Abstract
Ubiquitous power Internet of Things (IoT) is a smart service system oriented to all aspects of the power system, and has the characteristics of universal interconnection, human-computer interaction, comprehensive state perception, efficient information processing, and other convenient and flexible applications. It has become a hot topic in the field of IoT. We summarize some existing research work on the IoT and edge computing framework. Because it is difficult to meet the requirements of ubiquitous power IoT for edge computing in terms of real time, security, reliability, and business function adaptation using the general edge computing framework software, we propose a trusted edge computing framework, named “EdgeKeeper,” adapting to the ubiquitous power IoT. Several key technologies such as security and trust, quality of service guarantee, application management, and cloud-edge collaboration are desired to meet the needs of the edge computing framework. Experiments comprehensively evaluate EdgeKeeper from the aspects of function, performance, and security. Comparison results show that EdgeKeeper is the most suitable edge computing framework for the electricity IoT. Finally, future directions for research are proposed.
摘要
泛在电力物联网是围绕电力系统各环节, 实现各环节万物互联、 人机交互, 具有状态全面感知、 信息高效处理、 应用便捷灵活特征的智慧服务系统, 已成为物联网领域研究的一个热点. 本文总结了物联网和边缘计算框架方面一些已有的研究工作. 由于通用边缘计算框架软件在实时性、 安全性、 可靠性和业务功能适配等方面难以满足泛在电力物联网对边缘计算的相关要求, 本文设计了一种适应于泛在电力物联网的可信边缘计算框架——EdgeKeeper, 并给出安全可信、 实时性QoS保障、 应用管理以及云边协同实现的关键技术方法. 实验章节从功能、 性能、 安全性等方面对EdgeKeeper进行全面评估, 通过对比说明EdgeKeeper是最适应泛在电力物联网的边缘计算框架. 最后, 展望了未来研究方向.
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References
Ahmed R, Zaheer Z, Li R, et al., 2018. Harpocrates: giving out your secrets and keeping them too. IEEE/ACM Symp on Edge Computing, p.103–114. https://doi.org/10.1109/SEC.2018.00015
Ai Y, Peng M, Zhang KC, 2018. Edge computing technologies for Internet of Things: a primer. Dig Commun Netw, 4(2):77–86. https://doi.org/10.1016/j.dcan.2017.07.001
Aral A, Brandic I, 2018. Dependency mining for service resilience at the edge. IEEE/ACM Symp on Edge Computing, p.228–242. https://doi.org/10.1109/SEC.2018.00024
Boutaud F, Ehlig PN, 1991. Series Maxium/Minimum Function Computing Devices, Systems and Methods. US Patent 5 072 418, USA.
Cai YM, Feng SY, Du HW, et al., 2019. Novel edge-ware adaptive data processing method for the ubiquitous electric power Internet of Things. High Volt Eng, 45(6): 1715–1722 (in Chinese). https://doi.org/10.13336/j.1003-6520.hve.20190604005
Chao MY, Yang C, Zeng YK, et al., 2018. F-MStorm: feedback-based online distributed mobile stream processing. IEEE/ACM Symp on Edge Computing, p.273–285. https://doi.org/10.1109/SEC.2018.00027
Chen XL, Wan S, Zhu YF, et al., 2019. Analysis of distributed power distribution fault processing based on edge computing. Electromech Inform, (17):32–33 (in Chinese). https://doi.org/10.19514/j.cnki.cn32-1628/tm.2019.17.018
Edge Computing Consortium, 2018. Edge Computing Reference Architecture 3.0. http://www.ecconsortium.org/Uploads/file/20190225/1551059767474697.pdf [Accessed on Sept. 12, 2019].
Feng ZQ, George S, Harkes J, et al., 2018. Edge-based discovery of training data for machine learning. IEEE/ACM Symp on Edge Computing, p.145–158. https://doi.org/10.1109/SEC.2018.00018
Fultz D, Ramanujan AS, Ibitayo KY, 2010. Rules Engine Architecture and Implementation. US Patent 7 853 786, USA.
Hu YC, Patel M, Sabella D, et al., 2015. Mobile Edge Computing—A Key Technology Towards 5G. ETSI White Paper No. 11, ETSI, France.
Jang SY, Lee Y, Shin B, et al., 2018. Application-aware IoT camera virtualization for video analytics edge computing. IEEE/ACM Symp on Edge Computing, p.132–144. https://doi.org/10.1109/SEC.2018.00017
Li JR, Li XY, Gao YL, et al., 2018. Review on data forwarding model in Internet of Things. J Softw, 29(1):196–224 (in Chinese). https://doi.org/10.13328/j.cnki.jos.005373
Li SN, Luo GJ, 2014. The overview of technologies and applications for industrial IOT. Telecommun Netw Technol, (3):26–31 (in Chinese).
