2019.1800356"},{"issue":"2","key":"e_1_2_10_3_1","first-page":"1","article-title":"Traffic data reconstruction based on compressive sensing with neighbor regularization","volume":"33","author":"Qin Z","year":"2020","journal-title":"Trans Emerg Telecommun Tech"},{"key":"e_1_2_10_4_1","doi-asserted-by":"publisher","DOI":"10.1002\/ett.4078"},{"issue":"18","key":"e_1_2_10_5_1","first-page":"1","article-title":"An improved top\u2010K algorithm for edge servers deployment in smart city","volume":"32","author":"Qin Z","year":"2021","journal-title":"Trans Emerg Telecommun Technol"},{"issue":"8","key":"e_1_2_10_6_1","first-page":"1","article-title":"Cooperative mobile edge computing\u2010cloud computing in internet of vehicle","volume":"32","author":"Xiaohui G","year":"2020","journal-title":"Arch Energy\u2010Efficient Workload Allocat"},{"key":"e_1_2_10_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/TETC.2013.2273457"},{"key":"e_1_2_10_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/MC.2018.3011041"},{"key":"e_1_2_10_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/LCSYS.2020.3006008"},{"key":"e_1_2_10_10_1","doi-asserted-by":"crossref","unstructured":"MahmoodA ButlerB JenningsB.Towards efficient network resource management in SDN\u2010based heterogeneous vehicular networks. Proceedings of the 2018 IEEE 42nd Annual Computer Software and Applications Conference (COMPSAC); 2018:813\u2010814; Tokyo. doi:10.1109\/COMPSAC.2018.00133","DOI":"10.1109\/COMPSAC.2018.00133"},{"key":"e_1_2_10_11_1","unstructured":"IEEE draft standard for framework of blockchain\u2010based Internet of Things (IoT) data management. P2144.1\/D2; July 2020:1\u201018."},{"issue":"2363240","key":"e_1_2_10_12_1","first-page":"1","article-title":"Leveraging fog computing for scalable IoT datacenter using spine\u2010leaf network topology","volume":"2017","author":"Okafor KC","year":"2017","journal-title":"J Electr Comput Eng"},{"key":"e_1_2_10_13_1","doi-asserted-by":"publisher","DOI":"10.1080\/1206212X.2019.1600830"},{"key":"e_1_2_10_14_1","doi-asserted-by":"crossref","unstructured":"DonassoloB FajjariI LegrandA MertikopoulosP.Demo: fog based framework for IoT service orchestration. Proceedings of the 2019 16th IEEE Annual Consumer Communications & Networking Conference (CCNC); 2019:1\u20102; Las Vegas NV. doi:10.1109\/CCNC.2019.8651852","DOI":"10.1109\/CCNC.2019.8651852"},{"key":"e_1_2_10_15_1","doi-asserted-by":"crossref","unstructured":"ShollaS NaazR ChishtiMA.Semantic smart city: context aware application architecture. Proceedings of the 2018 2nd International Conference on Electronics Communication and Aerospace Technology (ICECA); 2018:721\u2010724; Coimbatore. doi:10.1109\/ICECA.2018.8474777","DOI":"10.1109\/ICECA.2018.8474777"},{"key":"e_1_2_10_16_1","doi-asserted-by":"crossref","unstructured":"PrasetyoYA ArmanAA.Group management system design for supporting society 5.0 in smart society platform. Proceedings of the 2017 International Conference on Information Technology Systems and Innovation (ICITSI); 2017:398\u2010404; Bandung. doi:10.1109\/ICITSI.2017.8267977","DOI":"10.1109\/ICITSI.2017.8267977"},{"key":"e_1_2_10_17_1","doi-asserted-by":"crossref","unstructured":"GiyenkoA ChoYI.Intelligent UAV in smart cities using IoT. Proceedings of the 2016 16th International Conference on Control Automation and Systems (ICCAS); 2016:207\u2010210; Gyeongju doi:10.1109\/ICCAS.2016.7832322","DOI":"10.1109\/ICCAS.2016.7832322"},{"key":"e_1_2_10_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/CC.2017.7942323"},{"key":"e_1_2_10_19_1","doi-asserted-by":"crossref","unstructured":"AlexandruAM Fiasch\u00e9M PinnaC TaischM FasanottiL GrasseniP.Building a smart maintenance architecture using smart devices: a web 2.0 based approach. Proceedings of the 2016 IEEE 2nd International Forum on Research and Technologies for Society and Industry