Skip to main content

Advanced Communications in Cyber-Physical Systems

  • Chapter
  • First Online:
Big Data Analytics for Cyber-Physical Systems

Abstract

The recent technological developments offer us a new generation of systems known as cyber-physical systems (CPSs). The emergence of CPSs introduces specialized networking and communication strategy, information technology, integrating them with physical world which enables the advancement of a new vision for the social facilities. A CPS is the integration of computation, communication, control, learning, and reasoning with physical processes. CPSs cannot be considered as conventional real-time systems or embedded systems. There are several features that exist in CPSs which make it different from other systems such as dynamically reconfigurable, fully automation, auto-assembly, and integration

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 149.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 199.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 199.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    A perfect modeling for such architectures is known to be infeasible [61].

References

  1. T. Sanislav, L. Miclea, Cyber-physical systems-concept, challenges and research areas. J. Control Eng. Appl. Inf. 14(2), 28–33 (2012)

    Google Scholar 

  2. S. Ali, S.B. Qaisar, H. Saeed, M.F. Khan, M. Naeem, A. Anpalagan, Network challenges for cyber physical systems with tiny wireless devices: a case study on reliable pipeline condition monitoring. Sensors 15(4), 7172–7205 (2015)

    Google Scholar 

  3. N. Mohamed, J. Al-Jaroodi, S. Lazarova-Molnar, I. Jawhar, Middleware to support cyber-physical systems, in 2016 IEEE 35th International Performance Computing and Communications Conference (IPCCC) (IEEE, Piscataway, 2016), pp. 1–3

    Google Scholar 

  4. J. Chen, X. Cao, P. Cheng, Y. Xiao, Y. Sun, Distributed collaborative control for industrial automation with wireless sensor and actuator networks. IEEE Trans. Ind. Electron. 57(12), 4219–4230 (2010)

    Google Scholar 

  5. A. Nayak, I. Stojmenovic, Wireless Sensor and Actuator Networks: Algorithms and Protocols for Scalable Coordination and Data Communication (Wiley, Hoboken, 2010)

    MATH  Google Scholar 

  6. F. Xia, L. Ma, J. Dong, Y. Sun, Network QoS management in cyber-physical systems, in International Conference on Embedded Software and Systems Symposia, 2008. ICESS Symposia’08 (IEEE, Piscataway, 2008), pp. 302–307

    Google Scholar 

  7. F. Xia, A. Vinel, R. Gao, L. Wang, T. Qiu, Evaluating IEEE 802.15. 4 for cyber-physical systems. EURASIP J. Wirel. Commun. Netw. 2011(1), 596397 (2011)

    Google Scholar 

  8. L.S. Committee et al., Part 15.4: Wireless Medium Access Control (mac) and Physical Layer (phy) Specifications for Low-rate Wireless Personal Area Networks (lr-wpans) (IEEE Computer Society, Washington, 2003)

    Google Scholar 

  9. J. Zheng, M. Lee, A comprehensive performance study of IEEE 802.15. 4. Sensor Network Operations, 1–14 (2004)

    Google Scholar 

  10. E. Callaway, P. Gorday, L. Hester, J.A. Gutierrez, M. Naeve, B. Heile, V. Bahl, Home networking with IEEE 802.15. 4: a developing standard for low-rate wireless personal area networks. IEEE Commun. Mag. 40(8), 70–77 (2002)

    Google Scholar 

  11. MAC, IEEE 802.15.4 (2003). https://en.wikipedia.org/wiki/IEEE_802.15.4. Accessed 20 Nov 2017

  12. B.P. Crow, I. Widjaja, L. Kim, P.T. Sakai, IEEE 802.11 wireless local area networks. IEEE Commun. Mag. 35(9), 116–126 (1997)

    Google Scholar 

  13. J.W. Hui, D.E. Culler, IP is dead, long live IP for wireless sensor networks, in Proceedings of the 6th ACM Conference on Embedded Network Sensor Systems (ACM, New York, 2008), pp. 15–28

