An Adaptive MAC Layer Energy-Saving Algorithm for ZigBee-Enabled IoT Networks

  • Yaxuan ZhangEmail author
  • Kun Yang
  • Hui Chen
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 1122)


Energy conservation has become a major bottleneck for wide deployment of Internet of Things (IoT) technologies. This paper presents energy consumption analysis of ZigBee-enabled IoT networks, and shows the primary energy consumption in a node from a practical aspect. Based on the analysis and experimental measurement, this paper proposes an adaptive MAC layer energy-saving algorithm. This algorithm can adaptively configure the MAC layer in each node based on real-time network traffic conditions. The aim is to minimize the power consumption of each node achieving a longer lifetime and better quality of service. In addition, a software and hardware experimental platform has been built up to verify the reliability and effectiveness of the algorithm. The experimental results show that the adaptive MAC layer energy-saving algorithm is effective and efficient in minimizing node energy consumption.


Internet of Things (IoT) ZigBee MAC layer Energy-saving Adaptive algorithm 



The work in this paper was partly supported by National Natural Science Foundation of China (NSFC) projects (61572389 and 61620106011), and Zhongshan City Team Project (No. 180809162197874).


  1. 1.
    Atzori, L., Iera, A., Morabito, G.: The internet of things: a survey. Comput. Netw. 54(15), 2787–2805 (2010)CrossRefGoogle Scholar
  2. 2.
    Al-Fuqaha, A., Guizani, M., Mohammadi, M., Aledhari, M., Ayyash, M.: Internet of Things: a survey on enabling technologies, protocols, and applications. IEEE Commun. Surv. Tutor. 17(4), 2347–2376 (2015)CrossRefGoogle Scholar
  3. 3.
    Karalis, A., Joannopoulos, J.D., Soljačić, M.: Efficient wireless non-radiative midrange energy transfer. Ann. Phys. 323(1), 34–48 (2008)CrossRefGoogle Scholar
  4. 4.
    Peng, X., Yin, J., Mak, P.I., Yu, W.H., Martins, R.P.: A 2.4-GHZ ZigBee transmitter using a function-reuse class-F DCO-PA and an ADPLL achieving 22.6% (14.5%) system efficiency at 6-dBm (0-dBm) \( P_{out}\). IEEE J. Solid-State Circuits 52(6), 1495–1508 (2017)Google Scholar
  5. 5.
    El-Hoiydi, A., Decotignie, J.D.: Low power downlink MAC protocols for infrastructure wireless sensor networks. Mob. Netw. Appl. 10(5), 675–690 (2005)CrossRefGoogle Scholar
  6. 6.
    Raghunathan, V., Ganeriwal, S., Srivastava, M.: Emerging techniques for long lived wireless sensor networks. IEEE Commun. Mag. 44(4), 108–114 (2006)CrossRefGoogle Scholar
  7. 7.
    Anchora, L., Capone, A., Mighali, V., Patrono, L., Simone, F.: A novel MAC scheduler to minimize the energy consumption in a wireless sensor network. Ad Hoc Netw. 16, 88–104 (2014)CrossRefGoogle Scholar
  8. 8.
    Alhmiedat, T.: Low-power environmental monitoring system for ZigBee wireless sensor network. KSII Trans. Internet Inf. Syst. 11(10), 4781–4803 (2017)Google Scholar
  9. 9.
    Pan, M.S., Tseng, Y.C.: Quick convergecast in ZigBee beacon-enabled tree-based wireless sensor networks. Comput. Commun. 31(5), 999–1011 (2008)CrossRefGoogle Scholar
  10. 10.
    Li, S.: Energy consumption optimization method of wireless sensor networks based on ZigBee. Ph.D. thesis, Hunan University (2010)Google Scholar
  11. 11.
    Zhen, C., Liu, W., Liu, Y., Yan, A.: Energy-efficient sleep/wake scheduling for acoustic localization wireless sensor network node. Int. J. Distrib. Sens. Netw. 10(2), 970524 (2014)CrossRefGoogle Scholar
  12. 12.
    Shun, J.: Research on energy consumption mechanism based on ZigBee network. Ph.D. thesis, Beijing University of Posts and Telecommunications (2015)Google Scholar
  13. 13.
    Jiang, B.: Research on MAC layer energy-efficient for ZigBee wireless sensor network. Ph.D. thesis, Shanghai Jiao Tong University (2014)Google Scholar
  14. 14.
    Bai, F.: Research on energy efficiency technology for ZigBee-based wireless sensor network. Ph.D. thesis, National University of Defense Technology (2008)Google Scholar
  15. 15.
    Gharghan, S., Nordin, R., Ismail, M.: Energy-efficient ZigBee-based wireless sensor network for track bicycle performance monitoring. Sensors 14(8), 15573–15592 (2014)CrossRefGoogle Scholar
  16. 16.
    ZigBee Alliance: ZigBee specification (2019).
  17. 17.
    IEEE: IEEE standard for local and metropolitan area networks-part 15.4: low-rate wireless personal area networks (LR-WPANs). IEEE Std 802.15.4-2011 (Revision of IEEE Std 802.15.4-2006), pp. 1–314, September 2011.
  18. 18.
    Willig, A.: Recent and emerging topics in wireless industrial communications: a selection. IEEE Trans. Ind. Inform. 4(2), 102–104 (2008)CrossRefGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.School of Information and Communication EngineeringUniversity of Electronic Science and Technology of ChinaChengduChina
  2. 2.School of Computer Science and Electronic EngineeringUniversity of EssexColchesterUK
  3. 3.Institute of Zhongshan, University of Electronic Science and Technology of ChinaZhongshanChina

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