survey

A Comprehensive Survey on Collaborative Data-access Enablers in the IIoT

Authors:

Schahram DustdarAuthors Info & Claims

ACM Computing Surveys, Volume 56, Issue 2

Article No.: 50, Pages 1 - 37

https://doi.org/10.1145/3612918

Published: 15 September 2023 Publication History

Abstract

The scope of the Industrial Internet of Things (IIoT) has stretched beyond manufacturing to include energy, healthcare, transportation, and all that tomorrow’s smart cities will entail. The realm of IIoT includes smart sensors, actuators, programmable logic controllers, distributed control systems (DCS), embedded devices, supervisory control, and data acquisition systems—all produced by manufacturers for different purposes and with different data structures and formats; designed according to different standards and made to follow different protocols. In this sea of incompatibility, how can we flexibly acquire these heterogeneous data, and how can we uniformly structure them to suit thousands of different applications? In this article, we survey the four pillars of information science that enable collaborative data access in an IIoT—standardization, data acquisition, data fusion, and scalable architecture—to provide an up-to-date audit of current research in the field. Here, standardization in IIoT relies on standards and technologies to make things communicative; data acquisition attempts to transparently collect data through plug-and-play architectures, reconfigurable schemes, or hardware expansion; data fusion refers to the techniques and strategies for overcoming heterogeneity in data formats and sources; and scalable architecture provides basic techniques to support heterogeneous requirements. The article also concludes with an overview of the frontier researches and emerging technologies for supporting or challenging data access from the aspects of 5G, machine learning, blockchain, and semantic web.

References

[1]

ISO T. C. 184. 2022. Automation systems and integration. Retrieved from https://www.iso.org/committee/54110.html

[2]

3GPP TR 22.804. 2020. Study on Communication for Automation in Vertical domains. Retrieved from https://portal.3gpp.org/desktopmodules/Specifications/SpecificationDetails.aspx?specificationId=3187

[3]

3GPP TR 22.821. 2018. Feasibility Study on LAN Support in 5G. Retrieved from https://portal.3gpp.org/desktopmodules/Specifications/SpecificationDetails.aspx?specificationId=3281

[4]

5G ACIA. 2019. 5G for Connected Industries and Automation. Retrieved from https://5g-acia.org/wp-content/uploads/2021/04/WP_5G_for_Connected_Industries_and_Automation_Download_19.03.19.pdf

[5]

ABB. 2022. Introducing ABB Ability. Retrieved from https://global.abb/topic/ability/en/about

[6]

Giuseppe Aceto, Valerio Persico, and Antonio Pescapé. 2019. A survey on information and communication technologies for industry 4.0: State-of-the-art, taxonomies, perspectives, and challenges. IEEE Commun. Surv. Tutor. 21, 4 (2019), 3467–3501.

Digital Library

[7]

Tolulope Adesina and Oladiipo Osasona. 2019. A novel cognitive IoT gateway framework: Towards a holistic approach to IoT interoperability. In IEEE 5th World Forum on Internet of Things (WF-IoT’19). IEEE, 53–58.

[8]

A. Ahmed and G. Pierre. 2018. Docker container deployment in fog computing infrastructures. In IEEE International Conference on Edge Computing (EDGE’18). 1–8.

[9]

Khaled Al-Gumaei, Kornelia Schuba, Andrej Friesen, Sascha Heymann, Carsten Pieper, Florian Pethig, and Sebastian Schriegel. 2018. A survey of internet of things and big data integrated solutions for industrie 4.0. In A Survey of Internet of Things and Big Data Integrated Solutions for Industrie 4.0, Vol. 1. IEEE, 1417–1424.

[10]

Fadi Al-Turjman and Sinem Alturjman. 2020. 5G/IoT-enabled UAVs for multimedia delivery in industry-oriented applications. Multim. Tools Applic. 79 (2020), 8627–8648.

[11]

Damminda Alahakoon and Xinghuo Yu. 2015. Smart electricity meter data intelligence for future energy systems: A survey. IEEE Trans. Industr. Inform. 12, 1 (2015), 425–436.

[12]

Mary B. Alatise and Gerhard P. Hancke. 2017. Pose estimation of a mobile robot based on fusion of IMU data and vision data using an extended Kalman filter. Sensors 17, 10 (2017), 2164.

[13]

Amazon. 2023. AWS IoT overview. Retrieved from https://aws.amazon.com/iot/?nc1=h_ls

[14]

Babu S. Anish, Hareesh M. J., John Paul Martin, Sijo Cherian, and Yedhu Sastri. 2014. System performance evaluation of para virtualization, container virtualization, and full virtualization using Xen, OpenVZ, and XenServer. In 4th International Conference on Advances in Computing and Communications. 247–250.

[15]

Ansif Arooj, Muhammad Shoaib Farooq, Tariq Umer, Ghulam Rasool, and Bo Wang. 2020. Cyber physical and social networks in IoV (CPSN-IoV): A multimodal architecture in edge-based networks for optimal route selection using 5G technologies. IEEE Access 8 (2020), 33609–33630.

[16]

Md. Asif-Ur-Rahman, Fariha Afsana, Mufti Mahmud, M. Shamim Kaiser, Muhammad R. Ahmed, Omprakash Kaiwartya, and Anne James-Taylor. 2018. Toward a heterogeneous mist, fog, and cloud-based framework for the internet of healthcare things. IEEE Internet Things J. 6, 3 (2018), 4049–4062.

[17]

Hany F. Atlam, Robert J. Walters, and Gary B. Wills. 2018. Fog computing and the internet of things: A review. Big Data Cogn. Comput. 2, 2 (2018), 10.

[18]

Arshdeep Bahga and Vijay K. Madisetti. 2016. Blockchain platform for industrial internet of things. J. Softw. Eng. Applic. 9, 10 (2016), 533–546.

[19]

Roger Baig, Roger Pueyo Centelles, Felix Freitag, and Leandro Navarro. 2017. On edge microclouds to provide local container-based services. In Global Information Infrastructure and Networking Symposium (GIIS’17). 31–36.

[20]

Balena. Balena. Retrieved from https://www.balena.io/

[21]

Suprateek Banerjee and Daniel Großmann. 2016. An electronic device description language based approach for communication with DBMS and file system in an industrial automation scenario. In IEEE 21st International Conference on Emerging Technologies and Factory Automation (ETFA’16). IEEE, 1–4.

Digital Library

[22]

Shuang Bao, Hairong Yan, Qingping Chi, Zhibo Pang, and Yuying Sun. 2017. FPGA-based reconfigurable data acquisition system for industrial sensors. IEEE Trans. Industr. Inform. 13, 4 (2017), 1503–1512.

[23]

A. Anand Bardwaj, M Anandaraj, K. Kapil, S. Vasuhi, and V. Vaidehi. 2008. Multi sensor data fusion methods using sensor data compression and estimated weights. In International Conference on Signal Processing, Communications and Networking. IEEE, 250–254.

[24]

Luis Barreto, Antonio Amaral, and Teresa Pereira. 2017. Industry 4.0 implications in logistics: An overview. Procedia Manuf. 13 (2017), 1245–1252.

[25]

Flavio Bonomi, Rodolfo Milito, Jiang Zhu, and Sateesh Addepalli. 2012. Fog computing and its role in the internet of things. In 1st Edition of the MCC Workshop on Mobile Cloud Computing. 13–16.

[26]

Borja Bordel, Diego Sánchez De Rivera, and Ramón Alcarria. 2016. Plug-and-play transducers in cyber-physical systems for device-driven applications. In 10th International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing (IMIS’16). IEEE, 316–321.

[27]

Mike Botts, George Percivall, Carl Reed, and John Davidson. 2006. OGC® sensor web enablement: Overview and high level architecture. In 2nd International Conference on GeoSensor Networks. Springer, 175–190.

[28]

Hugh Boyes, Bil Hallaq, Joe Cunningham, and Tim Watson. 2018. The Industrial Internet of Things (IIoT): An analysis framework. Comput. Industr. 101 (2018), 1–12.

[29]

Arne Bröring, Patrick Maué, Krzysztof Janowicz, Daniel Nüst, and Christian Malewski. 2011. Semantically-enabled sensor plug & play for the sensor web. Sensors 11, 8 (2011), 7568–7605.

[30]

Edouard Bugnion, Scott Devine, Mendel Rosenblum, Jeremy Sugerman, and Edward Y. Wang. 2012. Bringing virtualization to the X86 architecture with the original VMware workstation. ACM Trans. Comput. Syst. 30, 4 (2012), 1–51.

Digital Library

[31]

He Cai, Cunqing Hua, and Wenchao Xu. 2019. Design of active learning framework for collaborative anomaly detection. In 11th International Conference on Wireless Communications and Signal Processing (WCSP’19). IEEE, 1–7.

[32]

Ronghui Cao, Zhuo Tang, Chubo Liu, and Bharadwaj Veeravalli. 2020. A scalable multicloud storage architecture for cloud-supported medical internet of things. IEEE Internet Things J. 7, 3 (2020), 1641–1654.

