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Part of the book series: Wireless Networks ((WN))

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Abstract

With the continuous development of information and communication technology, advanced wireless technologies have been widely used in industrial automation. The wireless communication technology provides a bridge between sensors, controllers, and actuators to enable the flexible and low-cost communication services for sensing and control applications. Industrial network system is the integration of traditional control system and wireless network, which has several advantages over traditional wired control systems, such as the elimination of unnecessary cables, the cost reduction of deployment and maintenance, the flexibility of system expansion and update. Recently, it has been applied in various areas, such as space exploration, environment monitoring, industrial automation, remote diagnostics and troubleshooting, teleoperations, and so on. Despite the appealing advantages of wireless communication, the harsh industrial environment and scarce spectrum resource make it very challenging to meet the high-reliability requirement of information transmission for control. This chapter will discuss the challenges for sensing and control over wireless network.

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References

  1. L. Zhang, H. Gao, O. Kaynak, Network-induced constraints in networked control systems—a survey. IEEE Trans. Ind. Inf. 9(1), 403–416 (2013)

    Article  Google Scholar 

  2. X. Zhang, Q. Han, X. Yu, Survey on recent advances in networked control systems. IEEE Trans. Ind. Inf. 12(5), 1740–1752 (2016)

    Article  Google Scholar 

  3. S. He, H.-S. Shin, S. Xu, A. Tsourdos, Distributed estimation over a low-cost sensor network: a review of state-of-the-art. Inf. Fus. 54, 21–43 (2020)

    Article  Google Scholar 

  4. K.-K.R. Choo, S. Gritzalis, J.H. Park, Cryptographic solutions for industrial internet-of-things: research challenges and opportunities. IEEE Trans. Ind. Inf. 14(8), 3567–3569 (2018)

    Article  Google Scholar 

  5. W. Na, Y. Lee, N.-N. Dao, D.N. Vu, A. Masood, S. Cho, Directional link scheduling for real-time data processing in smart manufacturing system. IEEE Internet Things J. 5(5), 3661–3671 (2018)

    Article  Google Scholar 

  6. J.-Q. Li, F.R. Yu, G. Deng, C. Luo, Z. Ming, Q. Yan, Industrial internet: a survey on the enabling technologies, applications, and challenges. IEEE Commun. Surv. Tutorials 19(3), 1504–1526 (2017)

    Article  Google Scholar 

  7. J. Ding, S. Sun, J. Ma, N. Li, Fusion estimation for multi-sensor networked systems with packet loss compensation. Inf. Fus. 45, 138–149 (2019)

    Article  Google Scholar 

  8. C. Zhu, Y. Xia, L. Yan, M. Fu, Centralised fusion over unreliable networks. Int. J. Control 85(4), 409–418 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  9. Q. Shen, J. Liu, X. Zhou, W. Qin, L. Wang, Q. Wang, Centralized fusion methods for multi-sensor system with bounded disturbances. IEEE Access 7, 141 612–141 626 (2019)

    Google Scholar 

  10. H. Lin, S. Lu, P. Lu, H. Que, P. Sun, Centralized fusion estimation over wireless sensor-actuator networks with unobservable packet dropouts. J. Frankl. Inst. 359(2), 1569–1584 (2022)

    Article  MathSciNet  MATH  Google Scholar 

  11. L. Lyu, C. Chen, J. Yan, F. Lin, C. Hua, X. Guan, State estimation oriented wireless transmission for ubiquitous monitoring in industrial cyber-physical systems. IEEE Trans. Emerg. Top. Comput. 7(1), 187–201 (2016)

    Article  Google Scholar 

  12. B. Chen, G. Hu, W.-A. Zhang, L. Yu, Distributed mixed h2h fusion estimation with limited communication capacity. IEEE Trans. Autom. Control 61(3), 805–810 (2016)

    Article  MATH  Google Scholar 

  13. B. Chen, G. Hu, D.W. Ho, L. Yu, A new approach to linear/nonlinear distributed fusion estimation problem. IEEE Trans. Autom. Control 64(3), 1301–1308 (2018)

    Article  MathSciNet  MATH  Google Scholar 

  14. B. Noack, J. Sijs, M. Reinhardt, U.D. Hanebeck, Decentralized data fusion with inverse covariance intersection. Automatica 79, 35–41 (2017)

