Internet of Things and Cyber-Physical Systems (Jan 2024)

LEACH-D: A low-energy, low-delay data transmission method for industrial internet of things wireless sensors

  • Desheng Liu,
  • Chen Liang,
  • Hongwei Mo,
  • Xiaowei Chen,
  • Dequan Kong,
  • Peng Chen

Journal volume & issue
Vol. 4
pp. 129 – 137

Abstract

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In recent years, the Internet of Things (IoT) has experienced extensive adoption in industrial environments, healthcare, smart cities, and more, playing a vital role in these domains. Within IoT-based systems, wireless sensor networks (WSNs) have emerged as a crucial method for collecting peripheral environmental data within industries, owing to their self-organizational attributes. Nevertheless, the enormous volume of heterogeneous data from various sensing devices presents many challenges for IoT-enabled WSNs, encompassing high transmission delay times (TD) and excessive battery energy consumption (EC). To address these challenges, it is imperative to prioritize efficiency and optimize energy utilization. Moreover, enhancing energy efficiency within the Industrial Internet of Things (IIoT) realm hinges significantly on factors such as data transmission modes and the allocation of cluster head nodes. Numerous researchers have proposed algorithms to minimize transmission time and energy consumption, specifically focusing on industrial environments. This paper introduces an inventive clustering-based data transmission algorithm for IIoT, LEACH-D, to enhance efficiency. The LEACH-D algorithm improves the transmission task duration while maintaining consistent battery energy consumption. It also seeks to elevate performance in metrics such as average transmission time during the first node death (FND). Numerous experimental results provide strong evidence that the algorithm introduced in this paper has effectively reduced the average transmission time by remarkable percentages: 51.32%, 12.12%, 12.96%, and 5.42%, while simultaneously increasing the number of FND rounds by significant margins: 222.43%, 36.63%, 33.72%, and 7.81%, respectively. These improvements stand in stark contrast to the performance of existing algorithms, including FREE_MODE, LEACH, EE-LEACH, and ETH-LEACH.

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