    Google Scholar 

  14. S. Deering, R. Hinden, RFC2460: Internet Protocol, Version 6 (IPv6) Specification (RFC Editor, USA, 1998)

    Google Scholar 

  15. H. Li, L. Lai, H.V. Poor, Multicast routing for decentralized control of cyber physical systems with an application in smart grid. IEEE J. Sel. Areas Commun. 30(6), 1097–1107 (2012)

    Google Scholar 

  16. C. Langbort, V. Gupta, Minimal interconnection topology in distributed control design. SIAM J. Control Optim. 48(1), 397–413 (2009)

    MathSciNet  MATH  Google Scholar 

  17. A. Bemporad, M. Morari, V. Dua, E.N. Pistikopoulos, The explicit linear quadratic regulator for constrained systems. Automatica 38(1), 3–20 (2002)

    MathSciNet  MATH  Google Scholar 

  18. M.R. Haque, M. Naznin, Monitoring cost reduction in sensor networks using proximity queries. JNW 6(1), 4–11 (2011) [Online]. Available https://doi.org/10.4304/jnw.6.1.4-11

  19. N. Majadi, M. Naznin, T. Ahmed, Energy efficient local search based target localization in an UWSN, in 12th IEEE International Conference on Wireless and Mobile Computing, Networking and Communications, WiMob 2016, New York, NY, October 17–19, 2016 (2016), pp. 1–8

    Google Scholar 

  20. M.S. Rahman, M. Naznin, T. Ahmed, Efficient routing in a sensor network using collaborative ants, in Advances in Swarm Intelligence, 7th International Conference, ICSI 2016, Bali, June 25–30, 2016, Proceedings, Part II (2016), pp. 333–340

    Google Scholar 

  21. W. Kang, K. Kapitanova, S.H. Son, Rdds: a real-time data distribution service for cyber-physical systems. IEEE Trans. Ind. Inf. 8(2), 393–405 (2012)

    Google Scholar 

  22. S. Oh, J.-H. Kim, G. Fox, Real-time performance analysis for publish/subscribe systems. Futur. Gener. Comput. Syst. 26(3), 318–323 (2010)

    Google Scholar 

  23. H. Ahmadi, T.F. Abdelzaher, I. Gupta, Congestion control for spatio-temporal data in cyber-physical systems, in Proceedings of the 1st ACM/IEEE International Conference on Cyber-Physical Systems (ACM, New York 2010), pp. 89–98

    Google Scholar 

  24. A.A. Al Islam, S.I. Alam, V. Raghunathan, S. Bagchi, Multi-armed bandit congestion control in multi-hop infrastructure wireless mesh networks, in 2012 IEEE 20th International Symposium on Modeling, Analysis & Simulation of Computer and Telecommunication Systems (MASCOTS) (IEEE, Piscataway, 2012), pp. 31–40

    Google Scholar 

  25. A.A. Al Islam, V. Raghunathan, End-to-end congestion control in wireless mesh networks using a neural network, in Wireless Communications and Networking Conference (WCNC), 2011 IEEE (IEEE, Piscataway, 2011), pp. 677–682

    Google Scholar 

  26. I.F. Akyildiz, X. Wang, W. Wang, Wireless mesh networks: a survey. Comput. Netw. 47(4), 445–487 (2005)

    MATH  Google Scholar 

  27. J.J. Hopfield, Neural networks and physical systems with emergent collective computational abilities. Proc. Natl. Acad. Sci. 79(8), 2554–2558 (1982)

    MathSciNet  MATH  Google Scholar 

  28. A.A. Al Islam, V. Raghunathan, iTCP: an intelligent TCP with neural network based end-to-end congestion control for ad-hoc multi-hop wireless mesh networks. Wirel. Netw. 21(2), 581–610 (2015)

    Google Scholar 

  29. P. Karn, C. Partridge, Improving round-trip time estimates in reliable transport protocols. ACM SIGCOMM Comput. Commun. Rev. 17(5), 2–7 (1987)

    Google Scholar 

  30. A.A. Al Islam, V. Raghunathan, QRTT: Stateful round trip time estimation for wireless embedded systems using Q-learning. IEEE Embed. Syst. Lett. 4(4), 102–105 (2012)