Leveraging a better tomorrow (RTSI); 2016:1\u20106; Bologna. doi:10.1109\/RTSI.2016.7740632","DOI":"10.1109\/RTSI.2016.7740632"},{"key":"e_1_2_10_20_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-99608-0_21"},{"key":"e_1_2_10_21_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-59767-6_34"},{"key":"e_1_2_10_22_1","doi-asserted-by":"publisher","DOI":"10.1109\/TETC.2015.2484839"},{"key":"e_1_2_10_23_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPDS.2012.53"},{"key":"e_1_2_10_24_1","doi-asserted-by":"crossref","unstructured":"YangC VyatkinV PangC.Service\u2010oriented extension of IEC 61850 for model\u2010driven smart grid automation design. Proceedings of the 43rd Annual Conference of the IEEE Industrial Electronics Society IECON 2017; 2017:5489\u20105496; Beijing. doi:10.1109\/IECON.2017.8216950","DOI":"10.1109\/IECON.2017.8216950"},{"key":"e_1_2_10_25_1","doi-asserted-by":"publisher","DOI":"10.1002\/9781119507314.ch8"},{"key":"e_1_2_10_26_1","doi-asserted-by":"publisher","DOI":"10.1109\/MC.2019.2934592"},{"key":"e_1_2_10_27_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jpdc.2018.07.003"},{"key":"e_1_2_10_28_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2861421"},{"key":"e_1_2_10_29_1","doi-asserted-by":"publisher","DOI":"10.1155\/2011\/596397"},{"key":"e_1_2_10_30_1","doi-asserted-by":"publisher","DOI":"10.1109\/MNET.011.1900299"},{"key":"e_1_2_10_31_1","doi-asserted-by":"crossref","unstructured":"RyashentsevaD Vogel\u2010HeuserB LuederA.Development and evaluation of a unified agents\u2010 and supervisory control theory based manufacturing control system. Proceedings of the 2018 IEEE 14th International Conference on Automation Science and Engineering (CASE); 2018:187\u2010192; Munich. doi:10.1109\/COASE.2018.8560539","DOI":"10.1109\/COASE.2018.8560539"},{"key":"e_1_2_10_32_1","doi-asserted-by":"crossref","unstructured":"MatsudaW FujimotoM AoyamaT MitsunagaT.Cyber security risk assessment on industry 4.0 using ICS testbed with AI and cloud. Proceedings of the 2019 IEEE Conference on Application Information and Network Security (AINS); 2019:54\u201059; Pulau Pinang Malaysia. doi:10.1109\/AINS47559.2019.8968698","DOI":"10.1109\/AINS47559.2019.8968698"},{"key":"e_1_2_10_33_1","doi-asserted-by":"crossref","unstructured":"WangF.AI and intelligent vehicles future challenge (IVFC) in China: from cognitive intelligence to parallel intelligence. Proceedings of the 2017 ITU Kaleidoscope: Challenges for a Data\u2010Driven Society (ITU K); 2017:1\u20102; Nanjing. . doi:10.23919\/ITU-WT.2017.8246841.","DOI":"10.23919\/ITU-WT.2017.8246841"},{"key":"e_1_2_10_34_1","doi-asserted-by":"crossref","unstructured":"AhmedHOFLS\u2010based collision avoidance cyber physical system for warehouse robots using FPGA. Proceedings of the 2019 6th International Conference on Dependable Systems and their Applications (DSA); 2020:262\u2010268; Harbin China. doi: 10.1109\/DSA.2019.00040","DOI":"10.1109\/DSA.2019.00040"},{"key":"e_1_2_10_35_1","doi-asserted-by":"crossref","unstructured":"MarrellaA MecellaM HalapuuP SardinaS.Automated process adaptation in cyber\u2010physical domains with the SmartPM system (short paper). Proceedings of the 2015 IEEE 8th International Conference on Service\u2010Oriented Computing and Applications (SOCA); 2015:59\u201064; Rome. doi:10.1109\/SOCA.2015.18","DOI":"10.1109\/SOCA.2015.18"},{"key":"e_1_2_10_36_1","doi-asserted-by":"publisher","DOI":"10.1109\/JAS.2020.1003072"},{"key":"e_1_2_10_37_1","doi-asserted-by":"crossref","unstructured":"WangB LiX FreiheitT EpureanuBI.Learning and intelligence in human\u2010cyber\u2010physical systems: framework and perspective. Proceedings of the 2020 2nd international conference on Transdisciplinary AI (TransAI); 2020:142\u2010145; Irvine CA.","DOI":"10.1109\/TransAI49837.2020.00032"},{"key":"e_1_2_10_38_1","doi-asserted-by":"crossref","unstructured":"Vogel\u2010HeuserB.Plenary