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<p>Cold and dry regions in China span vast geographical areas, motivating long-term field monitoring deployments. However, field observation instrument networks (FOINs) often operate in harsh environments, making reliable real-time data collection and transmission challenging and exacerbating energy consumption, which shortens network lifetime. To address this issue, we propose FOI-CTMOA, a multi-objective routing protocol for FOINs. FOI-CTMOA selects high-quality cluster heads, constructs a balanced clustering structure, and optimizes data-transmission paths to balance energy consumption and network lifetime while improving data collection quality. The protocol consists of two stages: candidate cluster head selection (ECC) and cluster head and path determination (CEPS). ECC identifies candidate cluster heads using clustering objectives and the coefficient of variation, whereas CEPS combines multi-objective particle swarm optimization with competitive radius and path-selection objectives to obtain a Pareto-optimal set. TOPSIS is then applied to select the final cluster head and routing path. Simulations and comparative experiments in MATLAB show that FOI-CTMOA improves network lifetime by 10.45%, energy efficiency by 20.63%, balance extent of energy dissipation by 33.33%, throughput by 47.93%, and data acquisition integrity by 4.23% over state-of-the-art protocols.</p>

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A multi-objective optimization-based routing protocol for field observation instrument network

  • 期刊论文

  • 发表日期：

    2026年5月9日

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  • Jiuyuan Huo,
  • Fang Cao,
  • Shubin Lu,
  • Jiguang Yang

摘要

Cold and dry regions in China span vast geographical areas, motivating long-term field monitoring deployments. However, field observation instrument networks (FOINs) often operate in harsh environments, making reliable real-time data collection and transmission challenging and exacerbating energy consumption, which shortens network lifetime. To address this issue, we propose FOI-CTMOA, a multi-objective routing protocol for FOINs. FOI-CTMOA selects high-quality cluster heads, constructs a balanced clustering structure, and optimizes data-transmission paths to balance energy consumption and network lifetime while improving data collection quality. The protocol consists of two stages: candidate cluster head selection (ECC) and cluster head and path determination (CEPS). ECC identifies candidate cluster heads using clustering objectives and the coefficient of variation, whereas CEPS combines multi-objective particle swarm optimization with competitive radius and path-selection objectives to obtain a Pareto-optimal set. TOPSIS is then applied to select the final cluster head and routing path. Simulations and comparative experiments in MATLAB show that FOI-CTMOA improves network lifetime by 10.45%, energy efficiency by 20.63%, balance extent of energy dissipation by 33.33%, throughput by 47.93%, and data acquisition integrity by 4.23% over state-of-the-art protocols.