    Google Scholar 

  31. P. Dayan, C. Watkins, Q-learning. Mach. Learn. 8(3), 279–292 (1992)

    MATH  Google Scholar 

  32. A.A. Al Islam, V. Raghunathan, Evaluating Q-learning based stateful round trip time estimation over high-data-rate wireless sensor networks, in 2013 16th International Conference on Computer and Information Technology (ICCIT) (IEEE, Piscataway, 2014), pp. 136–141

    Google Scholar 

  33. K. Jacobsson, H. Hjalmarsson, N. Möller, K.H. Johansson, Estimation of RTT and bandwidth for congestion control applications in communication networks, in IEEE CDC, Paradise Island (IEEE, Piscataway, 2004)

    Google Scholar 

  34. A.C. Harvey, Forecasting, Structural Time Series Models and the Kalman Filter (Cambridge University Press, Cambridge, 1990)

    MATH  Google Scholar 

  35. F. Gustafsson, F. Gustafsson, Adaptive Filtering and Change Detection, vol. 1 (Wiley, New York, 2000)

    MATH  Google Scholar 

  36. A. Kesselman, Y. Mansour, Optimizing TCP retransmission timeout, in Networking-ICN 2005 (2005), pp. 133–140

    Google Scholar 

  37. L. Militano, G. Araniti, M. Condoluci, I. Farris, A. Iera, Device-to-device communications for 5g internet of things, in IOT, EAI (2015)

    Google Scholar 

  38. G. Camarillo, M.-A. Garcia-Martin, The 3G IP Multimedia Subsystem (IMS): Merging the Internet and the Cellular Worlds (Wiley, Chichester, 2007)

    Google Scholar 

  39. V. Karagiannis, P. Chatzimisios, F. Vazquez-Gallego, J. Alonso-Zarate, A survey on application layer protocols for the internet of things. Trans. IoT Cloud Comput. 3(1), 11–17 (2015)

    Google Scholar 

  40. L. Fourati, L. Kamoun, Performance Analysis of IEEE 802.15.4/Zigbee Standard Under Real Time Constraints. International Journal of Computer Networks & Communications 315 (2011). https://doi.org/10.5121/ijcnc.2011.3517

  41. Z. Shelby, C. Bormann, 6LoWPAN: The Wireless Embedded Internet, vol. 43 (Wiley, Chichester, 2011)

    Google Scholar 

  42. J. Gozalvez, New 3gpp standard for iot [mobile radio]. IEEE Veh. Technol. Mag. 11(1), 14–20 (2016)

    Google Scholar 

  43. Etsi 3gpp (1998). http://www.etsi.org/about/what-we-do/global-collaboration/3gpp. Accessed 20 Nov 2017

  44. AMQP, Advanced message queuing protocol (2003). http://en.wikipedia.org/wiki/AdvancedMessageQueuingProtocol. Accessed 20 Nov 2017

  45. S. Lee, H. Kim, D.-k. Hong, H. Ju, Correlation analysis of MQTT loss and delay according to QoS level, in 2013 International Conference on Information Networking (ICOIN) (IEEE, Piscataway, 2013), pp. 714–717

    Google Scholar 

  46. F.T. Johnsen, T.H. Bloebaum, M. Avlesen, S. Spjelkavik, B. Vik, Evaluation of transport protocols for web services, in Military Communications and Information Systems Conference (MCC), 2013 (IEEE, Piscataway, 2013), pp. 1–6

    Google Scholar 

  47. D. Thangavel, X. Ma, A. Valera, H.-X. Tan, C.K.-Y. Tan, Performance evaluation of MQTT and CoAP via a common middleware, in 2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP) (IEEE, Piscataway, 2014), pp. 1–6

    Google Scholar 

  48. IoT, Platform (2017). https://www.devteam.space/blog/10-best-internet-of-things-iot-cloud-platforms/. Accessed 20 Nov 2017

  49. F. Bonomi, R. Milito, P. Natarajan, J. Zhu, Fog computing: a platform for internet of things and analytics, in Big Data and Internet of Things: A Roadmap for Smart Environments (Springer, Cham, 2014), pp. 169–186