lecture 1: cyber physical production systems\/industry 4.0\u2010challenges in research and industrial application. Proceedings of the 41st Annual Conference of the IEEE Industrial Electronics Society IECON 2015; 2015:11\u201013; Yokohama. doi:10.1109\/IECON.2015.7392973","DOI":"10.1109\/IECON.2015.7392973"},{"key":"e_1_2_10_39_1","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2019.2936045"},{"key":"e_1_2_10_40_1","doi-asserted-by":"crossref","unstructured":"LiuZ JinC JinW et al.Industrial AI enabled prognostics for high\u2010speed railway systems. Proceedings of the 2018 IEEE International Conference on Prognostics and Health Management (ICPHM); 2018:1\u20108; Seattle WA doi:10.1109\/ICPHM.2018.8448431","DOI":"10.1109\/ICPHM.2018.8448431"},{"key":"e_1_2_10_41_1","doi-asserted-by":"publisher","DOI":"10.1109\/TVT.2016.2563164"},{"key":"e_1_2_10_42_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.2968045"},{"key":"e_1_2_10_43_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.2973239"},{"key":"e_1_2_10_44_1","doi-asserted-by":"crossref","unstructured":"WangF ZhangJJ.Transportation 5.0 in CPSS: towards ACP\u2010based society\u2010centered intelligent transportation. Proceedings of the 2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC); 2017:762\u2010767; Yokohama. doi:10.1109\/ITSC.2017.8317905","DOI":"10.1109\/ITSC.2017.8317905"},{"key":"e_1_2_10_45_1","doi-asserted-by":"publisher","DOI":"10.1002\/9781119507314.ch1"},{"key":"e_1_2_10_46_1","doi-asserted-by":"crossref","unstructured":"LestariRD RusdinarA MurtiMA TawaqalG LeeD.Design of IoT\u2010based river water monitoring robot data transmission model using low power wide area network (LPWAN) communication technology. Proceedings of the 2019 IEEE International Conference on Internet of Things and Intelligence System (IoTaIS); 2019:201\u2010205; BALI Indonesia. doi:10.1109\/IoTaIS47347.2019.8980377","DOI":"10.1109\/IoTaIS47347.2019.8980377"},{"key":"e_1_2_10_47_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNSM.2015.2407882"},{"key":"e_1_2_10_48_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11227-016-1785-9"},{"key":"e_1_2_10_49_1","doi-asserted-by":"crossref","unstructured":"AlmutairiAA El RahmanSA.The impact of IBM cloud solutions on students in Saudi Arabia. Proceedings of the 2016 4th International Japan\u2010Egypt Conference on Electronics Communications and Computers (JEC\u2010ECC); 2016:115\u2010118; Cairo. doi:10.1109\/JEC-ECC.2016.7518981","DOI":"10.1109\/JEC-ECC.2016.7518981"},{"key":"e_1_2_10_50_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2877704"},{"key":"e_1_2_10_51_1","doi-asserted-by":"publisher","DOI":"10.1109\/LCOMM.2020.2984430"}],"container-title":["Transactions on Emerging Telecommunications Technologies"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/ett.4407","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/full-xml\/10.1002\/ett.4407","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/ett.4407","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,8,26]],"date-time":"2023-08-26T00:10:22Z","timestamp":1693008622000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/ett.4407"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,12,3]]},"references-count":50,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2022,4]]}},"alternative-id":["10.1002\/ett.4407"],"URL":"https:\/\/doi.org\/10.1002\/ett.4407","archive":["Portico"],"relation":{},"ISSN":["2161-3915","2161-3915"],"issn-type":[{"value":"2161-3915","type":"print"},{"value":"2161-3915","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,12,3]]},"assertion":[{"value":"2021-03-04","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2021-11-03","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2021-12-03","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"e4407"}}