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Theoretical modeling for performance analysis of IEEE 1901 power-line communication networks in the multi-hop environment

  • Sheng Hao
  • Hu-yin ZhangEmail author
Article
  • 23 Downloads

Abstract

As one of the most promising networking technologies, power-line communication (PLC) networks have been gradually used not only in home networking systems but also in industrial IoT (Internet of things). Current studies of PLC medium access control (MAC) protocol (i.e., IEEE 1901) only focus on the single-hop environment; however, in practical industrial IoT and home access communication systems, PLC networks generally utilize a multi-hop architecture. In addition, due to the difference in the MAC standard between 802 series and 1901, existing analytical models of multi-hop IEEE 802.11 wireless networks are not suitable for multi-hop IEEE 1901 PLC networks. In this paper, we propose a theoretical model for performance analysis of multi-hop IEEE 1901 PLC networks, where the impacts of traffic rate (containing relay traffic), buffer size, deferral counter process of 1901, hidden terminal problem and multi-hop environment are comprehensively considered. The modeling process is divided into two parts. In the local modeling part, we construct a brand-new Markov chain model to investigate the carrier sense multiple access with collision avoidance process of IEEE 1901 protocol under the multi-hop environment. In the coupling queueing modeling part, we employ queueing theory to analyze the packet transmission procedure between successive hops. On the basis, we derive the closed-form expressions of throughput, medium access delay, packet blocking probability, end-to-end successful transmission delay and goodput. Through extensive simulations, we verify that our theoretical model can accurately estimate the MAC performance of IEEE 1901 PLC networks in the multi-hop environment.

Keywords

Power-line communication (PLC) IEEE 1901 MAC protocol Multi-hop environment CSMA/CA Performance analysis Markov chain Queueing theory 

Notes

Acknowledgements

The author would like to thank the editor and four anonymous reviewers for helpful comments that have improved the quality of the paper. This work is supported by the National Natural Science Foundation of China (No. 61772386).

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Copyright information

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

Authors and Affiliations

  1. 1.School of ComputerWuhan UniversityWuhanPeople’s Republic of China

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