    Article  MathSciNet  MATH  Google Scholar 

  15. T. Tian, S. Sun, Distributed fusion estimation for multisensor multirate systems with packet dropout compensations and correlated noises. IEEE Trans. Syst. Man Cybern. Syst. Hum. 51(9), 5762–5772 (2019)

    Article  Google Scholar 

  16. Z. Xing, Y. Xia, Distributed federated Kalman filter fusion over multi-sensor unreliable networked systems. IEEE Trans. Circuits Syst. Regul. Pap. 63(10), 1714–1725 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  17. B. Sinopoli, L. Schenato, M. Franceschetti, K. Poolla, M.I. Jordan, S.S. Sastry, Kalman filtering with intermittent observations. IEEE Trans. Autom. Control 49(9), 1453–1464 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  18. L. Schenato, Optimal estimation in networked control systems subject to random delay and packet drop. IEEE Trans. Autom. Control 53(5), 1311–1317 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  19. I. Penarrocha, R. Sanchis, P. Albertos, Estimation in multisensor networked systems with scarce measurements and time varying delays. Syst. Control Lett. 61(4), 555–562 (2012)

    Article  MATH  Google Scholar 

  20. B. Chen, W.-A. Zhang, L. Yu, Distributed fusion estimation with missing measurements, random transmission delays and packet dropouts. IEEE Trans. Autom. Control 59(7), 1961–1967 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  21. A.S. Leong, S. Dey, D.E. Quevedo, Sensor scheduling in variance based event triggered estimation with packet drops. IEEE Trans. Autom. Control 62(4), 1880–1895 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  22. Z. Liu, Y. Luo, Y. Zhu, State estimation for linear dynamic system with multiple-step random delays using high-order Markov chain. IEEE Access 8, 76 218–76 227 (2020)

    Google Scholar 

  23. J. Li, G. AlRegib, Distributed estimation in energy-constrained wireless sensor networks. IEEE Trans. Signal Process. 57(10), 3746–3758 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  24. C. Chen, L. Lyu, S. Zhu, X. Guan, On-demand transmission for edge-assisted remote control in industrial network systems. IEEE Trans. Ind. Inf. 16(7), 4842–4854 (2019)

    Article  Google Scholar 

  25. S. Al-Areqi, D. Görges, S. Liu, Event-based networked control and scheduling codesign with guaranteed performance. Automatica 57, 128–134 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  26. Y.-R. Tsai, C.-J. Chang, Cooperative information aggregation for distributed estimation in wireless sensor networks. IEEE Trans. Signal Process. 59(8), 3876–3888 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  27. A.W. Al-Dabbagh, T. Chen, Design considerations for wireless networked control systems. IEEE Trans. Ind. Electron. 63(9), 5547–5557 (2016)

    Article  Google Scholar 

  28. Y. He, Q.-G. Wang, An improved ILMI method for static output feedback control with application to multivariable PID control. IEEE Trans. Autom. Control 51(10), 1678–1683 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  29. J.-S. Wang, G.-H. Yang, Data-driven output-feedback fault-tolerant compensation control for digital PID control systems with unknown dynamics. IEEE Trans. Ind. Electron. 63(11), 7029–7039 (2016)

    Article  Google Scholar 

  30. E. T. Ceran, D. Gündüz, A. György, A reinforcement learning approach to age of information in multi-user networks with HARQ. IEEE J. Sel. Areas Commun. 39(5), 1412–1426 (2021)

    Article  Google Scholar 

  31. M. Levorato, U. Mitra, M. Zorzi, Cognitive interference management in retransmission-based wireless networks. IEEE Trans. Inf. Theory 58(5), 3023–3046 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  32. J. Wu, Q.-S. Jia, K.H. Johansson, L. Shi, Event-based sensor data scheduling: trade-off between communication rate and estimation quality. IEEE Trans. Autom. Control 58(4), 1041–1046 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  33. L. Li, D. Yu, Y. Xia, H. Yang, Remote nonlinear state estimation with stochastic event-triggered sensor schedule. IEEE Trans. Cybern. 49(3), 734–745 (2018)

    Article  Google Scholar 

  34. S. Weerakkody, Y. Mo, B. Sinopoli, D. Han, L. Shi, Multi-sensor scheduling for state estimation with event-based, stochastic triggers. IEEE Trans. Autom. Control 61(9), 2695–2701 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  35. H. Ren, R. Lu, J. Xiong, Y. Xu, Optimal estimation for discrete-time linear system with communication constraints and measurement quantization. IEEE Trans. Syst. Man Cybern. Syst. Hum. 50(5), 1932–1942 (2018)

