Skip to main content
Log in

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

  • Published:
The Journal of Supercomputing Aims and scope Submit manuscript

Abstract

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.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14

Similar content being viewed by others

References

  1. Vermesan O, Friess P (eds) (2014) Internet of Things—from research and innovation to market deployment. River Publishers, Aalborg

    Google Scholar 

  2. Giusto D, Iera A, Morabito G, Atzori L (eds) (2010) The Internet of Things. Springer, New York

    Google Scholar 

  3. Xu L, He W, Li S (2014) Internet of Things in industries: a survey. IEEE Trans Ind Inf 10(4):2233–2248

    Article  Google Scholar 

  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):1750011-1–1750011-22

    Google Scholar 

  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):3–34

    Google Scholar 

  6. Ngu HCV, Huh J-H (2017) B+-tree construction on massive data with Hadoop. Cluster Comput 1–11. https://doi.org/10.1007/s10586-017-1183-y

  7. Moon SY, Park JH (2016) Efficient Hardware-Based Code Convertor of a Quantum Computer. Journal of Convergence 7:1–9

    Google Scholar 

  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 9:2309

    Article  Google Scholar 

  9. Yin Y, Zeng Y, Chen X, Fan Y (2016) The Internet of Things in healthcare: an overview. J Ind Inf Integr 1:3–13

    Google Scholar 

  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 3:8–19

    Google Scholar 

  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 2:19–29

    Google Scholar 

  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):2177–2186

    Article  Google Scholar 

  13. Hwang S, Yu D (2012) Remote monitoring and controlling system based on ZigBee networks. Int J Softw Eng Appl SERSC 6(3):35–42

    Google Scholar 

  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 13:1152

    Article  Google Scholar 

  15. Huh J-H (2017) PLC-based design of monitoring system for ICT-integrated vertical fish farm. Human-centric Comput Inf Sci 7(1):1–19

    Article  MathSciNet  Google Scholar 

  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 1–425

    Google Scholar 

  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):348–359

    Google Scholar 

  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):1862–1877

    Article  Google Scholar 

  19. Banafa A (2017) Why IoT needs AI. https://www.bbvaopenmind.com/en/why-iot-needs-ai/. Accessed 17 May 2018

  20. Sinha PK (1997) Distributed operating systems: concepts and design. IEEE Computer Society, pp 282–292

  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 96–106

  22. Gupta A (2016) Time in the IoT. Workshop on synchronization and timing systems (WSTS)

  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 139–149

  24. Mills DL (2003) A brief history of NTP time: memoirs of an Internet timekeeper. ACM SIGCOMM Comput Commun Rev 33(2):9–21

    Article  MathSciNet  Google Scholar 

  25. Lombardi M (2018) Computer time synchronization, Time and Frequency Division, National Institute of Standards and Technology (NIST). https://tf.nist.gov/service/pdf/computertime.pdf. Accessed 9 Jan 2018

  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, USA

  27. Edison JC (2018) Measurement, control and communication using IEEE 1588. Springer, New York

    Google Scholar 

  28. Karl H, Willig A (2005) Time synchronization in protocols and architectures for wireless sensor networks. Wiley, West Sussex, pp 201–229

    Book  Google Scholar 

  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 2016

  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):10–16

    Article  Google Scholar 

  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):2241–2250

    Article  Google Scholar 

  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):29–39

    Google Scholar 

  33. Hassan QF (ed) (2018) Internet of Things A to Z technologies and applications. IEEE Press, Wiley, New Jersey

    Google Scholar 

  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):1–14

    Google Scholar 

  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 2017

  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 2017

  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):161–175

    Article  Google Scholar 

  38. Time Considerations. https://github.com/MicrosoftArchive/iot-journey/blob/master/docs/09-time-considerations.md. Accessed 11 Jan 2018

  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 382–383

  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: 5905

  41. Coordinated Universal Time (UTC) https://www.bipm.org/cc/CCTF/Allowed/18/CCTF_09-32_noteUTC.pdf. Accessed 22 Jan 2018

  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 1

Download references

Acknowledgements

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).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Soyoung Hwang.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Hwang, S. A network clock model for time awareness in the Internet of things and artificial intelligence applications. J Supercomput 75, 4309–4328 (2019). https://doi.org/10.1007/s11227-019-02774-0

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11227-019-02774-0

Keywords

Navigation