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相关概念视频

Cluster Sampling Method01:20

Cluster Sampling Method

Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

Beams are structural elements commonly employed in engineering applications requiring different load-carrying capacities. The first step in analyzing a beam under a distributed load is to simplify the problem by dividing the load into smaller regions, which allows one to consider each region separately and calculate the magnitude of the equivalent resultant load acting on each portion of the beam. The magnitude of the equivalent resultant load for each region can be determined by calculating...

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相关实验视频

Updated: Jun 2, 2026

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

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在无线传感器网络中改进了基于白优化算法的集群路由.

Hao Yuan1, Qiang Chen1, Hongbing Li2,3

  • 1Chongqing Key Laboratory of Geological Environmental Monitoring and Disaster Early Warning in the Three Gorges Reservoir Area, Chongqing Three Gorges University, Chongqing 404120, China.

Mathematical biosciences and engineering : MBE
|March 29, 2024
PubMed
概括
此摘要是机器生成的。

本研究介绍了tCBWO-DPR,这是无线传感器网络 (WSN) 的改进路由策略. 它增强了集群头选择和数据传输路径,以延长网络寿命并降低能源消耗.

关键词:
贝卢加的优化优化 贝卢加的优化启发式算法 启发式算法层次化路由是指层次化的路由.最少跨越树的树.无线传感器网络是无线传感器网络.

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相关实验视频

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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:

  • 无线传感器网络 (WSN) 中的集群路由面临着由于集群头分布和数据传输路径不足的不均能源耗尽的挑战.
  • 现有的方法难以平衡能源消耗和网络稳定性,导致过早的网络故障.

研究的目的:

  • 为集群WSN提出一个新的路由策略,tCBWO-DPR,以解决不均的能源耗尽问题.
  • 增强集群头选择和优化数据传输路线,以提高网络寿命和效率.

主要方法:

  • 为集群头选择引入了一个新的激发函数,将节点能量与位置关系相关联.
  • 改进了白优化 (BWO) 算法,使用了等号因子和t-分布 (tCBWO-DPR) 来实现更好的搜索能力和趋同.
  • 利用Prim的跨树构建算法和基于相关距离的最佳集群间路由的新 DPR 方法.

主要成果:

  • tCBWO-DPR算法在延长网络存活周期方面取得了显著的改进.
  • 模拟结果证实,无线传感器网络的平均能耗显著减少.
  • 改进的集群头选择和优化的数据传输路径有助于提高网络稳定性.

结论:

  • 拟议的tCBWO-DPR路由策略有效地减轻了聚类WSN中不均的能量耗尽.
  • 增强的白优化算法和优化的路由路径带来了卓越的网络性能和寿命.
  • 这种方法为节能和稳定的WSN运行提供了有希望的解决方案.