    Google Scholar 

  50. A.A. Al Islam, M.J. Islam, N. Nurain, V. Raghunathan, Channel assignment techniques for multi-radio wireless mesh networks: a survey. IEEE Commun. Surv. Tutorials 18(2), 988–1017 (2016)

    Google Scholar 

  51. P. Gupta, P.R. Kumar, The capacity of wireless networks. IEEE Trans. Inf. Theory 46(2), 388–404 (2000)

    MathSciNet  MATH  Google Scholar 

  52. H. Dinh, Y.-A. Kim, S. Lee, M. Shin, B. Wang, SDP-based approach for channel assignment in multi-radio wireless networks. Networks 13, 15 (2007)

    Google Scholar 

  53. M. Shin, S. Lee, Y.-a. Kim, Distributed channel assignment for multi-radio wireless networks, in 2006 IEEE International Conference on Mobile Adhoc and Sensor Systems (MASS) (IEEE, Piscataway, 2006), pp. 417–426

    Google Scholar 

  54. Y. Ding, K. Pongaliur, L. Xiao, Channel allocation and routing in hybrid multichannel multiradio wireless mesh networks. IEEE Trans. Mobile Comput. 12(2), 206–218 (2013)

    Google Scholar 

  55. K.N. Ramachandran, E.M. Belding-Royer, K.C. Almeroth, M.M. Buddhikot, Interference-aware channel assignment in multi-radio wireless mesh networks, in Infocom, vol. 6 (2006), pp. 1–12

    Google Scholar 

  56. J. Gummeson, D. Ganesan, M.D. Corner, P. Shenoy, An adaptive link layer for range diversity in multi-radio mobile sensor networks, in INFOCOM 2009, IEEE (IEEE, Piscataway, 2009), pp. 154–162

    Google Scholar 

  57. R.S. Sutton, A.G. Barto, Introduction to Reinforcement Learning, 2nd edn. (MIT Press, Cambridge, MA, USA, 2018). isbn:978-0-262-03924-6

    MATH  Google Scholar 

  58. P. Kyasanur, N.H. Vaidya, Routing and link-layer protocols for multi-channel multi-interface ad hoc wireless networks. ACM SIGMOBILE Mobile Comput. Commun. Rev. 10(1), 31–43 (2006)

    Google Scholar 

  59. A.A. Al Islam, M.S. Hossain, V. Raghunathan, Y.C. Hu, Backpacking: deployment of heterogeneous radios in high data rate sensor networks, in 2011 Proceedings of 20th International Conference on Computer Communications and Networks (ICCCN) (IEEE, Piscataway, 2011), pp. 1–8

    Google Scholar 

  60. A.A. Al Islam, M.S. Hossain, V. Raghunathan, Y.C. Hu, Backpacking: energy-efficient deployment of heterogeneous radios in multi-radio high-data-rate wireless sensor networks. IEEE Access 2, 1281–1306 (2014)

    Google Scholar 

  61. A. Islam, V. Raghunathan, Assessing the viability of cross-layer modeling for asynchronous, multi-hop, ad-hoc wireless mesh networks, in Proceedings of the 9th ACM International Symposium on Mobility Management and Wireless Access (ACM, New York, 2011), pp. 147–152

    Google Scholar 

  62. A.A. Al Islam, V. Raghunathan, SiAc: simultaneous activation of heterogeneous radios in high data rate multi-hop wireless networks. Wirel. Netw. 21(7), 2425–2452 (2015)

    Google Scholar 

  63. A.A. Al Islam, V. Raghunathan, Symco: symbiotic coexistence of single-hop and multi-hop transmissions in next-generation wireless mesh networks. Wirel. Netw. 21(7), 2115–2136 (2015)

    Google Scholar 

  64. K. Li, Q. Liu, F. Wang, X. Xie, Joint optimal congestion control and channel assignment for multi-radio multi-channel wireless networks in cyber-physical systems, in Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing, 2009. UIC-ATC’09 (IEEE, Piscataway, 2009), pp. 456–460

    Google Scholar 

  65. X. Lin, N.B. Shroff, R. Srikant, A tutorial on cross-layer optimization in wireless networks. IEEE J. Sel. Areas Commun. 24(8), 1452–1463 (2006)