[33]

Hyunseok Chang, Adiseshu Hari, Sarit Mukherjee, and T. V. Lakshman. 2014. Bringing the cloud to the edge. In IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS’14). IEEE, 346–351.

[34]

Wo L. Chang, David Boyd, and Orit Levin. 2019. NIST Big Data Interoperability Framework: Volume 6, Reference Architecture. (October 2019).

[35]

Djabir Abdeldjalil Chekired, Lyes Khoukhi, and Hussein T. Mouftah. 2018. Industrial IoT data scheduling based on hierarchical fog computing: A key for enabling smart factory. IEEE Trans. Industr. Inform. 14, 10 (2018), 4590–4602.

[36]

Hung-Li Chen and Fuchun Joseph Lin. 2019. Scalable IoT/M2M platforms based on Kubernetes-enabled NFV MANO architecture. In International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData). 1106–1111.

[37]

Jiasi Chen and Xukan Ran. 2019. Deep learning with edge computing: A review. Proc. IEEE 107, 8 (2019), 1655–1674.

[38]

Jiangfeng Cheng, Weihai Chen, Fei Tao, and Chun-Liang Lin. 2018. Industrial IoT in 5G environment towards smart manufacturing. J. Industr. Inf. Integ. 10 (2018), 10–19.

[39]

Ledan Cheng, Songtao Guo, Ying Wang, and Yuanyuan Yang. 2016. Lifting wavelet compression based data aggregation in big data wireless sensor networks. In IEEE 22nd International Conference on Parallel and Distributed Systems (ICPADS’16). IEEE, 561–568.

[40]

Ying Cheng, Yongping Zhang, Ping Ji, Wenjun Xu, Zude Zhou, and Fei Tao. 2018. Cyber-physical integration for moving digital factories forward towards smart manufacturing: A survey. Int. J. Advan. Manuf. Technol. 97, 1–4 (2018), 1209–1221.

[41]

Avarachan Cherian, Darold Wobschall, and Mehrdad Sheikholeslami. 2017. An IoT interface for industrial analog sensor with IEEE 21451 protocol. In IEEE Sensors Applications Symposium (SAS’17). IEEE, 1–5.

[42]

Qingping Chi, Hairong Yan, Chuan Zhang, Zhibo Pang, and Li Da Xu. 2014. A reconfigurable smart sensor interface for industrial WSN in IoT environment. IEEE Trans. Industr. Inform. 10, 2 (2014), 1417–1425.

[43]

Yuanfang Chi, Yanjie Dong, Jane Wang, F. Richard Yu, and Victor C. M. Leung. 2022. Knowledge-based fault diagnosis in industrial internet of things: A survey. IEEE Internet Things J. 9, 15 (2022), 12886–12900.

[44]

Industrial Internet Consortium.2022. Industrial internet reference architecture. Retrieved from https://www.iiconsortium.org/IIRA/

[45]

Li Da Xu, Wu He, and Shancang Li. 2014. Internet of things in industries: A survey. IEEE Trans. Industr. Inform. 10, 4 (2014), 2233–2243.

[46]

Jad Darrous, Thomas Lambert, and Shadi Ibrahim. 2019. On the importance of container image placement for service provisioning in the edge. In 28th International Conference on Computer Communication and Networks (ICCCN’19). 1–9.

[47]

Suparna De, Maria Bermudez-Edo, Honghui Xu, and Zhipeng Cai. 2022. Deep generative models in the industrial internet of things: A survey. IEEE Trans. Industr. Inform. 18, 9 (2022), 5728–5737.

[48]

Shuiguang Deng, Zhengzhe Xiang, Peng Zhao, Javid Taheri, Honghao Gao, Jianwei Yin, and Albert Y. Zomaya. 2020. Dynamical resource allocation in edge for trustable internet-of-things systems: A reinforcement learning method. IEEE Trans. Industr. Inform. 16, 9 (2020), 6103–6113.

[49]

Shuiguang Deng, Hailiang Zhao, Weijia Fang, Jianwei Yin, Schahram Dustdar, and Albert Y. Zomaya. 2020. Edge intelligence: The confluence of edge computing and artificial intelligence. IEEE Internet Things J. 7, 8 (2020), 7457–7469.

[50]

Christian Diedrich, Alexander Belyaev, Tizian Schröder, Jens Vialkowitsch, Alexander Willmann, Thomas Usländer, Heiko Koziolek, Jörg Wende, Florian Pethig, and Oliver Niggemann. 2017. Semantic interoperability for asset communication within smart factories. In 22nd IEEE International Conference on Emerging Technologies and Factory Automation (ETFA’17). IEEE, 1–8.

Digital Library

[51]

Zhiming Ding, Bin Yang, Yuanying Chi, and Limin Guo. 2015. Enabling smart transportation systems: A parallel spatio-temporal database approach. IEEE Trans. Comput. 65, 5 (2015), 1377–1391.

Digital Library

[52]

Jasenka Dizdarević, Francisco Carpio, Admela Jukan, and Xavi Masip-Bruin. 2019. A survey of communication protocols for internet of things and related challenges of fog and cloud computing integration. ACM Computing Surveys (CSUR) 51, 6 (2019), 1–29.

Digital Library

[53]

Docker. What is a Container? Retrieved from https://www.docker.com/resources/what-container. (n.d.).

[54]

Rong Du, Paolo Santi, Ming Xiao, Athanasios V. Vasilakos, and Carlo Fischione. 2018. The sensable city: A survey on the deployment and management for smart city monitoring. IEEE Commun. Surv. Tutor. 21, 2 (2018), 1533–1560.

[55]

Corentin Dupont, Raffaele Giaffreda, and Luca Capra. 2017. Edge computing in IoT context: Horizontal and vertical Linux container migration. In 2017 Global Internet of Things Summit (GIoTS). IEEE, 1–4.

[56]

Charbel El Kaed, Imran Khan, Hicham Hossayni, and Philippe Nappey. 2016. SQenloT: Semantic query engine for industrial Internet-of-Things gateways. In 2016 IEEE 3rd World Forum on Internet of Things (WF-IoT). IEEE, 204–209.

[57]

Charbel El Kaed, Imran Khan, Andre Van Den Berg, Hicham Hossayni, and Christophe Saint-Marcel. 2017. SRE: Semantic rules engine for the industrial Internet-of-Things gateways. IEEE Trans. Industr. Inform. 14, 2 (2017), 715–724.

[58]

Melike Erol-Kantarci and Hussein T. Mouftah. 2014. Energy-efficient information and communication infrastructures in the smart grid: A survey on interactions and open issues. IEEE Commun. Surv. Tutor. 17, 1 (2014), 179–197.

Digital Library

[59]

Alireza Esfahani, Georgios Mantas, Rainer Matischek, Firooz B Saghezchi, Jonathan Rodriguez, Ani Bicaku, Silia Maksuti, Markus G. Tauber, Christoph Schmittner, and Joaquim Bastos. 2017. A lightweight authentication mechanism for M2M communications in industrial IoT environment. IEEE Internet Things J. 6, 1 (2017), 288–296.

[60]

Lennart Espe, Anshul Jindal, Vladimir Podolskiy, and Michael Gerndt. 2020. Performance Evaluation of Container Runtimes. In Proceedings of the 10th International Conference on Cloud Computing and Services Science (CLOSER’20). 273–281.

[61]

Xi Fang, Satyajayant Misra, Guoliang Xue, and Dejun Yang. 2011. Smart grid—The new and improved power grid: A survey. IEEE Commun. Surv. Tutor. 14, 4 (2011), 944–980.

[62]

Miguel A. Fernandes, Samuel G. Matos, Emanuel Peres, Carlos R. Cunha, Juan A. López, P. J. S. G. Ferreira, M. J. C. S. Reis, and Raul Morais. 2013. A framework for wireless sensor networks management for precision viticulture and agriculture based on IEEE 1451 standard. Comput. Electron. Agric. 95 (2013), 19–30.

Digital Library

[63]

Santiago Figueroa-Lorenzo, Javier Añorga, and Saioa Arrizabalaga. 2020. A survey of IIoT protocols: A measure of vulnerability risk analysis based on CVSS. ACM Comput. Surv. 53, 2 (2020), 1–53.

Digital Library

[64]

Ian Foster. 2003. THE GRID: Computing without bounds. Scient. Am. 288, 4 (2003), 78–85.

[65]

Paula Fraga-Lamas, Tiago M. Fernández-Caramés, and Luis Castedo. 2017. Towards the internet of smart trains: A review on industrial IoT-connected railways. Sensors 17, 6 (2017), 1457.

[66]

Yuan Gao, Haoxuan Wang, and Xin Huang. 2016. Applying Docker swarm cluster into software defined internet of things. In 8th International Conference on Information Technology in Medicine and Education (ITME’16). IEEE, 445–449.

