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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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Short-distance transport refers to transport that occurs over a distance of just 2-3 cells, crossing the plasma membrane in the process. Small uncharged molecules, such as oxygen, carbon dioxide, and water, can diffuse across the plasma membrane on their own. In contrast, ions and larger molecules require the assistance of transport proteins due to their charge or size. Transport across membranes also occurs within individual cells, playing a variety of essential roles for the plant as a whole.
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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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基于改进的海优化算法,用于异质无线传感器网络的节能和高效部署策略.

Li Cao1, Zihui Wang1, Zihao Wang1

  • 1School of Intelligent Manufacturing and Electronic Engineering, Wenzhou University of Technology, Wenzhou 325035, China.

Biomimetics (Basel, Switzerland)
|June 27, 2023
PubMed
概括
此摘要是机器生成的。

本研究介绍了一种自适应合作优化海算法 (PSO-SOA),以改善传感器网络覆盖率并减少物联网中的能源消耗. 与现有算法相比,新方法显著提高了覆盖率,并最大限度地降低了网络成本.

关键词:
物联网的物联网,就是物联网.覆盖范围覆盖范围的覆盖范围.环境监测 环境监测 环境监测不同质的无线传感器网络.节点部署部署节点部署海优化算法 海优化算法

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科学领域:

  • 环境科学 环境科学
  • 计算机科学 计算机科学
  • 工程 工程师 工程师 工程师

背景情况:

  • 物联网 (IoT) 为环境监测提供了方便的数据采集,但最初的传感器部署往往会导致覆盖问题.
  • 传统的数据采集方法可能会造成侵入性损害,这凸显了对高效无线传感器网络 (WSN) 部署的需求.

研究的目的:

  • 解决异质物联网传感器网络中的覆盖盲区和冗余问题.
  • 为最佳的传感器节点部署提出一个自适应合作优化海算法 (PSO-SOA).

主要方法:

  • 开发了一个自适应合作优化海算法 (PSO-SOA),结合了缩放因子和随机对立学习.
  • 根据节点数,覆盖半径和区域尺寸计算个人健身,以最大限度地提高覆盖率.
  • 通过代更新和微调优化传感器节点位置,以改善探索,利用和全球最佳搜索.

主要成果:

  • 该PSO-SOA算法实现了比PSO,GWO和基本SOA算法分别更高的6.1%,4.8%和1.2%的覆盖率.
  • 与PSO,GWO和基本SOA相比,网络能耗减少了86.8%,68.4%和52.6%,分别减少了86.8%,68.4%和52.6%.
  • 拟议的方法有效地避免了覆盖盲区和异质传感器网络中的冗余性.

结论:

  • 适应性合作优化海算法为物联网中的异质传感器网络提供了有效的最佳部署策略.
  • 这种方法显著提高了网络覆盖率,降低了运营成本,同时提高了数据采集效率.
  • 该PSO-SOA算法在克服随机传感器部署的局限性方面表现出卓越的性能.