WSN中基于双群体差分进化的资源分配优化算法

郝晓辰; 王立元; 刘金硕; 解力霞; 张文焕

doi:10.11959/j.issn.1000-436x.2018061

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WSN中基于双群体差分进化的资源分配优化算法

学术论文 | 更新时间：2024-06-05

- WSN中基于双群体差分进化的资源分配优化算法
- Resource allocation optimization algorithm based on double populations differential evolution in WSN
- 通信学报 2018年39卷第4期页码：68-75
- 作者机构：
  
  燕山大学电气工程学院，河北秦皇岛 066004
- 作者简介：
  
  [ "郝晓辰（1980-），男，河北衡水人，博士，燕山大学教授，主要研究方向为无线传感器网络拓扑控制、无线传感器网络的资源分配。" ]
  [ "王立元（1993-），女，河北衡水人，燕山大学硕士生，主要研究方向为无线传感器网络的资源分配算法。" ]
  [ "刘金硕（1992-），女，河北衡水人，燕山大学硕士生，主要研究方向为无线传感器的拓扑控制、无线传感器的功率与信道联合优化算法。" ]
  [ "解力霞（1991-），女，山东菏泽人，燕山大学硕士生，主要研究方向为无线传感器网络的拓扑控制、无线传感器网络的功率与信道联合优化算法。" ]
  [ "张文焕（1993-），女，河北邢台人，燕山大学硕士生，主要研究方向为无线传感器网络资源分配算法。" ]
- 基金信息：
  
  国家自然科学基金资助项目(61403336);河北省自然科学基金资助项目(F2015203342);燕山大学青年教师自主研究计划基金资助项目(15LGB007)
- DOI：10.11959/j.issn.1000-436x.2018061
  中图分类号： TP393
- 网络出版日期：2018-04，
  
  纸质出版日期：2018-04-25
- 稿件说明：
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郝晓辰, 王立元, 刘金硕, 等. WSN中基于双群体差分进化的资源分配优化算法[J]. 通信学报, 2018,39(4):68-75.

Xiaochen HAO, Liyuan WANG, Jinshuo LIU, et al. Resource allocation optimization algorithm based on double populations differential evolution in WSN[J]. Journal on communications, 2018, 39(4): 68-75.
郝晓辰, 王立元, 刘金硕, 等. WSN中基于双群体差分进化的资源分配优化算法[J]. 通信学报, 2018,39(4):68-75. DOI： 10.11959/j.issn.1000-436x.2018061.

Xiaochen HAO, Liyuan WANG, Jinshuo LIU, et al. Resource allocation optimization algorithm based on double populations differential evolution in WSN[J]. Journal on communications, 2018, 39(4): 68-75. DOI： 10.11959/j.issn.1000-436x.2018061.

摘要

针对多射频多信道（MRMC

multi-radio multi-channel）无线传感器网络中的链路冲突和链路干扰过大而导致的网络能耗过大、容量受限、资源分配不均衡的问题，提出一种基于双群体差分进化的联合资源分配优化算法（RADEA）。RADEA 综合考虑了信道分配、功率控制和时隙分配之间相互影响的关系，以链路的冲突和干扰为约束条件，以减小网络能耗、最大化网络容量、提高资源分配的均衡性为目标函数，构建了系统的资源分配多目标优化模型。考虑到解决多目标优化问题的复杂性，采用双群体差分进化算法对模型进行迭代求解。仿真实验表明，该算法能够有效地避免链路冲突，同时能有效地降低网络干扰，提高网络容量和资源分配均衡性。

Abstract

A resource allocation algorithm was proposed for improving the network performance through jointing channel allocation

power control and timeslot allocation in multi-radio multi-channel wireless sensor network.More specifically

the network was modeled as a multi-objective optimization problem where the energy efficient

resource allocation balanced

networks capacity maximized were considered under the link interference and link conflict constraints.Due to the problem was NP-Hardness

a simple centralized algorithm——differential evolution based on double populations was used to solve the constrained multi-objective optimization problem.The simulation results show that the proposed algorithm significantly improves the network capacity and energy efficiency and guarantees the resource allocation balancing while reducing link interference and avoiding link conflict.

关键词

Keywords

references

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