[67]

Rafael Garcia, Ann Gordon-Ross, and Alan D. George. 2009. exploiting partially reconfigurable FPGAs for situation-based reconfiguration in wireless sensor networks. In 17th IEEE Symposium on Field Programmable Custom Computing Machines. IEEE, 243–246.

[68]

Dimitrios Georgakopoulos, Prem Prakash Jayaraman, Maria Fazia, Massimo Villari, and Rajiv Ranjan. 2016. Internet of things and edge cloud computing roadmap for manufacturing. IEEE Cloud Comput. 3, 4 (2016), 66–73.

[69]

Ammar Gharaibeh, Mohammad A. Salahuddin, Sayed Jahed Hussini, Abdallah Khreishah, Issa Khalil, Mohsen Guizani, and Ala Al-Fuqaha. 2017. Smart cities: A survey on data management, security, and enabling technologies. IEEE Commun. Surv. Tutor. 19, 4 (2017), 2456–2501.

[70]

Nam Ky Giang, Victor C. M. Leung, and Rodger Lea. 2016. On developing smart transportation applications in fog computing paradigm. In 6th ACM Symposium on Development and Analysis of Intelligent Vehicular Networks and Applications. 91–98.

[71]

Franco Giustozzi, Julien Saunier, and Cecilia Zanni-Merk. 2018. Context modeling for Industry 4.0: An ontology-based proposal. Procedia Comput. Sci. 126 (2018), 675–684.

Digital Library

[72]

Sotirios K. Goudos, Panagiotis I. Dallas, Stella Chatziefthymiou, and Sofoklis Kyriazakos. 2017. A survey of IoT key enabling and future technologies: 5G, mobile IoT, sematic web and applications. Wirel. Person. Commun. 97, 2 (2017), 1645–1675.

Digital Library

[73]

Robert David Graham and Peter C. Johnson. 2014. Finite state machine parsing for internet protocols: Faster than you think. In IEEE Security and Privacy Workshops. IEEE, 185–190.

[74]

Irlán Grangel-González, Paul Baptista, Lavdim Halilaj, Steffen Lohmann, Maria-Esther Vidal, Christian Mader, and Sören Auer. 2017. The Industry 4.0 standards landscape from a semantic integration perspective. In 22nd IEEE International Conference on Emerging Technologies and Factory Automation (ETFA’17). IEEE, 1–8.

Digital Library

[75]

Marcel Großmann and Clemens Klug. 2017. Monitoring container services at the network edge. In 29th International Teletraffic Congress (ITC’17).. 130–133.

[76]

Jean A. Guevara, Enrique A. Vargas, Arturo F. Fatecha, and Federico Barrero. 2015. Dynamically reconfigurable WSN node based on ISO/IEC/IEEE 21451 TEDS. IEEE Sensors J. 15, 5 (2015), 2567–2576.

[77]

Shaoyong Guo, Yao Dai, Siya Xu, Xuesong Qiu, and Feng Qi. 2019. Trusted cloud-edge network resource management: Drl-driven service function chain orchestration for IoT. IEEE Internet of Things Journal 7, 7 (2019).

[78]

Quang Phuc Ha, Santanu Metia, and Manh Duong Phung. 2020. Sensing data fusion for enhanced indoor air quality monitoring. IEEE Sensors J. 20, 8 (2020), 4430–4441.

[79]

Lida Haghnegahdar, Sameehan S. Joshi, and Narendra B. Dahotre. 2022. From IoT-based cloud manufacturing approach to intelligent additive manufacturing: Industrial Internet of Things—An overview. Int. J. Advan. Manuf. Technol. 79 (2022), 1–18.

[80]

Ibrahim Abaker Targio Hashem, Ibrar Yaqoob, Nor Badrul Anuar, Salimah Mokhtar, Abdullah Gani, and Samee Ullah Khan. 2015. The rise of “big data” on cloud computing: Review and open research issues. Inf. Syst. 47 (2015), 98–115.

Digital Library

[81]

Abhishek Hazra, Mainak Adhikari, Tarachand Amgoth, and Satish Narayana Srirama. 2021. A comprehensive survey on interoperability for IIoT: Taxonomy, standards, and future directions. ACM Comput. Surv. 55, 1 (2021), 1–35.

Digital Library

[82]

Heiko Hinkelmann, Andreas Reinhardt, Sameer Varyani, and Manfred Glesner. 2008. A reconfigurable prototyping platform for smart sensor networks. In 4th Southern Conference on Programmable Logic. 125–130.

[83]

Pascal Hitzler, Markus Krotzsch, and Sebastian Rudolph. 2009. Foundations of Semantic Web Technologies. CRC Press.

[84]

Saiful Hoque, Mathias Santos De Brito, Alexander Willner, Oliver Keil, and Thomas Magedanz. 2017. Towards container orchestration in fog computing infrastructures. In IEEE 41st Annual Computer Software and Applications Conference (COMPSAC’17). 294–299.

[85]

Ian Horrocks, Peter F. Patel-Schneider, Harold Boley, Said Tabet, Benjamin Grosof, and Mike Dean. 2004. SWRL: A semantic web rule language combining OWL and RuleML. W3C Memb. Submiss. 21, 79 (2004), 1–31.

[86]

M. Shamim Hossain and Ghulam Muhammad. 2016. Cloud-assisted Industrial Internet of Things (IIoT)–enabled framework for health monitoring. Comput. Netw. 101 (2016), 192–202.

Digital Library

[87]

Kevin Hsieh, Aaron Harlap, Nandita Vijaykumar, Dimitris Konomis, Gregory R. Ganger, Phillip B. Gibbons, and Onur Mutlu. 2017. Gaia: Geo-distributed machine learning approaching LAN speeds. In USENIX Symposium on Networked Systems Design and Implementation (NSDI’17). 629–647.

[88]

Yu-Chen Hsieh, Hua-Jun Hong, Pei-Hsuan Tsai, Yu-Rong Wang, Qiuxi Zhu, M.d. Yusuf Sarwar Uddin, Nalini Venkatasubramanian, and Cheng-Hsin Hsu. 2018. Managed edge computing on Internet-of-Things devices for smart city applications. In IEEE/IFIP Network Operations and Management Symposium. 1–2.

[89]

Bobo Huang, Rui Zhang, Zhihui Lu, Yiming Zhang, Jie Wu, Lu Zhan, and Patrick C. K. Hung. 2020. BPS: A reliable and efficient pub/sub communication model with blockchain-enhanced paradigm in multi-tenant edge cloud. Journal of Parallel and Distributed Computing 143, (2020).

[90]

Junqin Huang, Linghe Kong, Guihai Chen, Min-You Wu, Xue Liu, and Peng Zeng. 2019. Towards secure industrial IoT: Blockchain system with credit-based consensus mechanism. IEEE Trans. Industr. Inform. 15, 6 (2019), 3680–3689.

[91]

Xumin Huang, Peichun Li, and Rong Yu. 2019. Social welfare maximization in container-based task scheduling for parked vehicle edge computing. IEEE Commun. Lett. 23, 8 (2019), 1347–1351.

[92]

Yuzhou Huang, Kaiyu Cai, Ran Zong, and Yugang Mao. 2019. Design and implementation of an edge computing platform architecture using Docker and Kubernetes for machine learning. In 3rd International Conference on High Performance Compilation, Computing and Communications. 29–32.

Digital Library

[93]

Ru Huo, Shiqin Zeng, Zhihao Wang, Jiajia Shang, Wei Chen, Tao Huang, Shuo Wang, F. Richard Yu, and Yunjie Liu. 2022. A comprehensive survey on blockchain in industrial internet of things: Motivations, research progresses, and future challenges. IEEE Commun. Surv. Tutor. 24, 1 (2022), 88–122.

[94]

Joo-Young Hwang, Sang-Bum Suh, Sung-Kwan Heo, Chan-Ju Park, Jae-Min Ryu, Seong-Yeol Park, and Chul-Ryun Kim. 2008. Xen on ARM: System virtualization using Xen hypervisor for ARM-based secure mobile phones. In 5th IEEE Consumer Communications and Networking Conference. 257–261.

[95]

IEC-International Electrotechnical Commission and others. 2016. IEC 61360-6. Retrieved from https://webstore.iec.ch/publication/25984

[96]

ISO. ISO/IEC 20005:2013. Retrieved from https://www.iso.org/cms/render/live/en/sites/isoorg/contents/data/standard/05/09/50952.html

[97]

ISO. ISO/IEC 20248:2018. Retrieved from https://www.iso.org/cms/render/live/en/sites/isoorg/contents/data/standard/06/74/67412.html

[98]

ISO. ISO/IEC 29143:2011. Retrieved from https://www.iso.org/cms/render/live/en/sites/isoorg/contents/data/standard/04/51/45166.html

[99]

ISO. ISO/IEC 29175:2012. Retrieved from https://www.iso.org/cms/render/live/en/sites/isoorg/contents/data/standard/04/52/45254.html

[100]

ISO. ISO/IEC 29182-1:2013. Retrieved from https://www.iso.org/cms/render/live/en/sites/isoorg/contents/data/standard/04/52/45261.html

[101]

ISO. ISO/IEC 30101:2014. Retrieved from https://www.iso.org/cms/render/live/en/sites/isoorg/contents/data/standard/05/32/53221.html

[102]

Davood Izadi, Jemal H. Abawajy, Sara Ghanavati, and Tutut Herawan. 2015. A data fusion method in wireless sensor networks. Sensors 15, 2 (2015), 2964–2979.