    Google Scholar 

  66. J. White, S. Clarke, C. Groba, B. Dougherty, C. Thompson, D.C. Schmidt, R&d challenges and solutions for mobile cyber-physical applications and supporting internet services. J. Internet Serv. Appl. 1(1), 45–56 (2010)

    Google Scholar 

  67. M. Conti, S.K. Das, C. Bisdikian, M. Kumar, L.M. Ni, A. Passarella, G. Roussos, G. Tröster, G. Tsudik, F. Zambonelli, Looking ahead in pervasive computing: challenges and opportunities in the era of cyber–physical convergence. Pervasive Mob. Comput. 8(1), 2–21 (2012)

    Google Scholar 

  68. X. Hu, T.H. Chu, H.C. Chan, V.C. Leung, Vita: a crowdsensing-oriented mobile cyber-physical system. IEEE Trans. Emerg. Top. Comput. 1(1), 148–165 (2013)

    Google Scholar 

  69. R. Baheti, H. Gill, Cyber-physical systems, in The Impact of Control Technology, vol. 12 (2011), pp. 161–166

    Google Scholar 

  70. R.R. Rajkumar, I. Lee, L. Sha, J. Stankovic, Cyber-physical systems: the next computing revolution, in Proceedings of the 47th Design Automation Conference (ACM, New York, 2010), pp. 731–736

    Google Scholar 

  71. M. Seyedzadegan, M. Othman, B.M. Ali, S. Subramaniam, Wireless mesh networks: WMN overview, WMN architecture, in International Conference on Communication Engineering and Networks IPCSIT, vol. 19 (2011), p. 2

    Google Scholar 

  72. F.-J. Wu, Y.-F. Kao, Y.-C. Tseng, From wireless sensor networks towards cyber physical systems. Pervasive Mob. Comput. 7(4), 397–413 (2011)

    Google Scholar 

  73. L. Han, S. Potter, G. Beckett, G. Pringle, S. Welch, S.-H. Koo, G. Wickler, A. Usmani, J.L. Torero, A. Tate, FireGrid: an e-infrastructure for next-generation emergency response support. J. Parallel Distrib. Comput. 70(11), 1128–1141 (2010)

    Google Scholar 

  74. M.S. Rahman, M. Naznin, Shortening the tour-length of a mobile data collector in the WSN by the method of linear shortcut, in Web Technologies and Applications – 15th Asia-Pacific Web Conference, APWeb 2013, Sydney, April 4–6, 2013. Proceedings (2013), pp. 674–685

    Google Scholar 

  75. G. Xing, T. Wang, Z. Xie, W. Jia, Rendezvous planning in wireless sensor networks with mobile elements. IEEE Trans. Mob. Comput. 7(12), 1430–1443 (2008)

    Google Scholar 

  76. K. Namuduri, Y. Wan, M. Gomathisankaran, R. Pendse, Airborne network: a cyber-physical system perspective, in Proceedings of the first ACM MobiHoc Workshop on Airborne Networks and Communications (ACM, New York, 2012), pp. 55–60

    Google Scholar 

  77. K. Sampigethaya, R. Poovendran, Aviation cyber–physical systems: foundations for future aircraft and air transport. Proc. IEEE 101(8), 1834–1855 (2013)

    Google Scholar 

  78. G. Ravikiran, S. Singh, Influence of mobility models on the performance of routing protocols in ad-hoc wireless networks, in 2004 IEEE 59th Vehicular Technology Conference, 2004. VTC 2004-Spring, vol. 4 (IEEE, Piscataway, 2004), pp. 2185–2189

    Google Scholar 

  79. P. Nain, D. Towsley, B. Liu, Z. Liu, Properties of random direction models, in INFOCOM 2005. 24th Annual Joint Conference of the IEEE Computer and Communications Societies. Proceedings IEEE, vol. 3 (IEEE, Piscataway, 2005), pp. 1897–1907

    Google Scholar 

  80. C. Bettstetter, H. Hartenstein, X. Pérez-Costa, Stochastic properties of the random waypoint mobility model. Wirel. Netw. 10(5), 555–567 (2004)

