MLMAC-HEAP: A Multi-Layer MAC Protocol for Wireless Sensor Networks Powered by Ambient Energy Harvesting

  • 32 Accesses


Limited availability of energy is the most crucial constraint of wireless sensor networks (WSN). Most power consuming part of WSN node is transreceiver and operation of transreciever to access medium is controlled by the medium access control (MAC) sublayer of the open systems interconnection (OSI) model. In WSN, till now, most of the present MAC protocols have addressed issues related to power saving. Because of energy constraints, performance is often not a focused design parameter in these MAC protocols. However, recent advances in energy harvesting technology have made it possible to obtain energy from the environment to solve energy limitations. So in this paper, a new multi layer based MAC protocol, MLMAC-HEAP is designed for solar energy harvesting criterion considering performance as the mainly focused parameter. Performance is illustrated in terms of throughput. This paper evaluates the performance of MLMAC-HEAP as a function of energy harvesting rate and number of nodes in network and results are compared and shown to outperform well known MAC protocols. Then, the paper analyses the protocol for various traffic models. Based on application-level requirements, optimization is also done for number of layers.

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

Access options

Buy single article

Instant unlimited access to the full article PDF.

US$ 39.95

Price includes VAT for USA

Subscribe to journal

Immediate online access to all issues from 2019. Subscription will auto renew annually.

US$ 199

This is the net price. Taxes to be calculated in checkout.

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
Fig. 15
Fig. 16


  1. 1.

    Althobaiti, A. S., & Abdullah, M. (2015). Medium access control protocols for wireless sensor networks classifications and cross-layering. Procedia Computer Science,65, 4–16.

  2. 2.

    Didioui, A. (2015). Energy-aware transceiver for energy harvesting wireless sensor networks. Signal and Image Processing.

  3. 3.

    Jha, M. K., Kumar, A., Pal, D., & Mohan, A. (2011). An energy-efficient multi-layer MAC (ML-MAC) protocol for wireless sensor networks. International Journal of Electronics and Communications (AEÜ),65(3), 209–216.

  4. 4.

    Ye, W., Heidemann, J., & Estrin, D. (2002). An energy-efficient MAC protocol for wireless sensor networks. In Proceedings of IEEE INFOCOM 2002 (pp. 1567–1576).

  5. 5.

    Thalore, R., Sharma, J., Khurana, M., & Jha, M. K. (2013). QoS evaluation of energy-efficient ML-MAC protocol for wireless sensor networks. International Journal of Electronics and Communications (AEÜ),67(12), 1048–1053.

  6. 6.

    Khurana, M., Thalore, R., Raina, V., & Jha, M. K. (2015). Improved time synchronization in ML-MAC for WSN using relay nodes. International Journal of Electronics and Communications (AEÜ),69(11), 1622–1626.

  7. 7.

    Sun, Y., Gurewitz, O., & Johnson, D. B. (2008). RI-MAC: A receiver-initiated asynchronous duty cycle MAC protocol for dynamic traffic loads in wireless sensor networks. In SenSys (pp. 1–14).

  8. 8.

    Fafoutis, X., & Dragoni, N. (2011). ODMAC: An on-demand MAC protocol for energy harvesting-wireless sensor networks. In PEWASUN 2011: Proceedings of the 8th ACM symposium on performance evaluation of wireless ad hoc, sensor, and ubiquitous networks (pp. 49–56).

  9. 9.

    Fafoutis, X., Mauro, A. D., Orfanidis, C., & Dragoni, N. (2015). Energy-efficient medium access control for energy harvesting communications. IEEE Transactions on Consumer Electronics,61(4), 402–410.

  10. 10.

    Fafoutis, X., & Dragoni, N. (2012). Adaptive media access control for energy-harvesting-wireless sensor networks. In INSS 2012: Ninth international conference on networked sensing systems, Belgium.

  11. 11.

    Nguyen, K., Nguyen, V., Le, D., Ji, Y., Duong, D. A., & Yamada, S. (2014). ERI-MAC: An energy-harvested receiver-initiated MAC protocol for wireless sensor networks. International Journal of Distributed Sensor Networks,10, 514167.

  12. 12.

    Eu, Z. A., Tan, H. P., & Seah, W. K. G. (2011). Design and performance analysis of MAC schemes for wireless sensor networks powered by ambient energy harvesting. Ad Hoc Networks,9(3), 300–323.

  13. 13.

    Eu, Z. A., & Tan, H. P. (2012) Probabilistic polling for multi-hop energy harvesting wireless sensor networks. In Ad hoc and sensor networking symposium. IEEE.

  14. 14.

    Frezzetti, A., Manfredi, S., & Pagano, M. (2015). A design approach of the solar harvesting control system for wireless sensor node. Control Engineering Practice,44, 45–54.

  15. 15.

    Kim, T., Park, J., Kim, J., Noh, J., & Cho, S. (2017). REACH : An efficient MAC protocol for RF energy harvesting in wireless sensor network. Wireless Communications and Mobile Computing.

  16. 16.

    Sherazi, H. H. R., Grieco, L. A., & Boggia, G. (2018). A comprehensive review on energy harvesting MAC protocols in WSNs: Challenges and tradeoffs. Ad Hoc Networks,71, 117–134.

  17. 17.

    Kosunalp, S. (2016). A new energy prediction algorithm for energy-harvesting wireless sensor networks with Q-learning. IEEE Access,4, 5755–5763.

  18. 18.

    Kosunalp, S. (2017). An energy prediction algorithm for wind-powered wireless sensor networks with energy harvesting. Energy,139, 1275–1280.

  19. 19.

    Singh, R., & Verma, A. K. (2017). Energy efficient cross layer based adaptive threshold routing protocol for WSN. International Journal of Electronics and Communications (AEÜ),72, 166–173.

  20. 20.

    Cammarano, A., Petrioli, C., & Spenza, D. (2012). Pro-energy: A novel energy prediction model for solar and wind energy-harvesting wireless sensor networks. In Proceedings of IEEE international conference on mobile ad-hoc and sensor systems (pp. 75–83).

  21. 21.

    Shaikh, F. K., & Zeadally, S. (2016). Energy harvesting in wireless sensor networks: A comprehensive review. Renewable and Sustainable Energy Reviews,55, 1041–1054.

  22. 22.

    Texas Instruments’ eZ430-RF2500-SEH datasheet. Retrieved April 02, 2018, from

  23. 23.

    Texas Instruments’s cc2500 low-cost low-power 2.4 GHz RF transceiver. Retrieved April 02, 2018, from

  24. 24.

    Wang, Q. (2010). Traffic analysis & modeling in wireless sensor networks and their applications on network. Network Protocols and Algorithms,2(1), 74–92.

  25. 25.

    Kassim, M., Ismail, M., & Yusof, M. I. (2015). Statistical analysis and modeling of internet traffic IP-based network for tele-traffic engineering. ARPN Journal of Engineering and Applied Science,10(3), 1505–1512.

Download references


This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Author information

Correspondence to Aarti Kochhar.

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

Verify currency and authenticity via CrossMark

Cite this article

Kochhar, A., Kaur, P., Singh, P. et al. MLMAC-HEAP: A Multi-Layer MAC Protocol for Wireless Sensor Networks Powered by Ambient Energy Harvesting. Wireless Pers Commun 110, 893–911 (2020) doi:10.1007/s11277-019-06762-8

Download citation


  • Wireless sensor network
  • MAC protocol
  • Solar energy harvesting
  • Throughput