[103]

Kavita Jaiswal, Srichandan Sobhanayak, Bhabendu Kumar Mohanta, and Debasish Jena. 2017. IoT-cloud based framework for patient’s data collection in smart healthcare system using Raspberry-Pi. In International Conference on Electrical and Computing Technologies and Applications (ICECTA’17). IEEE, 1–4.

[104]

Bilal Jan, Haleem Farman, Murad Khan, Muhammad Talha, and Ikram Ud Din. 2019. Designing a smart transportation system: An internet of things and big data approach. IEEE Wirel. Commun. 26, 4 (2019), 73–79.

Digital Library

[105]

Kanwal Janjua, Munam Ali Shah, Ahmad Almogren, Hasan Ali Khattak, Carsten Maple, and Ikram Ud Din. 2020. Proactive forensics in IoT: Privacy-aware log-preservation architecture in fog-enabled-cloud using holochain and containerization technologies. Electronics 9, 7 (2020), 1172.

[106]

Juergen Jasperneite, Thilo Sauter, and Martin Wollschlaeger. 2020. Why we need automation models: Handling complexity in Industry 4.0 and the internet of things. IEEE Industr. Electron. Mag. 14, 1 (Mar.2020), 29–40.

[107]

Isam Mashhour Al Jawarneh, Paolo Bellavista, Filippo Bosi, Luca Foschini, Giuseppe Martuscelli, Rebecca Montanari, and Amedeo Palopoli. 2019. Container orchestration engines: A thorough functional and performance comparison. In IEEE International Conference on Communications (ICC’19). 1–6.

[108]

Chengfeng Jian, Jing Ping, and Meiyu Zhang. 2021. A cloud edge-based two-level hybrid scheduling learning model in cloud manufacturing. Int. J. Product. Res. 59, 16 (2021), 4836–4850.

[109]

Bin Jiang, Jianqiang Li, Guanghui Yue, and Houbing Song. 2021. Differential privacy for industrial internet of things: Opportunities, applications, and challenges. IEEE Internet Things J. 8, 13 (2021), 10430–10451.

[110]

Feibo Jiang, Kezhi Wang, Li Dong, Cunhua Pan, Wei Xu, and Kun Yang. 2020. Deep-learning-based joint resource scheduling algorithms for hybrid MEC networks. IEEE Internet Things J. 7, 7 (2020), 6252–6265.

[111]

Tao Jiang, Jianhua Zhang, Pan Tang, Lei Tian, Yi Zheng, Jianwu Dou, Henrik Asplund, Leszek Raschkowski, Raffaele D’Errico, and Tommi Jämsä. 2021. 3GPP standardized 5G channel model for IIoT scenarios: A survey. IEEE Internet Things J. 8, 11 (2021), 8799–8815.

[112]

Rajive Joshi, Paul Didier, Jaime Jimenez, and Timothy Carey. 2017. The industrial internet of things volume G5: Connectivity framework. Industr. Internet Consort. Rep. (2017). https://www.iiconsortium.org/pdf/IIC_PUB_G5_V1.0_PB_20170228.pdf

[113]

Amin Jula, Elankovan Sundararajan, and Zalinda Othman. 2014. Cloud computing service composition: A systematic literature review. Expert Syst. Applic. 41, 8 (2014), 3809–3824.

Digital Library

[114]

Jun Zhang, Kai Chen, Baojing Zuo, Ruhui Ma, Yaozu Dong, and Haibing Guan. 2010. Performance analysis towards a KVM-based embedded real-time virtualization architecture. In 5th International Conference on Computer Sciences and Convergence Information Technology. 421–426.

[115]

Shahidullah Kaiser, M.d. Sadun Haq, Ali Şaman Tosun, and Turgay Korkmaz. 2022. Container technologies for ARM architecture: A comprehensive survey of the state-of-the-art. IEEE Access 10 (2022), 84853–84881.

[116]

Syed Rameez Ullah Kakakhel, Lauri Mukkala, Tomi Westerlund, and Juha Plosila. 2018. Virtualization at the network edge: A technology perspective. In 3rd International Conference on Fog and Mobile Edge Computing (FMEC’18). 87–92.

[117]

David Kampert and Ulrich Epple. 2012. Modeling asset information for interoperable software systems. In IEEE 10th International Conference on Industrial Informatics. IEEE, 947–952.

[118]

Yiping Kang, Johann Hauswald, Cao Gao, Austin Rovinski, Trevor Mudge, Jason Mars, and Lingjia Tang. 2017. Neurosurgeon: Collaborative intelligence between the cloud and mobile edge. ACM SIGARCH Comput. Archit. News 45, 1 (2017), 615–629.

Digital Library

[119]

Gayatri Kapil, Alka Agrawal, and R. A. Khan. 2016. A study of big data characteristics. In International Conference on Communication and Electronics Systems (ICCES’16). 1–4.

[120]

Kuljeet Kaur, Sahil Garg, Georges Kaddoum, Syed Hassan Ahmed, and Mohammed Atiquzzaman. 2020. KEIDS: Kubernetes based Energy and Interference Driven Scheduler for industrial IoT in edge-cloud ecosystem. IEEE Internet Things J. 7, 5 (2020), 4228–4237.

[121]

Ruhul Amin Khalil, Nasir Saeed, Mudassir Masood, Yasaman Moradi Fard, Mohamed-Slim Alouini, and Tareq Y. Al-Naffouri. 2021. Deep learning in the industrial internet of things: Potentials, challenges, and emerging applications. IEEE Internet Things J. 8, 14 (2021), 11016–11040.

[122]

Wazir Zada Khan, M. H. Rehman, Hussein Mohammed Zangoti, Muhammad Khalil Afzal, Nasrullah Armi, and Khaled Salah. 2020. Industrial internet of things: Recent advances, enabling technologies and open challenges. Comput. Electric. Eng. 81 (2020), 106522.

Digital Library

[123]

Jayoung Kim, Alan S. Campbell, Berta Esteban-Fernández de Ávila, and Joseph Wang. 2019. Wearable biosensors for healthcare monitoring. Nat. Biotechnol. 37, 4 (2019), 389–406.

[124]

Tim Kraska, Ameet Talwalkar, John C. Duchi, Rean Griffith, Michael J. Franklin, and Michael I. Jordan. 2013. MLbase: A Distributed Machine-learning System. In 6th Biennial Conference on Innovative Data Systems Research (CIDR’13). 2–1.

[125]

X. Krasniqi and E. Hajrizi. 2016. Use of IoT technology to drive the automotive industry from connected to full autonomous vehicles. IFAC-PapersOnLine 49, 29 (2016), 269–274.

[126]

Yana Esteves Krasteva, Jorge Portilla, Eduardo de la Torre, and Teresa Riesgo. 2011. Embedded runtime reconfigurable nodes for wireless sensor networks applications. IEEE Sensors J. 11, 9 (2011), 1800–1810.

[127]

Nihal Kularatna and B. H. Sudantha. 2008. An environmental air pollution monitoring system based on the IEEE 1451 standard for low cost requirements. IEEE Sensors J. 8, 4 (2008), 415–422.

[128]

Anuj Kumar and Gerhard P. Hancke. 2014. An energy-efficient smart comfort sensing system based on the IEEE 1451 standard for green buildings. IEEE Sensors J. 14, 12 (2014), 4245–4252.

[129]

Anuj Kumar, Abhishek Singh, Ashok Kumar, Manoj Kumar Singh, Pinakeswar Mahanta, and Subhas Chandra Mukhopadhyay. 2018. Sensing technologies for monitoring intelligent buildings: A review. IEEE Sensors J. 18, 12 (2018), 4847–4860.

[130]

Anuj Kumar, I. P. Singh, and S. K. Sud. 2011. Energy efficient and low-cost indoor environment monitoring system based on the IEEE 1451 standard. IEEE Sensors J. 11, 10 (2011), 2598–2610.

[131]

K. N. Prashanth Kumar, V. Ravi Kumar, and K. Raghuveer. 2017. A survey on semantic web technologies for the internet of things. In International Conference on Current Trends in Computer, Electrical, Electronics and Communication (CTCEEC’17). IEEE, 316–322.

[132]

Benoit Larras and Antoine Frappé. 2020. Distributed clique-based neural networks for data fusion at the edge. In IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS’20). 55–58.

[133]

Billy Pik Lik Lau, Sumudu Hasala Marakkalage, Yuren Zhou, Naveed Ul Hassan, Chau Yuen, Meng Zhang, and U-Xuan Tan. 2019. A survey of data fusion in smart city applications. Inf. Fusion 52 (2019), 357–374.