    Article  Google Scholar 

  36. S. Al-Areqi, D. Görges, S. Liu, Event-based control and scheduling codesign: stochastic and robust approaches. IEEE Trans. Autom. Control 60(5), 1291–1303 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  37. A. Heydari, Optimal codesign of control input and triggering instants for networked control systems using adaptive dynamic programming. IEEE Trans. Ind. Electron. 66(1), 482–490 (2018)

    Article  Google Scholar 

  38. L. Lyu, C. Chen, N. Cheng, S. Zhu, X. Guan, X. Shen, Noma-assisted on-demand transmissions for monitoring applications in industrial IoT networks. IEEE Trans. Veh. Technol. 69(10), 12 264–12 276 (2020)

    Google Scholar 

  39. W. Ejaz, M. Naeem, S. Zeadally, On-demand sensing and wireless power transfer for self-sustainable industrial internet of things networks. IEEE Trans. Ind. Inf. 17(10), 7075–7084 (2020)

    Article  Google Scholar 

  40. C. Li, W. Chen, K.B. Letaief, Joint scheduling of proactive caching and on-demand transmission traffics over shared spectrum. IEEE Trans. Commun. 69(12), 8319–8334 (2021)

    Article  Google Scholar 

  41. X. Wang, C. Chen, J. He, S. Zhu, X. Guan, AoI-aware control and communication co-design for industrial IoT systems. IEEE Internet Things J. 8(10), 8464–8473 (2020)

    Article  Google Scholar 

  42. B. Chang, G. Zhao, L. Zhang, M.A. Imran, Z. Chen, L. Li, Dynamic communication QoS design for real-time wireless control systems. IEEE Sens. J. 20(6), 3005–3015 (2019)

    Article  Google Scholar 

  43. A. Saifullah, C. Wu, P.B. Tiwari, Y. Xu, Y. Fu, C. Lu, Y. Chen, Near optimal rate selection for wireless control systems. ACM Trans. Embed. Comput. Syst. 13(4s), 1–25 (2014)

    Article  Google Scholar 

  44. B. Chen, L. Yu, W.-A. Zhang, A. Liu, Robust information fusion estimator for multiple delay-tolerant sensors with different failure rates. IEEE Trans. Circuits Syst. Regul. Pap. 60(2), 401–414 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  45. H.P. Breivold, K. Sandström, Internet of things for industrial automation–challenges and technical solutions, in 2015 IEEE International Conference on Data Science and Data Intensive Systems (IEEE, Piscataway, 2015), pp. 532–539

    Google Scholar 

  46. Q. Tang, F.R. Yu, R. Xie, A. Boukerche, T. Huang, Y. Liu, Internet of intelligence: a survey on the enabling technologies, applications, and challenges. IEEE Commun. Surv. Tutorials. 24(3), 1394–1434 (2022)

    Article  Google Scholar 

  47. C. Lu, A. Saifullah, B. Li, M. Sha, H. Gonzalez, D. Gunatilaka, C. Wu, L. Nie, Y. Chen, Real-time wireless sensor-actuator networks for industrial cyber-physical systems. Proc. IEEE 104(5), 1013–1024 (2015)

    Article  Google Scholar 

  48. X. Cao, P. Cheng, J. Chen, S.S. Ge, Y. Cheng, Y. Sun, Cognitive radio based state estimation in cyber-physical systems. IEEE J. Sel. Areas Commun. 32(3), 489–502 (2014)

    Article  Google Scholar 

  49. N.B. Khalifa, V. Angilella, M. Assaad, M. Debbah, Low-complexity channel allocation scheme for URLLC traffic. IEEE Trans. Commun. 69(1), 194–206 (2020)

    Article  Google Scholar 

  50. W.R. Ghanem, V. Jamali, Y. Sun, R. Schober, Resource allocation for multi-user downlink MISO OFDMA-URLLC systems. IEEE Trans. Commun. 68(11), 7184–7200 (2020)

    Article  Google Scholar 

  51. H. Gong, R. Li, J. An, W. Chen, K. Li, Scheduling algorithms of flat semi-dormant multicontrollers for a cyber-physical system. IEEE Trans. Ind. Inf. 13(4), 1665–1680 (2017)

    Article  Google Scholar 

  52. F. Lin, W. Dai, W. Li, Z. Xu, L. Yuan, A framework of priority-aware packet transmission scheduling in cluster-based industrial wireless sensor networks. IEEE Trans. Ind. Inf. 16(8), 5596–5606 (2019)

