UWSNs clustering routing algorithm based on improved grey wolf optimization

JIANG Hua; CAI Wei; WANG Xin; QIN Qin

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UWSNs clustering routing algorithm based on improved grey wolf optimization

更新时间：2026-09-04

- UWSNs clustering routing algorithm based on improved grey wolf optimization
- Vol. 37, Issue 6, Pages: 46-50(2020)
- 作者机构：
  
  1. 桂林电子科技大学机构计算机信息与安全学院,广西,桂林,541004
  2. 桂林电子科技大学北海校区,广西,北海,536005
- 作者简介：
- 基金信息：
- DOI：
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- Published：2020
- 稿件说明：
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蒋华, 蔡玮, 王鑫, 覃琴. 基于改进灰狼优化的UWSNs分簇路由算法[J]. 微电子学与计算机, 2020, 37(6): 46-50,56.

JIANG Hua, CAI Wei, WANG Xin, et al. UWSNs clustering routing algorithm based on improved grey wolf optimization[J]. 2020, 37(6): 46-50.
蒋华, 蔡玮, 王鑫, 覃琴. 基于改进灰狼优化的UWSNs分簇路由算法[J]. 微电子学与计算机, 2020, 37(6): 46-50,56. DOI：

JIANG Hua, CAI Wei, WANG Xin, et al. UWSNs clustering routing algorithm based on improved grey wolf optimization[J]. 2020, 37(6): 46-50. DOI：

摘要

针对水下无线传感器网络中存在的严重的能耗问题，提出一种基于改进灰狼优化的UWSNs分簇路由算法，采用改进灰狼优化算法进行迭代更新，保证簇首分布均匀，节约簇首能量，平衡负载.数据传输阶段采用最短路径选择策略，保证多跳传输能耗最小.通过实验分析，该方法能够降低UWSNs能耗，延长网络生命周期.

Abstract

Aiming at the energy consumption problem in underwater wireless sensor networks

a UWSNs clustering routing algorithm based on improved gray wolf optimization is proposed. It uses the improved grey wolf optimization algorithm to iteratively update to ensure uniform cluster head distribution

balance load and saveenergy. The data transmission phase uses the shortest path selection strategy to ensure minimum energy consumption for multi-hop transmission.Simulation resultsshows thatthis method can reduce the energy consumption of UWSNs and prolong the network life cycle.

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references

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