Digital Library

[134]

Juyong Lee and Jihoon Lee. 2020. Juice recipe recommendation system using machine learning in MEC environment. IEEE Consum. Electron. Mag. 9, 5 (2020), 79–84.

[135]

Kyung Chang Lee, Man Ho Kim, Suk Lee, and Hong Hee Lee. 2004. IEEE-1451-based smart module for in-vehicle networking systems of intelligent vehicles. IEEE Trans. Industr. Electron. 51, 6 (2004), 1150–1158.

[136]

Joerg Leukel. 2004. Standardization of product ontologies in B2B relationships-on the role of ISO 13584. In Americas Conference on Information Systems (AMCIS’04). 510. https://aisel.aisnet.org/cgi/viewcontent.cgi?article=2086&context=amcis2004

[137]

Peilong Li, Chen Xu, Hao Jin, Chunyang Hu, Yan Luo, Yu Cao, Jomol Mathew, and Yunsheng Ma. 2020. ChainSDI: A software-defined infrastructure for regulation-compliant home-based healthcare services secured by blockchains. IEEE Syst. J. 14, 2 (2020), 2042–2053.

[138]

Quanyi Li, Haipeng Yao, Tianle Mai, Chunxiao Jiang, and Yan Zhang. 2020. Reinforcement-learning- and belief-learning-based double auction mechanism for edge computing resource allocation. IEEE Internet Things J. 7, 7 (2020), 5976–5985.

[139]

Youhuizi Li, Jiancheng Zhang, Congfeng Jiang, Jian Wan, and Zujie Ren. 2019. PINE: Optimizing performance isolation in container environments. IEEE Access 7 (2019), 30410–30422.

[140]

Torben R. Licht. 2001. The IEEE 1451.4 proposed standard. IEEE Instrum. Measur. Mag. 4, 1 (2001), 12–18.

[141]

Alex X. Liu, Chad R. Meiners, Eric Norige, and Eric Torng. 2014. High-speed application protocol parsing and extraction for deep flow inspection. IEEE J. Select. Areas Commun. 32, 10 (2014), 1864–1880.

[142]

Boyi Liu, Lujia Wang, and Ming Liu. 2019. Lifelong Federated Reinforcement Learning: A learning architecture for navigation in cloud robotic systems. IEEE Robotics and Automation Letters 4, 4 (2019), 4555–4562.

[143]

Fanzhen Liu, Shan Xue, Jia Wu, Chuan Zhou, Wenbin Hu, Cecile Paris, Surya Nepal, Jian Yang, and Philip S. Yu. 2020. Deep learning for community detection: Progress, challenges and opportunities. In 29th International Joint Conference on Artificial Intelligence (IJCAI’20). 4981–4987.

[144]

Xiaolan Liu, Jiadong Yu, Jian Wang, and Yue Gao. 2020. Resource allocation with edge computing in IoT networks via machine learning. IEEE Internet Things J. 7, 4 (2020), 3415–3426.

[145]

Wei Lu, Xianyu Meng, and Guanfei Guo. 2019. Fast service migration method based on virtual machine technology for MEC. IEEE Internet Things J. 6, 3 (2019), 4344–4354.

[146]

Yang Lu. 2017. Industry 4.0: A survey on technologies, applications and open research issues. J. Industr. Inf. Integ. 6 (2017), 1–10.

[147]

Yan Lu, Paul Witherell, and Albert Jones. 2020. Standard connections for IIoT empowered smart manufacturing. Manuf. Lett. 26 (2020), 17–20.

[148]

Henrik Lund, Poul Alberg Østergaard, David Connolly, and Brian Vad Mathiesen. 2017. Smart energy and smart energy systems. Energy 137 (2017), 556–565.

[149]

Jia Luo, Qianbin Chen, F. Richard Yu, and Lun Tang. 2020. Blockchain-enabled software-defined industrial internet of things with deep reinforcement learning. IEEE Internet Things J. 7, 6 (2020), 5466–5480.

[150]

Lele Ma, Shanhe Yi, Nancy Carter, and Qun Li. 2019. Efficient live migration of edge services leveraging container layered storage. IEEE Trans. Mob. Comput. 18, 9 (2019), 2020–2033.

Digital Library

[151]

Xiaoxiao Ma, Jia Wu, Shan Xue, Jian Yang, Quan Z. Sheng, and Hui Xiong. 2021. A comprehensive survey on graph anomaly detection with deep learning. arXiv preprint arXiv:2106.07178 (2021).

[152]

Mohammed M. Mabkhot, Abdulrahman M. Al-Ahmari, Bashir Salah, and Hisham Alkhalefah. 2018. Requirements of the smart factory system: A survey and perspective. Machines 6, 2 (2018), 23.

[153]

Andrew Machen, Shiqiang Wang, Kin K. Leung, Bong Jun Ko, and Theodoros Salonidis. 2017. Live service migration in mobile edge clouds. IEEE Wirel. Commun. 25, 1 (2017), 140–147.

Digital Library

[154]

Ananda Maiti, Alexander A. Kist, and Andrew D. Maxwell. 2018. Automata-based generic model for interoperating context-aware ad-hoc devices in internet of things. IEEE Internet Things J. 5, 5 (2018), 3837–3852.

[155]

Simon Mayer, Jack Hodges, Dan Yu, Mareike Kritzler, and Florian Michahelles. 2017. An open semantic framework for the industrial internet of things. IEEE Intell. Syst. 32, 1 (2017), 96–101.

Digital Library

[156]

Deborah L. McGuinness and Frank Van Harmelen. 2004. OWL web ontology language overview. W3C Recomm. 10, 10 (2004), 2004.

[157]

Darshan Vishwasrao Medhane, Arun Kumar Sangaiah, M. Shamim Hossain, Ghulam Muhammad, and Jin Wang. 2020. Blockchain-enabled distributed security framework for next generation IoT: An edge-cloud and software defined network integrated approach. IEEE Internet Things J. 7, 7 (2020), 6143–6149.

[158]

Pankaj Mendki. 2018. Docker container based analytics at IoT edge video analytics usecase. In 3rd International Conference on Internet of Things: Smart Innovation and Usages (IoT-SIU’18). 1–4.

[159]

Zhaozong Meng, Zhipeng Wu, Cahyo Muvianto, and John Gray. 2016. A data-oriented M2M messaging mechanism for industrial IoT applications. IEEE Internet Things J. 4, 1 (2016), 236–246.

[160]

Inc. Mesosphere. 2023. Marathon: A container orchestration platform for Mesos and DC/OS. Retrieved from https://mesosphere.github.io/marathon/

[161]

Microsoft. 2023. Azure IoT overview. Retrieved from https://azure.microsoft.com/en-au/overview/iot/#overview

[162]

Roberto Minerva, Gyu Myoung Lee, and Noel Crespi. 2020. Digital twin in the IoT context: A survey on technical features, scenarios, and architectural models. Proc. IEEE 108, 10 (2020), 1785–1824.

[163]

Arsh Modak, S. D. Chaudhary, P. S. Paygude, and S. R. Ldate. 2018. Techniques to secure data on cloud: Docker swarm or Kubernetes? In 2nd International Conference on Inventive Communication and Computational Technologies (ICICCT’18). 7–12.

[164]

Cristina Morariu, Octavian Morariu, Silviu Răileanu, and Theodor Borangiu. 2020. Machine learning for predictive scheduling and resource allocation in large scale manufacturing systems. Comput. Industr. 120 (2020), 103244.

[165]

Dariusz Mrozek, Anna Koczur, and Bożena Małysiak-Mrozek. 2020. Fall detection in older adults with mobile IoT devices and machine learning in the cloud and on the edge. Inf. Sci. 537 (2020), 132–147.

[166]

Luís Neto, Gil Gonçalves, Pedro Torres, Rogério Dionísio, and Sérgio Malhão. 2019. An industry 4.0 self description information model for software components contained in the administration shell. In 8th International Conference on Intelligent Systems and Applications.

[167]

Irene C. L. Ng and Susan Y. L. Wakenshaw. 2017. The internet-of-things: Review and research directions. Int. J. Res. Market. 34, 1 (2017), 3–21.

[168]

Zhaolong Ning, Xiangjie Kong, Feng Xia, Weigang Hou, and Xiaojie Wang. 2019. Green and sustainable cloud of things: Enabling collaborative edge computing. IEEE Commun. Mag. 57, 1 (2019), 72–78.

Digital Library

[169]

Masaaki Nishikiori. 2011. Server virtualization with VMware vSphere 4. Fujitsu Scient. Technic. J. 47, 3 (2011), 356–361.

[170]

OMRON. 2023. Omron CP1W-20EDR1 datasheet. Retrieved from https://datasheet.octopart.com/CP1W-20EDR1-Omron-datasheet-12510914.pdf

[171]

Michal Orzechowski, Bartosz Balis, Krystian Pawlik, Maciej Pawlik, and Maciej Malawski. 2018. Transparent deployment of scientific workflows across clouds—Kubernetes approach. In IEEE/ACM International Conference on Utility and Cloud Computing Companion (UCC Companion’18). 9–10.

