A network clock model for time awareness in the Internet of things and artificial intelligence applications

  • Soyoung HwangEmail author


The Internet has immeasurably changed all aspects of life, from work to social relationships. The Internet of things (IoT) promises to add a new dimension by making possible not only communications with and among objects but also, thereby, the vision of anytime, anywhere, anything communications. The IoT allows sensing or control of objects remotely across network infrastructures. Its application, thus, is very extensive. The principal IoT applications are infrastructure management, smart manufacturing, smart agriculture, energy management, environment monitoring, building and home automation, metropolitan-scale deployments, medicine and health care, and smart transportation. Many IoT applications entail the collection and also forwarding of event data. To realize the IoT’s potential, combining it with artificial intelligence (AI) technologies is necessary. The IoT collects data, which AI processes so as to make sense of it. In order to trigger an action in the IoT and in AI applications, knowledge of the time at which an event occurs can be very useful. Time information, in fact, is an essential infrastructural component of any distributed system. Indeed, in IoT and AI applications, time information and time synchronization are among the most fundamental components. The IoT and AI thus require a scheme for data’s combination with time. This paper proposes a network clock model that enables the sharing, by IoT and AI devices, of a consistent notion of time. A proposed network clock model is implemented and evaluated in an actual test platform of MICAz-compatible sensor nodes operated in TinyOS 2.0 and Arduino Uno (R3) in order to verify its feasibility. The experimental results indicate that, for any application, IoT devices are capable of maintaining standard time and serving a standard timestamp.


Clock model Internet of things (IoT) Time awareness Artificial intelligence (AI) System time 



The first draft of this paper was presented at the 12th KIPS International Conference on Ubiquitous Information Technologies and Applications (CUTE 2017), Taichung, Taiwan, December 18–20, 2017 [42]. This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (NRF-2017R1A2B4009167).