Liang JY, Liu B, Liu F, 2019. The present situation of open source platforms for edge computing. ZTE Technol, 25(3):8–14 (in Chinese). https://doi.org/10.12142/ZTETJ.201903002
Liu RL, Liu HT, Xia SF, et al., 2019. Internet of Things technology application and prospects in distribution transformer service area management. High Volt Eng, 45(6): 1707–1714 (in Chinese). https://doi.org/10.13336/j.1003-6520.hve.20190604004
Luan TH, Gao LX, Li Z, et al., 2015. Fog computing: focusing on mobile users at the edge. https://arxiv.org/abs/1502.01815
Mach P, Becvar Z, 2017. Mobile edge computing: a survey on architecture and computation offloading. IEEE Commun Surv Tutor, 19(3):1628–1656. https://doi.org/10.1109/COMST.2017.2682318
Maheshwari S, Raychaudhuri D, Seskar I, et al., 2018. Scalability and performance evaluation of edge cloud systems for latency constrained applications. IEEE/ACM Symp on Edge Computing, p.286–299. https://doi.org/10.1109/SEC.2018.00028
Mao YY, You CS, Zhang J, et al., 2017. A survey on mobile edge computing: the communication perspective. IEEE Commun Surv Tutor, 19(4):2322–2358. https://doi.org/10.1109/COMST.2017.2745201
Satyanarayanan M, 2017. The emergence of edge computing. Computer, 50(1):30–39. https://doi.org/10.1109/MC.2017.9
Saxena H, Salem K, 2015. EdgeX: edge replication for web applications. 8th Int Conf on Cloud Computing, p.1041–1044. https://doi.org/10.1109/CLOUD.2015.147
Sha LT, Xiao P, Chen W, et al., 2018. Leakage perception method for backdoor privacy in industry Internet of Things environment. J Softw, 29(7):1863–1879 (in Chinese). https://doi.org/10.13328/j.cnki.jos.005356
Shen SB, Yang Z, 2015. Architecture of Internet of Things and its standardization. J Nanjing Univ Post Telecommun (Nat Sci), 35(1):1–18 (in Chinese). https://doi.org/10.14132/j.cnki.1673-5439.2015.01.001
Shi WS, Dustdar S, 2016. The promise of edge computing. Computer, 49(5):78–81. https://doi.org/10.1109/MC.2016.145
Shi WS, Cao J, Zhang Q, et al., 2016. Edge computing: vision and challenges. IEEE Int Things J, 3(5):637–646. https://doi.org/10.1109/JIOT.2016.2579198
Shi WS, Sun H, Cao J, et al., 2017. Edge computing—an emerging computing model for the Internet of Everything era. J Comput Res Dev, 54(5):907–924 (in Chinese). https://doi.org/10.7544/issn1000-1239.2017.20160941
Wang H, Li Y, Mi MR, et al., 2013. Secure data fusion method based on supervisory mechanism for industrial Internet of Things. Chin J Sci Instrum, 34(4):817–824 (in Chinese). https://doi.org/10.3969/j.issn.0254-3087.2013.04.016
Xu H, 2019. Implementation of edge calculation in motor monitoring system. Electron Technol Soft Eng, 90–192 (in Chinese).
Yang WY, Liu W, Huang H, et al., 2016. Research on power private micro kernel-based secure operating system technology. Electron Power Inform Commun Technol, 14(11):22–27 (in Chinese). https://doi.org/10.16543/j.2095-641x.electric.power.ict.2016.11.004
Yang WY, Liu W, Wei XS, et al., 2019. Micro-kernel OS architecture and its ecosystem construction for ubiquitous electric power IoT. IEEE Int Conf on Energy Internet, p.179–184. https://doi.org/10.1109/ICEI.2019.00038
Yang YM, Song ZH, 2015. Research on industrial Internet of Things security and protection technology. Int Things Technol, 5(3):64–66, 69 (in Chinese). https://doi.org/10.3969/j.issn.2095-1302.2015.03.028
Zhang JX, Wu XL, Yang Z, et al., 2018. Research and application of industrial data acquisition based on industrial Internet of Things. Telecommun Sci, 34(10): 124–129 (in Chinese). https://doi.org/10.11959/j.issn.1000-0801.2018271
Zhou Q, 2018. GE Industrial Internet five years. Chin Ind Inform Technol, (7):32–38. https://doi.org/10.19609/j.cnki.cn10-1299/f.2018.07.005
Zuo PL, Zhou Q, Dai X, 2019. Analysis of industrial Internet of Things technology in smart factory. Style Sci Technol, (8):88 (in Chinese). https://doi.org/10.19392/j.cnki.1671-7341.201908072
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Contributions
Weiyong YANG designed the EdgeKeeper framework. Wei LIU analyzed the EdgeKeeper framework and designed the experimental scheme. Xingshen WEI and Huang HAO analyzed the experimental data. Weiyong YANG and Kangle YANG drafted the manuscript. Zixin GUO analyzed the experimental scheme and provided materials and analysis tools. Longyun QI studied the EdgeKeeper framework in depth and proposed a modification plan which is of constructive significance. Kangle YANG participated in the experiment and revised and finalized the paper.
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Weiyong YANG, Wei LIU, Xingshen WEI, Zixin GUO, Kangle YANG, Hao HUANG, and Longyun QI declare that they have no conflict of interest.
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Project supported by the State Grid Corporation Science and Technology Project, China
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Yang, W., Liu, W., Wei, X. et al. EdgeKeeper: a trusted edge computing framework for ubiquitous power Internet of Things. Front Inform Technol Electron Eng 22, 374–399 (2021). https://doi.org/10.1631/FITEE.1900636
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DOI: https://doi.org/10.1631/FITEE.1900636
Key words
- Internet of Things
- Ubiquitous power Internet of Things
- Edge computing
- Trusted computing
- Network security