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An energy efficient data transmission approach for low-duty-cycle wireless sensor networks

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Abstract

In low-duty-cycle wireless sensor networks, the lifetime of energy-limited nodes is improved, but the network’s transmission delay is also increased. However, many systems with real-time capabilities require data to be sent to the data center within a specified time. In this paper, we first analyze the relationship between the duty cycle of the node and the network lifetime and transmission delay, and then propose a novel scheme named transmission delay minimization based on adjustable duty cycle (DMADC). In the DMADC scheme, a higher duty cycle is employed in the non-hotspot region to achieve a lower latency, and a lower duty cycle is used in the hot spot area to achieve higher network life. This method can make full use of the residual energy of the nodes at the edge of the network to dynamically adjust its duty cycle, reduce the waiting delay in the data transmission process, and select a path close to the global optimum for each node in the network, so that our scheme is able to achieve a minimum average end-to-end delay. The theoretical analysis and experimental results demonstrate that the performance of DMADC is better than that proposed in previous studies. Compared with previous research schemes, the DMADC scheme can reduce the end-to-end data transmission delay by 10.25%–26.37% while maintaining the network lifetime, and increase the energy utilization rate by more than 25%. The DMADC scheme improves network lifetime by about 30% while maintaining end-to-end latency.

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Acknowledgments

This work is supported by the National Natural Science Foundation of China (Grant No.71633006, Grant No. 61672540, Grant No. 61379057). This work is supported by the China Postdoctoral Science Foundation funded project (Grant No. 2017 M612586). This work is supported by the Postdoctoral Science Foundation of Central South University (Grant No. 185684). Also, this work was supported partially by” Mobile Health” Ministry of Education - China Mobile Joint Laboratory.

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Authors and Affiliations

  1. School of computer science and engineering, Central South University Chang Sha, Hu Nan, 410075, China

    Jian Wu, Zhigang Chen, Jia Wu, Xiao Liu & Genghua Yu

  2. School of automation, Central South University Changsha, Hu Nan, 410075, China

    Yedong Zhao

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  1. Jian Wu
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  2. Zhigang Chen
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  3. Jia Wu
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  4. Xiao Liu
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  5. Genghua Yu
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  6. Yedong Zhao
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Correspondence to Zhigang Chen or Jia Wu.

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Wu, J., Chen, Z., Wu, J. et al. An energy efficient data transmission approach for low-duty-cycle wireless sensor networks. Peer-to-Peer Netw. Appl. 13, 255–268 (2020). https://doi.org/10.1007/s12083-019-00762-y

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