    Google Scholar 

  81. T. Yang, H. Feng, C. Yang, Z. Sun, R. Deng, Resource allocation in cooperative cognitive radio networks towards maritime cyber physical systems, in 2016 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE) (IEEE, Piscataway, 2016), pp. 1–4

    Google Scholar 

  82. C. news, Maritime WiMAX network launched in Singapore (2008). http://www.cellular-news.com/story/29749.php. Accessed 24 June 2017

  83. P.S. Jirapure, A.V. Vidhate, Survey and analysis of handoff decision strategies for heterogeneous mobile wireless networks. Int. J. 4(4), 703–713 (2014)

    Google Scholar 

  84. N. Nurain, T. Akter, H. Zannat, M.M. Akter, A.A. Al Islam, M.H. Kabir, General-purpose multi-objective vertical hand-off mechanism exploiting network dynamics, in 2015 IEEE 11th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob) (IEEE, Piscataway, 2015), pp. 825–832

    Google Scholar 

  85. D. Hong, S.S. Rappaport, Traffic model and performance analysis for cellular mobile radio telephone systems with prioritized and nonprioritized handoff procedures. IEEE Trans. Veh. Technol. 35(3), 77–92 (1986)

    Google Scholar 

  86. A. Ahmed, L.M. Boulahia, D. Gaiti, Enabling vertical handover decisions in heterogeneous wireless networks: a state-of-the-art and a classification. IEEE Commun. Surv. Tutorials 16(2), 776–811 (2014)

    Google Scholar 

  87. Y. Zhou, B. Ai, Handover schemes and algorithms of high-speed mobile environment: a survey. Comput. Commun. 47, 1–15 (2014)

    Google Scholar 

  88. K. Benson, C. Fracchia, G. Wang, Q. Zhu, S. Almomen, J. Cohn, L. D’arcy, D. Hoffman, M. Makai, J. Stamatakis et al., Scale: safe community awareness and alerting leveraging the internet of things. IEEE Commun. Mag. 53(12), 27–34 (2015)

    Google Scholar 

  89. P. Kolodzy et al., Next generation communications: Kickoff meeting, in Proc. DARPA, vol. 10 (2001)

    Google Scholar 

  90. G. Staple, K. Werbach, The end of spectrum scarcity [spectrum allocation and utilization]. IEEE Spect. 41(3), 48–52 (2004)

    Google Scholar 

  91. C.S. Hyder, A.A. Al Islam, L. Xiao, E. Torng, Interference aware reliable cooperative cognitive networks for real-time applications. IEEE Trans. Cogn. Commun. Netw. 2(1), 53–67 (2016)

    Google Scholar 

  92. C.S. Hyder, A.A. Al Islam, L. Xiao, Enhancing reliability of real-time traffic via cooperative scheduling in cognitive radio networks, in 2015 IEEE 23rd International Symposium on Quality of Service (IWQoS) (IEEE, Piscataway, 2015), pp. 249–254

    Google Scholar 

  93. S. Haykin, Cognitive radio: brain-empowered wireless communications. IEEE J. Sel. Areas Commun. 23(2), 201–220 (2005)

    Google Scholar 

  94. M. Dillinger, K. Madani, N. Alonistioti, Software Defined Radio: Architectures, Systems and Functions (Wiley, Chichester, 2005)

    Google Scholar 

  95. J. Mitola, The software radio architecture. IEEE Communications Magazine 33(5), 26–38 (1995)

    Google Scholar 

  96. D.B. Rawat, C. Bajracharya, Vehicular cyber physical systems (2016)

    Google Scholar 

  97. D.B. Rawat, S. Reddy, N. Sharma, B.B. Bista, S. Shetty, Cloud-assisted GPS-driven dynamic spectrum access in cognitive radio vehicular networks for transportation cyber physical systems, in 2015 IEEE Wireless Communications and Networking Conference (WCNC) (IEEE, Piscataway, 2015), pp. 1942–1947