    Article  Google Scholar 

  53. T. Hegazy, M. Hefeeda, Industrial automation as a cloud service. IEEE Trans. Parallel Distrib. Syst. 26(10), 2750–2763 (2014)

    Article  Google Scholar 

  54. Y. Sun, H. Luo, S.K. Das, A trust-based framework for fault-tolerant data aggregation in wireless multimedia sensor networks. IEEE Trans. Dependable Secure Comput. 9(6), 785–797 (2012)

    Article  Google Scholar 

  55. C.-F. Liu, M. Bennis, M. Debbah, H.V. Poor, Dynamic task offloading and resource allocation for ultra-reliable low-latency edge computing. IEEE Trans. Commun. 67(6), 4132–4150 (2019)

    Article  Google Scholar 

  56. Y. Mao, J. Zhang, S. Song, K.B. Letaief, Stochastic joint radio and computational resource management for multi-user mobile-edge computing systems. IEEE Trans. Wirel. Commun. 16(9), 5994–6009 (2017)

    Article  Google Scholar 

  57. M.H. Mamduhi, D. Maity, S. Hirche, J.S. Baras, K.H. Johansson, Delay-sensitive joint optimal control and resource management in multiloop networked control systems. IEEE Trans. Control Netw. Syst. 8(3), 1093–1106 (2021)

    Article  MathSciNet  Google Scholar 

  58. M.H. Mamduhi, A. Molin, D. Tolić, S. Hirche, Error-dependent data scheduling in resource-aware multi-loop networked control systems. Automatica 81, 209–216 (2017)

    Article  MathSciNet  MATH  Google Scholar 

  59. Y. Sadi, S. Coleri Ergen, Energy and delay constrained maximum adaptive schedule for wireless networked control systems. IEEE Trans. Wirel. Commun. 14(7), 3738–3751 (2015)

    Article  Google Scholar 

  60. S. Hu, W. Chen, Joint lossy compression and power allocation in low latency wireless communications for IIoT: a cross-layer approach. IEEE Trans. Commun. 69(8), 5106–5120 (2021)

    Article  Google Scholar 

  61. M. Stoyanova, Y. Nikoloudakis, S. Panagiotakis, E. Pallis, E.K. Markakis, A survey on the internet of things (IoT) forensics: challenges, approaches, and open issues. IEEE Commun. Surv. Tutorials 22(2), 1191–1221 (2020)

    Article  Google Scholar 

  62. F. Khan, M.A. Jan, A. ur Rehman, S. Mastorakis, M. Alazab, P. Watters, A secured and intelligent communication scheme for IIoT-enabled pervasive edge computing. IEEE Trans. Ind. Inf. 17(7), 5128–5137 (2020)

    Google Scholar 

  63. C. Gehrmann, M. Gunnarsson, A digital twin based industrial automation and control system security architecture. IEEE Trans. Ind. Inf. 16(1), 669–680 (2019)

    Article  Google Scholar 

  64. M.M. Sandhu, S. Khalifa, R. Jurdak, M. Portmann, Task scheduling for energy-harvesting-based IoT: a survey and critical analysis. IEEE Internet Things J. 8(18), 13 825–13 848 (2021)

    Google Scholar 

  65. H. Azarhava, J.M. Niya, Energy efficient resource allocation in wireless energy harvesting sensor networks. IEEE Wirel. Commun. Lett. 9(7), 1000–1003 (2020)

    Google Scholar 

  66. M.M. Vasconcelos, M. Gagrani, A. Nayyar, U. Mitra, Optimal scheduling strategy for networked estimation with energy harvesting. IEEE Trans. Control Netw. Syst. 7(4), 1723–1735 (2020)

    Article  MathSciNet  MATH  Google Scholar 

  67. L. Lei, Y. Kuang, X.S. Shen, K. Yang, J. Qiao, Z. Zhong, Optimal reliability in energy harvesting industrial wireless sensor networks. IEEE Trans. Wirel. Commun. 15(8), 5399–5413 (2016)

    Article  Google Scholar 

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Lyu, L., Guan, X., Cheng, N., Shen, X.S. (2023). Introduction. In: Advanced Wireless Technologies for Industrial Network Systems. Wireless Networks. Springer, Cham. https://doi.org/10.1007/978-3-031-26963-9_1

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  • DOI: https://doi.org/10.1007/978-3-031-26963-9_1

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