[172]

Emmanuel Oyekanlu. 2018. Osmotic collaborative computing for machine learning and cybersecurity applications in industrial IoT networks and cyber physical systems with Gaussian mixture models. In IEEE 4th International Conference on Collaboration and Internet Computing (CIC’18). IEEE, 326–335.

[173]

Claus Pahl and Brian Lee. 2015. Containers and clusters for edge cloud architectures—A technology review. In 3rd International Conference on Future Internet of Things and Cloud. 379–386.

Digital Library

[174]

Junmin Park, Hyunjae Park, and Young-June Choi. 2018. Data compression and prediction using machine learning for industrial IoT. In International Conference on Information Networking (ICOIN’18). IEEE, 818–820.

[175]

Florian Pethig, Oliver Niggemann, and Armin Walter. 2017. Towards Industrie 4.0 compliant configuration of condition monitoring services. In IEEE 15th International Conference on Industrial Informatics (INDIN’17). IEEE, 271–276.

[176]

Alexey S. Petrenko, Sergei A. Petrenko, Krystina A. Makoveichuk, and Petr V. Chetyrbok. 2018. The IIoT/IoT device control model based on narrow-band IoT (NB-IoT). In IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus’18). IEEE, 950–953.

[177]

Riccardo Petrolo, Valeria Loscri, and Nathalie Mitton. 2017. Towards a smart city based on cloud of things, a survey on the smart city vision and paradigms. Trans. Emerg. Telecommun. Technol. 28, 1 (2017), e2931.

[178]

Ilia Pietri and Rizos Sakellariou. 2016. Mapping virtual machines onto physical machines in cloud computing: A survey. Comput. Surv. 49, 3 (2016).

Digital Library

[179]

Jorge Portilla, Teresa Riesgo, and Angel de Castro. 2007. A reconfigurable FPGA-based architecture for modular nodes in wireless sensor networks. In 3rd Southern Conference on Programmable Logic. 203–206.

[180]

D. Potter. 2002. Smart plug and play sensors. IEEE Instrum. Measur. Mag. 5, 1 (2002), 28–30.

[181]

Gang Qian, Siliang Lu, Donghui Pan, Huasong Tang, Yongbin Liu, and Qunjing Wang. 2019. Edge computing: A promising framework for real-time fault diagnosis and dynamic control of rotating machines using multi-sensor data. IEEE Sensors J. 19, 11 (2019), 4211–4220.

[182]

Tie Qiu, Ning Chen, Keqiu Li, Mohammed Atiquzzaman, and Wenbing Zhao. 2018. How can heterogeneous internet of things build our future: A survey. IEEE Commun. Surv. Tutor. 20, 3 (2018), 2011–2027.

[183]

Tie Qiu, Jiancheng Chi, Xiaobo Zhou, Zhaolong Ning, Mohammed Atiquzzaman, and Dapeng Oliver Wu. 2020. Edge computing in industrial internet of things: Architecture, advances and challenges. IEEE Commun. Surv. Tutor. 22, 4 (2020), 2462–2488.

[184]

Sriganesh K. Rao and Ramjee Prasad. 2018. Impact of 5G technologies on Industry 4.0. Wirel. Person. Commun. 100, 1 (2018), 145–159.

Digital Library

[185]

M. Mazhar Rathore, Awais Ahmad, Anand Paul, and Gwanggil Jeon. 2015. Efficient graph-oriented smart transportation using internet of things generated big data. In 11th International Conference on Signal-Image Technology & Internet-based Systems (SITIS’15). IEEE, 512–519.

Digital Library

[186]

Gourav Rattihalli, Madhusudhan Govindaraju, and Devesh Tiwari. 2019. Towards enabling dynamic resource estimation and correction for improving utilization in an Apache Mesos cloud environment. In 19th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID’19). 188–197.

[187]

Partha Pratim Ray. 2016. A survey of IoT cloud platforms. Fut. Comput. Inform. J. 1, 1–2 (2016), 35–46.

[188]

Yi Ren, Ling Liu, Qi Zhang, Qingbo Wu, Jianbo Guan, Jinzhu Kong, Huadong Dai, and Lisong Shao. 2016. Shared-memory optimizations for inter-virtual-machine communication. Comput. Surv. 48, 4 (2016), 1–42.

Digital Library

[189]

Yuzheng Ren, Renchao Xie, F. Richard Yu, Tao Huang, and Yunjie Liu. 2020. Potential identity resolution systems for the industrial internet of things: A survey. IEEE Commun. Surv. Tutor. 23, 1 (2020), 391–430.

[190]

Wenjie Ruan, Quan Z. Sheng, Lina Yao, Xue Li, Nickolas J. G. Falkner, and Lei Yang. 2018. Device-free human localization and tracking with UHF passive RFID tags: A data-driven approach. J. Netw. Comput. Applic. 104 (2018), 78–96.

[191]

Ahmad-Reza Sadeghi, Christian Wachsmann, and Michael Waidner. 2015. Security and privacy challenges in industrial internet of things. In 52nd Annual Design Automation Conference. IEEE, 1–6.

Digital Library

[192]

T. Sanpechuda and L. Kovavisaruch. 2008. A review of RFID localization: Applications and techniques. In 5th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology. IEEE, 769–772.

[193]

Mahadev Satyanarayanan. 2017. The emergence of edge computing. Computer 50, 1 (2017), 30–39.

Digital Library

[194]

Jacqueline Schmitt, Jochen Bönig, Thorbjörn Borggräfe, Gunter Beitinger, and Jochen Deuse. 2020. Predictive model-based quality inspection using machine learning and edge cloud computing. Adv. Eng. Inform. 45 (2020), 101101.

[195]

Schneider. 2023. TM3XTRA1 remote transmitter module TM3 bus Schneider Electric. Retrieved June 23, 2023 from https://www.schneider-electric.com/en/product/TM3XTRA1/remote-transmitter-module-tm3---bus/

[196]

Stan Schneider. 2017. The Industrial Internet of Things (IIoT) applications and taxonomy. Internet Things Data Analyt. Handb. (2017), 41–81.

[197]

Schneider Electric. 2022. What Are EcoStruxure IT Software & Digital Services? Retrieved from https://ecostruxureit.com/what-is-ecostruxure-it/

[198]

Karsten Schweichhart. 2016. Reference Architectural Model Industrie 4.0 (RAMI 4.0). Retrieved from https://www.plattform-i40.de

[199]

Jayasree Sengupta, Sushmita Ruj, and Sipra Das Bit. 2020. A comprehensive survey on attacks, security issues and blockchain solutions for IoT and IIoT. J. Netw. Comput. Applic. 149 (2020), 102481.

Digital Library

[200]

Shree Krishna Sharma and Xianbin Wang. 2017. Live data analytics with collaborative edge and cloud processing in wireless IoT networks. IEEE Access 5 (2017), 4621–4635.

[201]

Kadam Rekha Shashikant and Anju Kulkarni. 2020. Reconfigurable patch antenna design using pin diodes and Raspberry PI for portable device application. Wirel. Person. Commun. 112, 3 (2020), 1809–1828.

Digital Library

[202]

Mu Shengdong, Xiong Zhengxian, and Tian Yixiang. 2019. Intelligent traffic control system based on cloud computing and big data mining. IEEE Trans. Industr. Inform. 15, 12 (2019), 6583–6592.

[203]

Weisong Shi, Jie Cao, Quan Zhang, Youhuizi Li, and Lanyu Xu. 2016. Edge computing: Vision and challenges. IEEE Internet Things J. 3, 5 (2016), 637–646.

[204]

Konstantin Shvachko, Hairong Kuang, Sanjay Radia, and Robert Chansler. 2010. The Hadoop distributed file system. In IEEE 26th Symposium on Mass Storage Systems and Technologies (MSST’10). IEEE, 1–10.

[205]

SIEMENS. 2023. Siemens 6ES76470AA001YA2. https://www.dacelsolutions.com/upload/dokumanlar/Siemens%206ES76470AA001YA2.pdf

[206]

Siemens. 2022. MindSphere documentation overview. Retrieved from https://siemens.mindsphere.io/en/docs/documentation-overview

[207]

Tanwa Sirisakdiwan and Natawut Nupairoj. 2019. Spark framework for real-time analytic of multiple heterogeneous data streams. In 2nd International Conference on Communication Engineering and Technology (ICCET’19). IEEE, 1–5.

[208]

Emiliano Sisinni, Abusayeed Saifullah, Song Han, Ulf Jennehag, and Mikael Gidlund. 2018. Industrial internet of things: Challenges, opportunities, and directions. IEEE Trans. Industr. Inform. 14, 11 (2018), 4724–4734.

[209]

Inés Sittón-Candanedo, Ricardo S. Alonso, Juan M. Corchado, Sara Rodríguez-González, and Roberto Casado-Vara. 2019. A review of edge computing reference architectures and a new global edge proposal. Fut. Gen. Comput. Syst. 99 (2019), 278–294.