    Google Scholar 

  98. J. Mitola, Cognitive radio for flexible mobile multimedia communications, in 1999 IEEE International Workshop on Mobile Multimedia Communications, 1999 (MoMuC’99) (IEEE, Piscataway, 1999), pp. 3–10

    Google Scholar 

  99. I.F. Akyildiz, W.-Y. Lee, M.C. Vuran, S. Mohanty, Next generation/dynamic spectrum access/cognitive radio wireless networks: a survey. Comput. Netw. 50(13), 2127–2159 (2006)

    MATH  Google Scholar 

  100. F. Riaz, M.A. Niazi, Spectrum mobility in cognitive radio-based vehicular cyber physical networks: a fuzzy emotion-inspired scheme, in 2015 13th International Conference on Frontiers of Information Technology (FIT) (IEEE, Piscataway, 2015), pp. 264–270

    Google Scholar 

  101. D. Jia, K. Lu, J. Wang, X. Zhang, X. Shen, A survey on platoon-based vehicular cyber-physical systems. IEEE Commun. Surv. Tutorials 18(1), 263–284 (2016)

    Google Scholar 

  102. R. Hall, C. Chin, Vehicle sorting for platoon formation: impacts on highway entry and throughput. Transp. Res. C Emerg. Technol. 13(5), 405–420 (2005)

    Google Scholar 

  103. P. Kavathekar, Y. Chen, Vehicle platooning: a brief survey and categorization, in ASME 2011 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference (American Society of Mechanical Engineers, New York, 2011), pp. 829–845

    Google Scholar 

  104. K. Zhu, D. Niyato, P. Wang, E. Hossain, D. In Kim, Mobility and handoff management in vehicular networks: a survey. Wirel. Commun. Mob. Comput. 11(4), 459–476 (2011)

    Google Scholar 

  105. G.I. Tsiropoulos, O.A. Dobre, M.H. Ahmed, K.E. Baddour, Radio resource allocation techniques for efficient spectrum access in cognitive radio networks. IEEE Commun. Surv. Tutorials 18(1), 824–847 (2016)

    Google Scholar 

  106. E.Z. Tragos, S. Zeadally, A.G. Fragkiadakis, V.A. Siris, Spectrum assignment in cognitive radio networks: a comprehensive survey. IEEE Commun. Surv. Tutorials 15(3), 1108–1135 (2013)

    Google Scholar 

  107. I.F. Akyildiz, W.-Y. Lee, M.C. Vuran, S. Mohanty, A survey on spectrum management in cognitive radio networks. IEEE Commun. Mag. 46(4), 40–48 (2008)

    Google Scholar 

  108. D.W.K. Ng, E.S. Lo, R. Schober, Multiobjective resource allocation for secure communication in cognitive radio networks with wireless information and power transfer. IEEE Trans. Veh. Technol. 65(5), 3166–3184 (2016)

    Google Scholar 

  109. L. Lyu, C. Chen, Y. Li, F. Lin, L. Liu, X. Guan, Cognitive radio enabled transmission for state estimation in industrial cyber-physical systems, in 2015 IEEE Global Communications Conference (GLOBECOM) (IEEE, Piscataway, 2015), pp. 1–6

    Google Scholar 

  110. 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)

    Google Scholar 

  111. Y.-C. Liang, Y. Zeng, E.C. Peh, A.T. Hoang, Sensing-throughput tradeoff for cognitive radio networks. IEEE Trans. Wirel. Commun. 7(4), 1326–1337 (2008)

    Google Scholar 

  112. T.A. Khan, C.S. Hyder, A.A. Al Islam, Towards exploiting a synergy between cognitive and multi-radio networking, in 2015 IEEE 11th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob) (IEEE, Piscataway, 2015), pp. 370–377

    Google Scholar 

  113. P. Mell, T. Grance, Draft NIST working definition of cloud computing-v15, 21. Aug 2009, vol. 2, pp. 123–135 (2009)

    Google Scholar 

  114. T. Dillon, C. Wu, E. Chang, Cloud computing: issues and challenges, in 2010 24th IEEE International Conference on Advanced Information Networking and Applications (AINA) (IEEE, Piscataway, 2010), pp. 27–33

