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<p>Wireless sensor networks play a crucial role in Internet of Things systems, whose development and prevalence have given rise to numerous challenges. One of the most notable problems regarding wireless sensor networks is the sensor deployment problem, where the objective is to minimize the number of nodes used and to satisfy the constraints of coverage and connectivity. In reality, sensors may be prone to errors and failures; therefore, simple coverage and simple connectivity cannot guarantee fault tolerance for a system. This leads to the concepts of <i>Q</i>-coverage and <i>Q</i>-connectivity, which indicates that each target needs <i>q</i> covering sensors and <i>q</i> node-disjoint paths to the base station. To minimize the number of nodes while still ensuring <i>Q</i>-coverage and <i>Q</i>-connectivity, we propose a heuristic algorithm and an algorithm based on the genetic algorithm. Besides, we construct various experiment scenarios and a realistic dataset to evaluate the efficiency of our proposed methods. The experiment results show that our proposed algorithms significantly outperform existing methods in both solution quality and running time.</p>

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Propagation-aware Q-coverage and Q-connectivity network design in relay-aided IoT sensor systems using heuristic and genetic algorithms

  • 期刊论文

  • 发表日期：

    2025年3月25日

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  • Nguyen Xuan Thang,
  • Nguyen Thi Hanh,
  • Nguyen Van Son,
  • Nguyen Phuc Tan,
  • To Quang Hung,
  • Trinh Van Chien,
  • Huynh Thi Thanh Binh

摘要

Wireless sensor networks play a crucial role in Internet of Things systems, whose development and prevalence have given rise to numerous challenges. One of the most notable problems regarding wireless sensor networks is the sensor deployment problem, where the objective is to minimize the number of nodes used and to satisfy the constraints of coverage and connectivity. In reality, sensors may be prone to errors and failures; therefore, simple coverage and simple connectivity cannot guarantee fault tolerance for a system. This leads to the concepts of Q-coverage and Q-connectivity, which indicates that each target needs q covering sensors and q node-disjoint paths to the base station. To minimize the number of nodes while still ensuring Q-coverage and Q-connectivity, we propose a heuristic algorithm and an algorithm based on the genetic algorithm. Besides, we construct various experiment scenarios and a realistic dataset to evaluate the efficiency of our proposed methods. The experiment results show that our proposed algorithms significantly outperform existing methods in both solution quality and running time.