Digital Library

[210]

Eugene Y. Song, Martin Burns, Abhinav Pandey, and Thomas Roth. 2019. IEEE 1451 smart sensor digital twin federation for IoT/CPS Research. In IEEE Sensors Applications Symposium (SAS’19). IEEE, 1–6.

[211]

Eugene Y. Song and Kang Lee. 2008. Understanding IEEE 1451-networked smart transducer interface standard—What is a smart transducer? IEEE Instrum. Measur. Mag. 11, 2 (2008), 11–17.

[212]

Dragan H. Stojanović, Natalija M. Stojanović, Igor Đorđević, and Aleksandra I. Stojnev Ilić. 2019. Sensor data fusion and big mobility data analytics for activity recognition. In 14th International Conference on Advanced Technologies, Systems and Services in Telecommunications (TELSIKS’19). IEEE, 66–69.

[213]

Xing Su, Shan Xue, Fanzhen Liu, Jia Wu, Jian Yang, Chuan Zhou, Wenbin Hu, Cecile Paris, Surya Nepal, Di Jin, Quan Z. Sheng, and Philip S. Yu. 2022. A comprehensive survey on community detection with deep learning. IEEE Trans. Neural Netw. Learn. Syst. (2022), 1–21. https://ieeexplore.ieee.org/document/9732192

[214]

Dawei Sun, Vincent C. S. Lee, and Ye Lu. 2016. An intelligent data fusion framework for structural health monitoring. In IEEE 11th Conference on Industrial Electronics and Applications (ICIEA’16). 49–54.

[215]

Danfeng Sun, Shan Xue, Huifeng Wu, and Jia Wu. 2021. A data stream cleaning system using edge intelligence for smart city industrial environments. IEEE Trans. Industr. Inform. 18, 2 (2021), 1165–1174.

[216]

R. Sundaramurthy and V. Nagarajan. 2016. Design and implementation of reconfigurable virtual instruments using Raspberry Pi core. In International Conference on Communication and Signal Processing (ICCSP’16). 2309–2313.

[217]

Jorg Swetina, Guang Lu, Philip Jacobs, Francois Ennesser, and JaeSeung Song. 2014. Toward a standardized common M2M service layer platform: Introduction to oneM2M. IEEE Wirel. Commun. 21, 3 (2014), 20–26.

[218]

Ioan Szilagyi and Patrice Wira. 2016. Ontologies and semantic web for the internet of things—A survey. In 42nd Annual Conference of the IEEE Industrial Electronics Society. IEEE, 6949–6954.

Digital Library

[219]

Seyede Zahra Tajalli, Mohammad Mardaneh, Elaheh Taherian-Fard, Afshin Izadian, Abdollah Kavousi-Fard, Morteza Dabbaghjamanesh, and Taher Niknam. 2020. DoS-resilient distributed optimal scheduling in a fog supporting IIoT-based smart microgrid. IEEE Trans. Industr. Applic. 56, 3 (2020), 2968–2977.

[220]

Kiyotaka Takahashi, Yuji Ogata, and Youichi Nonaka. 2017. A proposal of unified reference model for smart manufacturing. In 13th IEEE Conference on Automation Science and Engineering (CASE’17). 964–969.

Digital Library

[221]

Jie Tang, Rao Yu, Shaoshan Liu, and Jean-Luc Gaudiot. 2020. A container based edge offloading framework for autonomous driving. IEEE Access 8 (2020), 33713–33726.

[222]

Koen Tange, Michele De Donno, Xenofon Fafoutis, and Nicola Dragoni. 2020. A systematic survey of industrial internet of things security: Requirements and fog computing opportunities. IEEE Commun. Surv. Tutor. 22, 4 (2020), 2489–2520.

[223]

Erdal Tantik and Reiner Anderl. 2017. Integrated data model and structure for the asset administration shell in industrie 4.0. Procedia CIRP 60 (2017), 86–91.

[224]

Amy J. C. Trappey, Charles V. Trappey, Usharani Hareesh Govindarajan, Allen C. Chuang, and John J. Sun. 2017. A review of essential standards and patent landscapes for the internet of things: A key enabler for industry 4.0. Adv. Eng. Inform. 33 (Aug.2017), 208–229.

Digital Library

[225]

D. Ursutiu, C. Samoila, V. Jinga, and F. Altoe. 2016. The future of “hardware–software reconfigurable.” In International Conference on Interactive Collaborative Learning. Springer, 269–275.

[226]

Fredy João Valente, João Paulo Morijo, Kelen Cristiane T. Vivaldini, and Luis Carlos Trevelin. 2019. Fog-based data fusion for heterogeneous IoT sensor networks: A real implementation. In 15th International Conference on Network and Service Management (CNSM’19). IEEE, 1–5.

[227]

Pal Varga, Jozsef Peto, Attila Franko, David Balla, David Haja, Ferenc Janky, Gabor Soos, Daniel Ficzere, Markosz Maliosz, and Laszlo Toka. 2020. 5G support for industrial IoT applications—Challenges, solutions, and research gaps. Sensors 20, 3 (2020), 828.

[228]

Jiafu Wan, Shenglong Tang, Di Li, Muhammad Imran, Chunhua Zhang, Chengliang Liu, and Zhibo Pang. 2018. Reconfigurable smart factory for drug packing in healthcare Industry 4.0. IEEE Trans. Industr. Inform. 15, 1 (2018), 507–516.

[229]

Jiafu Wan, Shenglong Tang, Zhaogang Shu, Di Li, Shiyong Wang, Muhammad Imran, and Athanasios V. Vasilakos. 2016. Software-defined industrial internet of things in the context of industry 4.0. IEEE Sensors J. 16, 20 (2016), 7373–7380.

[230]

Lan Wang, Shinpei Hayashi, and Motoshi Saeki. 2021. Applying class distance to decide similarity on information models for automated data interoperability. Int. J. Softw. Eng. Knowl. Eng. 31, 03 (Mar.2021), 405–434.

[231]

Pan Wang, Feng Ye, and Xuejiao Chen. 2018. A smart home gateway platform for data collection and awareness. IEEE Commun. Mag. 56, 9 (2018), 87–93.

[232]

Shulong Wang, Yibin Hou, Fang Gao, and Xinrong Ji. 2016. A novel IoT access architecture for vehicle monitoring system. In IEEE 3rd World Forum on Internet of Things (WF-IoT’16). 639–642.

[233]

Wendong Wang, Cheng Feng, Bo Zhang, and Hui Gao. 2019. Environmental monitoring based on fog computing paradigm and internet of things. IEEE Access 7 (2019), 127154–127165.

[234]

P. D. Wegener. 2018. German standardization roadmap industrie 4.0 version 3. DIN e 2018 (2018).

[235]

Jiantao Wei, Naiqian Zhang, Ning Wang, Donald Lenhert, Mitchell Neilsen, and Masaaki Mizuno. 2005. Use of the “smart transducer” concept and IEEE 1451 standards in system integration for precision agriculture. Comput. Electron. Agric. 48, 3 (2005), 245–255.

Digital Library

[236]

Alexander Willner, Christian Diedrich, Raéd Ben Younes, Stephan Hohmann, and Andreas Kraft. 2017. Semantic communication between components for smart factories based on oneM2M. In 22nd IEEE International Conference on Emerging Technologies and Factory Automation (ETFA’17). IEEE, 1–8.

Digital Library

[237]

Krzysztof Witkowski. 2017. Internet of things, big data, industry 4.0—Innovative solutions in logistics and supply chains management. Procedia Eng. 182 (2017), 763–769.

[238]

Huifeng Wu, Junjie Hu, Jiexiang Sun, and Danfeng Sun. 2019. Edge computing in an IoT base station system: Reprogramming and real-time tasks. Complexity 2019 (2019). https://www.hindawi.com/journals/complexity/2019/4027638/

Digital Library

[239]

Huifeng Wu, Danfeng Sun, Lan Peng, Yuan Yao, Jia Wu, Quan Z. Sheng, and Yi Yan. 2019. Dynamic edge access system in IoT environment. IEEE Internet Things J. 7, 4 (2019), 2509–2520.

[240]

Huifeng Wu, Yi Yan, Danfeng Sun, and Simon Rene. 2019. A customized real-time compilation for motion control in embedded PLCs. IEEE Trans. Industr. Inform. 15, 2 (2019), 812–821.

[241]

Huifeng Wu, Yi Yan, Danfeng Sun, and Rene Simon. 2019. VCA protocol-based multilevel flexible architecture on embedded PLCs for visual servo control. IEEE Trans. Industr. Electron. 67, 3 (2019), 2450–2459.

[242]

Yulei Wu, Hong-Ning Dai, Haozhe Wang, Zehui Xiong, and Song Guo. 2022. A survey of intelligent network slicing management for industrial IoT: Integrated approaches for smart transportation, smart energy, and smart factory. IEEE Commun. Surv. Tutor. 24, 2 (2022), 1175–1211.

