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针对混合WSN-LTE辅助物联网网络的多因素优化的移动水槽数据收集框架.

Saranga Mohan1, Sunita Panda1

  • 1Department of Electrical, Electronics, and Communication Engineering, GITAM School of Technology, GITAM (Deemed to Be University), Bengaluru, India.

Heliyon
|March 12, 2024
PubMed
概括

这项研究通过优化能源使用以延长设备寿命来增强无线传感器网络 (WSN) 和物联网 (IoT) 系统. 新的混合方法提高了网络性能和数据传输效率.

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:

  • 无线传感器网络 (WSN) 对物联网 (IoT) 应用至关重要.
  • 电池驱动的传感器需要节能,以延长运行时间.
  • 移动水槽用于延长网络寿命,但可扩展性和多标准优化仍然具有挑战性.

研究的目的:

  • 为应对在移动水槽辅助WSNs中最大化网络寿命和服务质量 (QoS) 的挑战.
  • 提出一种混合架构,将WSN与长期进化 (LTE) 集成在一起.
  • 开发一个两个阶段的优化策略,用于集群和数据收集路径调度.

主要方法:

  • 一种混合的元启发学方法被用于多标准的最佳集群问题.
  • 基于最小施泰纳树的图形理论用于有效的数据收集路径调度.
  • 网络自适应性流量基于类的数据调度已集成,用于增强的 QoS.

主要成果:

  • 拟议的混合方法可以实现寿命最大化,而不会影响QoS.
  • 模拟显示,网络寿命显著增加 (至少6%).
  • 与现有方法相比,数据包交付延迟减少了26%.
关键词:
集群优化优化 集群优化图形理论是指图形的理论.物联网的物联网,就是物联网.移动洗手间的水槽服务质量的多重标准服务质量.无线传感器网络是无线传感器网络.

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结论:

  • 混合化策略有效地延长了WSN的寿命,并增强了QoS.
  • 集成多标准聚类,最佳路径调度和自适应数据调度是关键.
  • 拟议的架构为移动水槽辅助WSNs提供了可扩展和有效的解决方案.