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一个多目标灰狼优化算法,用于在支持物联网的WSN中进行节能集群式路由.

Selvaganapathi Sennan1, Sankar S2, Ramasubbareddy Somula3

  • 1Technical Architect, Hexaware Technologies, Jersey City, USA.

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概括
此摘要是机器生成的。

本研究介绍了一种多目标灰狼优化 (MOGWO) 算法,以提高物联网 (IoT) 网络寿命. MOGWO 提高了物联网设备的能源效率和数据传输.

关键词:
和鱼优化的优化.灰狼优化优化 灰狼优化物联网的物联网,就是物联网.优化算法的优化算法

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科学领域:

  • 计算机科学 计算机科学
  • 电气工程 电气工程
  • 网络工程 网络工程

背景情况:

  • 物联网 (IoT) 节点的资源有限,使得网络寿命延长成为一个关键的挑战.
  • 聚类对于管理物联网数据至关重要,特别是在智能农业和环境监测等应用中.
  • 有效的集群头 (CH) 选择对于优化集群物联网网络中的能源消耗至关重要.

研究的目的:

  • 为物联网网络中选择集群头 (CHs) 提出一种新的优化算法.
  • 提高物联网系统的整体网络寿命和能源效率.
  • 为了解决CH选择中现有的优化方法的局限性.

主要方法:

  • 为CH选择开发了一种多目标灰狼优化 (MOGWO) 算法.
  • 设计了一个结合模糊逻辑的健身功能,以根据距离,邻居数量和剩余能量评估潜在的CHs.
  • 模拟使用MATLAB 2019a进行了性能评估.

主要成果:

  • 与LEACH,IFFOA,SHO-CH和SHO-OBL相比,MOGWO算法证明了网络寿命延长了10-20%.
  • 使用拟议的MOGWO算法,通信开销减少了5-10%.
  • 随着MOGWO方法的使用,包裹交付率得到了2-10%的改善.

结论:

  • MOGWO算法在延长物联网网络寿命和提高性能指标方面提供了显著的改进.
  • 在MOGWO内部的模糊逻辑集成提供了一个强大的CH选择方法,平衡多个关键因素.
  • 在资源有限的物联网环境中,MOGWO为节能数据管理提供了一个有前途的解决方案.