    Google Scholar 

  115. C. Zou, J. Wan, M. Chen, D. Li, Simulation modeling of cyber-physical systems exemplified by unmanned vehicles with WSNs navigation, in Embedded and Multimedia Computing Technology and Service (Springer, Dordrecht, 2012), pp. 269–275

    Google Scholar 

  116. X. Li, C. Qiao, X. Yu, A. Wagh, R. Sudhaakar, S. Addepalli, Toward effective service scheduling for human drivers in vehicular cyber-physical systems. IEEE Trans. Parallel Distrib. Syst. 23(9), 1775–1789 (2012)

    Google Scholar 

  117. J. Wan, M. Chen, F. Xia, L. Di, K. Zhou, From machine-to-machine communications towards cyber-physical systems. Comput. Sci. Inf. Syst. 10(3), 1105–1128 (2013)

    Google Scholar 

  118. J. Wan, D. Zhang, Y. Sun, K. Lin, C. Zou, H. Cai, VCMIA: a novel architecture for integrating vehicular cyber-physical systems and mobile cloud computing. Mobile Netw. Appl. 19(2), 153–160 (2014)

    Google Scholar 

  119. J. Wan, D. Zhang, S. Zhao, L. Yang, J. Lloret, Context-aware vehicular cyber-physical systems with cloud support: architecture, challenges, and solutions. IEEE Commun. Mag. 52(8), 106–113 (2014)

    Google Scholar 

  120. A. Rakotonirainy, Design of context-aware systems for vehicle using complex systems paradigms (2005)

    Google Scholar 

  121. S. Al-Sultan, A.H. Al-Bayatti, H. Zedan, Context-aware driver behavior detection system in intelligent transportation systems. IEEE Trans. Veh. Technol. 62(9), 4264–4275 (2013)

    Google Scholar 

  122. J. Santa, A.F. Gomez-Skarmeta, Sharing context-aware road and safety information. IEEE Pervasive Comput. 8(3), 58–65 (2009)

    Google Scholar 

  123. K.K. Venkatasubramanian, S. Nabar, S.K. Gupta, R. Poovendran, Cyber physical security solutions for pervasive health monitoring systems, in User-Driven Healthcare: Concepts, Methodologies, Tools, and Applications (IGI Global, Hershey, 2013), pp. 447–465

    Google Scholar 

  124. M. Bouet, A.L. Dos Santos, RFID tags: positioning principles and localization techniques, in Wireless Days, 2008. WD’08. 1st IFIP (IEEE, Piscataway, 2008), pp. 1–5

    Google Scholar 

  125. Y. Khan, A.E. Ostfeld, C.M. Lochner, A. Pierre, A.C. Arias, Monitoring of vital signs with flexible and wearable medical devices. Adv. Mater. 28, 4373–4395 (2016)

    Google Scholar 

  126. T. Shah, A. Yavari, S.S. Karan Mitra, P.P. Jayaraman, F. Rabhi, R. Ranjan, Remote health care cyber-physical system: quality of service (QoS) challenges and opportunities. IET Cyber-Phys. Syst. Theory Appl. 1(1), 40–48 (2016)

    Google Scholar 

  127. M. Chen, Y. Ma, Y. Li, D. Wu, Y. Zhang, C.-H. Youn, Wearable 2.0: enabling human-cloud integration in next generation healthcare systems. IEEE Commun. Mag. 55(1), 54–61 (2017)

    Google Scholar 

  128. M.S. Hossain, M.A. Rahman, G. Muhammad, Cyber–physical cloud-oriented multi-sensory smart home framework for elderly people: an energy efficiency perspective. J. Parallel Distrib. Comput. 103, 11–21 (2017)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Khan, T.A., Tairin, S., Naznin, M., Bhuyian, M., Al Islam, A. . .A. (2020). Advanced Communications in Cyber-Physical Systems. In: Hu, S., Yu, B. (eds) Big Data Analytics for Cyber-Physical Systems. Springer, Cham. https://doi.org/10.1007/978-3-030-43494-6_3

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-43494-6_3

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-43493-9

  • Online ISBN: 978-3-030-43494-6

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics