Scholarlink

<p>Dynamic routing problem is an important research challenge for the robust working of the Internet of Things network as many sensors are equipped with limited energy resources. The work carried out in this paper uses a novel energy model to formulate the routing problem for IoT networks. An AI-based approach using a modified A* algorithm proposes a dynamic routing framework for IoT. The simulated results are compared with the k-Means algorithm and genetic algorithm in terms of energy consumption and the number of dead nodes. This comparison reveals the proposed routing framework to outperform than k-Means algorithm and GA by extending the lifetime of the IoT network by a factor of thrice and twice, respectively. Further, the proposed routing framework is also compared over different network configurations.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

An AI-based approach for dynamic routing in IoT networks

  • 期刊论文

  • 发表日期：

    2025年3月4日

查看全文
  • Debasis Gountia,
  • Pranati Mishra,
  • Ranjan Kumar Dash,
  • Nihar Ranjan Pradhan,
  • Sachi Nandan Mohanty

摘要

Dynamic routing problem is an important research challenge for the robust working of the Internet of Things network as many sensors are equipped with limited energy resources. The work carried out in this paper uses a novel energy model to formulate the routing problem for IoT networks. An AI-based approach using a modified A* algorithm proposes a dynamic routing framework for IoT. The simulated results are compared with the k-Means algorithm and genetic algorithm in terms of energy consumption and the number of dead nodes. This comparison reveals the proposed routing framework to outperform than k-Means algorithm and GA by extending the lifetime of the IoT network by a factor of thrice and twice, respectively. Further, the proposed routing framework is also compared over different network configurations.