[243]

Jost Wübbeke, Mirjam Meissner, Max J. Zenglein, Jaqueline Ives, and Björn Conrad. 2016. Made in China 2025. Mercator Instit. China Studies. Pap. China 2 (2016), 74.

[244]

Xiangdong Hao, Fei Li, and Xiaoguang Gao. 2015. Construction of information fusion system based on cloud computing. In 4th International Conference on Computer Science and Network Technology (ICCSNT’15). 1461–1465.

[245]

Yonggang Xiao, Yanbing Liu, and Tun Li. 2020. Edge computing and blockchain for quick fake news detection in IoV. Sensors 20, 16 (2020), 4360.

[246]

Xu Xin, Zhang Yan, Hao Yueying, Jiang Yulei, and Geng Mingzhi. 2022. Research of container security reinforcement multi-service APP deployment for new power system on substation. In 4th Asia Energy and Electrical Engineering Symposium (AEEES’22). 945–949.

[247]

Ying Xiong, Yulin Sun, Li Xing, and Ying Huang. 2018. Extend cloud to edge with KubeEdge. In IEEE/ACM Symposium on Edge Computing (SEC’18). 373–377.

[248]

Hansong Xu, Wei Yu, David Griffith, and Nada Golmie. 2018. A survey on industrial internet of things: A cyber-physical systems perspective. IEEE Access 6 (2018), 78238–78259.

[249]

Yang Xu, Ju Ren, Guojun Wang, Cheng Zhang, Jidian Yang, and Yaoxue Zhang. 2019. A blockchain-based nonrepudiation network computing service scheme for industrial IoT. IEEE Trans. Industr. Inform. 15, 6 (2019), 3632–3641.

[250]

Jianghui Yan, Jinping Liu, and Fang-Mei Tseng. 2020. An evaluation system based on the self-organizing system framework of smart cities: A case study of smart transportation systems in China. Technol. Forecast. Social Change 153 (2020), 119371.

[251]

Linfu Yang and Bin Liu. 2019. Temporal data fusion at the edge. In IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS). IEEE, 9–14.

[252]

Lina Yao, Quan Z. Sheng, Xue Li, Tao Gu, Mingkui Tan, Xianzhi Wang, Sen Wang, and Wenjie Ruan. 2017. Compressive representation for device-free activity recognition with passive RFID signal strength. IEEE Trans. Mob. Comput. 17, 2 (2017), 293–306.

Digital Library

[253]

Abbas Yazdinejad, Reza M. Parizi, Ali Dehghantanha, Qi Zhang, and Kim-Kwang Raymond Choo. 2020. An energy-efficient SDN controller architecture for IoT networks with blockchain-based security. IEEE Trans. Serv. Comput. 13, 4 (2020), 625–638.

[254]

Xun Ye and Seung Ho Hong. 2019. Toward industry 4.0 components: Insights into and implementation of asset administration shells. IEEE Industr. Electron. Mag. 13, 1 (Mar.2019), 13–25.

[255]

ChuanTao Yin, Zhang Xiong, Hui Chen, JingYuan Wang, Daven Cooper, and Bertrand David. 2015. A literature survey on smart cities. Sci. China Inf. Sci. 58, 10 (2015), 1–18.

[256]

Matti Yli-Ojanperä, Seppo Sierla, Nikolaos Papakonstantinou, and Valeriy Vyatkin. 2019. Adapting an agile manufacturing concept to the reference architecture model industry 4.0: A survey and case study. J. Industr. Inf. Integ. 15 (Sept.2019), 147–160.

[257]

Xiao Yue, Huiju Wang, Dawei Jin, Mingqiang Li, and Wei Jiang. 2016. Healthcare data gateways: Found healthcare intelligence on blockchain with novel privacy risk control. J. Med. Syst. 40, 10 (2016), 218.

Digital Library

[258]

Matei Zaharia, Mosharaf Chowdhury, Tathagata Das, Ankur Dave, Justin Ma, Murphy McCauly, Michael J. Franklin, Scott Shenker, and Ion Stoica. 2012. Resilient distributed datasets: A fault-tolerant abstraction for in-memory cluster computing. In 9th USENIX Symposium on Networked Systems Design and Implementation (NSDI’12). 15–28.

[259]

František Zezulka, P. Marcon, Zdenek Bradac, Jakub Arm, T. Benesl, and Ivo Vesely. 2018. Communication systems for industry 4.0 and the IIoT. IFAC-PapersOnLine 51, 6 (2018), 150–155.

[260]

Daniel Zhang, Nathan Vance, and Dong Wang. 2019. When social sensing meets edge computing: Vision and challenges. In 28th International Conference on Computer Communication and Networks (ICCCN’19). IEEE, 1–9.

[261]

Lingwen Zhang, Ning Xiao, Wenkao Yang, and Jun Li. 2019. Advanced heterogeneous feature fusion machine learning models and algorithms for improving indoor localization. Sensors 19, 1 (2019), 125.

[262]

Lili Zhang, Yuxiang Xie, Luan Xidao, and Xin Zhang. 2018. Multi-source heterogeneous data fusion. In International Conference on Artificial Intelligence and Big Data (ICAIBD’18). 47–51.

[263]

Qikun Zhang, Yongjiao Li, Ruifang Wang, Lu Liu, Yu-an Tan, and Jingjing Hu. 2021. Data security sharing model based on privacy protection for blockchain-enabled industrial Internet of Things. Int. J. Intell. Syst. 36, 1 (2021), 94–111.

Digital Library

[264]

Yin Zhang, Yongfeng Qian, Di Wu, M. Shamim Hossain, Ahmed Ghoneim, and Min Chen. 2019. Emotion-aware multimedia systems security. IEEE Trans. Multim. 21, 3 (2019), 617–624.

[265]

Zheng Zhang, Liang Huang, Renzhong Tang, Tao Peng, Lihang Guo, and Xingwei Xiang. 2020. Industrial blockchain of things: A solution for trustless industrial data sharing and beyond. In IEEE 16th International Conference on Automation Science and Engineering (CASE’20). 1187–1192.

[266]

Ma Zhaofeng, Wang Xiaochang, Deepak Kumar Jain, Haneef Khan, Gao Hongmin, and Wang Zhen. 2020. A blockchain-based trusted data management scheme in edge computing. IEEE Trans. Industr. Inform. 16, 3 (2020), 2013–2021.

[267]

Pai Zheng, Zhiqian Sang, Ray Y. Zhong, Yongkui Liu, Chao Liu, Khamdi Mubarok, Shiqiang Yu, and Xun Xu. 2018. Smart manufacturing systems for industry 4.0: Conceptual framework, scenarios, and future perspectives. Front. Mechan. Eng. 13, 2 (2018), 137–150.

[268]

Funa Zhou, Po Hu, Shuai Yang, and Chenglin Wen. 2018. A multimodal feature fusion-based deep learning method for online fault diagnosis of rotating machinery. Sensors 18, 10 (2018), 3521.

[269]

Yuqing Zhou and Wei Xue. 2018. A multisensor fusion method for tool condition monitoring in milling. Sensors 18, 11 (2018), 3866.

[270]

Tao Zhu, Sahraoui Dhelim, Zhihao Zhou, Shunkun Yang, and Huansheng Ning. 2017. An architecture for aggregating information from distributed data nodes for industrial internet of things. Comput. Electric. Eng. 58 (2017), 337–349.

Digital Library

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Index Terms

A Comprehensive Survey on Collaborative Data-access Enablers in the IIoT
1. Computer systems organization
  1. Architectures
    1. Distributed architectures
      1. Cloud computing
    2. Other architectures
      1. Data flow architectures
2. Information systems
  1. Data management systems

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cover image ACM Computing Surveys

ACM Computing Surveys Volume 56, Issue 2

February 2024

974 pages

EISSN:1557-7341

DOI:10.1145/3613559

Editor:
Albert Zomaya
University of Sydney, Australia

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Publication History

Published: 15 September 2023

Online AM: 07 August 2023

Accepted: 11 July 2023

Revised: 03 July 2023

Received: 10 May 2022

Published in CSUR Volume 56, Issue 2

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https://doi.org/10.1016/j.compind.2024.104210
Zhu ZGou GWang CZhou HLin CXiong G(2025)User Behavior Forensics on Encrypted Traffic in the Industrial Internet of ThingsAdvances in Digital Forensics XX10.1007/978-3-031-71025-4_7(119-139)Online publication date: 7-Jan-2025
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Humayun MTariq NAlfayad MZakwan MAlwakid GAssiri M(2024)Securing the Internet of Things in Artificial Intelligence Era: A Comprehensive SurveyIEEE Access10.1109/ACCESS.2024.336563412(25469-25490)Online publication date: 2024
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Ceselli ADe Martino GPremoli M(2024)Identification of sensors in smart manufacturing via mutually exclusive multiple time series classificationJournal of Intelligent Manufacturing10.1007/s10845-024-02531-yOnline publication date: 25-Nov-2024
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