  1. 1.
    Vermesan O, Friess P (eds) (2014) Internet of Things—from research and innovation to market deployment. River Publishers, AalborgGoogle Scholar
  2. 2.
    Giusto D, Iera A, Morabito G, Atzori L (eds) (2010) The Internet of Things. Springer, New YorkGoogle Scholar
  3. 3.
    Xu L, He W, Li S (2014) Internet of Things in industries: a survey. IEEE Trans Ind Inf 10(4):2233–2248CrossRefGoogle Scholar
  4. 4.
    Kim J (2017) A review of cyber-physical system research relevant to the emerging IT trends: industry 4.0, IoT, big data, and cloud computing. J Ind Integr Manag 2(3):1750011-1–1750011-22Google Scholar
  5. 5.
    Liu F, Tan C, Lim E, Choi B (2017) Traversing knowledge networks: an algorithmic historiography of extant literature on the Internet of Things (IoT). J Manag Anal 4(1):3–34Google Scholar
  6. 6.
    Ngu HCV, Huh J-H (2017) B+-tree construction on massive data with Hadoop. Cluster Comput 1–11.
  7. 7.
    Moon SY, Park JH (2016) Efficient Hardware-Based Code Convertor of a Quantum Computer. Journal of Convergence 7:1–9Google Scholar
  8. 8.
    Chui K-T, Alhalabi W, Pang SS-H, Ordóñez de Pablos P, Liu R-W, Zhao M (2017) Disease diagnosis in smart healthcare: innovation. Technol Appl Sustain 9:2309CrossRefGoogle Scholar
  9. 9.
    Yin Y, Zeng Y, Chen X, Fan Y (2016) The Internet of Things in healthcare: an overview. J Ind Inf Integr 1:3–13Google Scholar
  10. 10.
    Zhai C, Zou Z, Chen Q, Xu L, Zheng L, Tenhunen H (2016) Delay-aware and reliability-aware contention-free MF-TDMA protocol for automated RFID monitoring in industrial IoT. J Ind Inf Integr 3:8–19Google Scholar
  11. 11.
    Mao J, Zhou Q, Sarmiento M, Chen J, Wang P, Jonsson F, Xu L, Zheng L, Zou Z (2016) A hybrid reader transceiver design for industrial Internet of Things. J Ind Inf Integr 2:19–29Google Scholar
  12. 12.
    Li S, Xu L, Wang X (2013) Compressed sensing signal and data acquisition in wireless sensor networks and Internet of Things. IEEE Trans Ind Inf 9(4):2177–2186CrossRefGoogle Scholar
  13. 13.
    Hwang S, Yu D (2012) Remote monitoring and controlling system based on ZigBee networks. Int J Softw Eng Appl SERSC 6(3):35–42Google Scholar
  14. 14.
    Marques G, Pitarma R (2016) An indoor monitoring system for ambient assisted living based on Internet of Things architecture. Int J Environ Res Public Health 13:1152CrossRefGoogle Scholar
  15. 15.
    Huh J-H (2017) PLC-based design of monitoring system for ICT-integrated vertical fish farm. Human-centric Comput Inf Sci 7(1):1–19MathSciNetCrossRefGoogle Scholar
  16. 16.
    Huh J-H (2017) Smart grid test bed using OPNET and power line communication. Advances in Computer and Electrical Engineering, IGI Global, Pennsylvania, pp 1–425Google Scholar
  17. 17.
    Kim S, Hwang K (2017) Design of real-time CAN framework based on plug and play functionality. J Inf Process Syst KIPS 13(2):348–359Google Scholar
  18. 18.
    Huh J-H, Otgonchimeg S, Seo K (2016) Advanced metering infrastructure design and test bed experiment using intelligent agents: focusing on the PLC network base technology for smart grid system. J Supercomput 72(5):1862–1877CrossRefGoogle Scholar
  19. 19.
    Banafa A (2017) Why IoT needs AI. Accessed 17 May 2018
  20. 20.
    Sinha PK (1997) Distributed operating systems: concepts and design. IEEE Computer Society, pp 282–292Google Scholar
  21. 21.
    Hwang S, Yu D, Li K (2004) Embedded system design for network time synchronization. In: Proceedings of the International Conference on Embedded and Ubiquitous Computing (EUC 2004), Aizu-Wakamatsu City, Japan, 25–27 August 2004, pp 96–106Google Scholar
  22. 22.
    Gupta A (2016) Time in the IoT. Workshop on synchronization and timing systems (WSTS)Google Scholar
  23. 23.
    PalChaudhuri S, Saha RK, Johnson DB (2004) Adaptive clock synchronization in sensor networks. In: Proceedings of the ACM International Conference on Embedded Networked Sensor Systems, pp 139–149Google Scholar
  24. 24.
    Mills DL (2003) A brief history of NTP time: memoirs of an Internet timekeeper. ACM SIGCOMM Comput Commun Rev 33(2):9–21CrossRefGoogle Scholar
  25. 25.
    Lombardi M (2018) Computer time synchronization, Time and Frequency Division, National Institute of Standards and Technology (NIST). Accessed 9 Jan 2018
  26. 26.
    IEEE P1588™ D2.2 Draft Standard for a Precision Clock Synchronization Protocol for Networked Measurement and Control Systems (2008) The Institute of Electrical and Electronics Engineers (IEEE), Inc. New York 10016-5997, USAGoogle Scholar
  27. 27.
    Edison JC (2018) Measurement, control and communication using IEEE 1588. Springer, New YorkGoogle Scholar
  28. 28.
    Karl H, Willig A (2005) Time synchronization in protocols and architectures for wireless sensor networks. Wiley, West Sussex, pp 201–229CrossRefGoogle Scholar
  29. 29.
    Guo X, Mohammad M, Saha S, Chan MC, Gilbert S, Leong D (2016) PSync: visible light-based time synchronization for Internet of Things (IoT). In: Proceedings of the 35th Annual IEEE International Conference on Computer Communications (IEEE INFOCOM 2016), San Francisco, CA, USA, 10–14 April 2016Google Scholar
  30. 30.
    Son S, Kim N, Lee B, Cho CH, Chong JW (2016) A time synchronization technique for coap-based home automation systems. IEEE Trans Consum Electron 62(1):10–16CrossRefGoogle Scholar
  31. 31.
    Elsts A, Fafoutis X, Duquennoy S, Oikonomou G, Piechocki R, Craddock I (2018) Temperature-resilient time synchronization for the Internet of Things. IEEE Trans Ind Inf 14(5):2241–2250CrossRefGoogle Scholar
  32. 32.
    Jeong D-G, Song D (2017) Characteristics of IoT-Artificial Intelligence technologies and their related industry trend. Korea Inst Inf Technol Mag 15(2):29–39Google Scholar
  33. 33.
    Hassan QF (ed) (2018) Internet of Things A to Z technologies and applications. IEEE Press, Wiley, New JerseyGoogle Scholar
  34. 34.
    Chen F, Deng P, Wan J, Zhang D, Vasilakos AV, Rong X (2015) Data Mining for the Internet of Things: literature review and challenges. Int J Distrib Sens Netw 11(8):1–14Google Scholar
  35. 35.
    Meidan Y, Bohadana M, Shabtai A, Guarnizo JD, Ochoa M, Tippenhauer NO, Elovici Y (2017) ProfilIoT: a machine learning approach for IoT device identification based on network traffic analysis. In: Proceedings of the symposium on applied computing (ACM SAC 2017), Marrakech, Morocco, 03–07 April 2017Google Scholar
  36. 36.
    Shanthamallu US, Spanias A, Tepedelenlioglu C, Stanley M (2017) A brief survey of machine learning methods and their sensor and IoT applications. In: Proceedings of the 8th International Conference on Information, Intelligence, Systems & Applications (IISA), Larnaca, Cyprus, 27–30 August 2017Google Scholar
  37. 37.
    Mahdavinejad MS, Rezvan M, Barekatain M, Adibi P, Barnaghi P, Sheth AP (2018) Machine learning for internet of things data analysis: a survey. Digit Commun Netw 4(3):161–175CrossRefGoogle Scholar
  38. 38.
  39. 39.
    Hwang S, Joo S-S (2009) Global time service in wireless sensor networks. In: Proceedings of the 9th international symposium on communication and information technology, pp 382–383Google Scholar
  40. 40.
    Mills D, Martin J, Burbank J, Kasch W (2010) Network time protocol version 4: protocol and algorithms specification, Internet Engineering Task Force (IETF) Request for Comments: 5905Google Scholar
  41. 41.
    Coordinated Universal Time (UTC) Accessed 22 Jan 2018
  42. 42.
    Hwang S, et al (2017) A network clock model for Internet of Things. In: Proceedings of the 12th KIPS International Conference on Ubiquitous Information Technologies and Applications (CUTE 2017), Taichung, Taiwan, 18–20 December 2017, p 1Google Scholar

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© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of SoftwareCatholic University of PusanBusanRepublic of Korea

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