基于改进人工蜂群算法的集成网络节点部署优化
TP301.6; 为提高集成网络节点的部署效率,在考虑节点交叉覆盖及节点间干扰等约束条件下,基于改进人工蜂群算法,提出一种集成网络节点位置部署算法.基于网络节点的信号传输模型将节点部署问题转化为在保证节点高覆盖率与低干扰目标下的优化问题,利用改进人工蜂群算法对节点部署目标函数进行优化.仿真实验结果表明,该算法不但能够快速精确地找到全局部署最优位置,而且能够在保证射频标签最大覆盖率的前提下有效地降低节点间的干扰....
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| Published in | 计算机工程 Vol. 42; no. 3; pp. 116 - 120 |
|---|---|
| Main Author | |
| Format | Journal Article |
| Language | Chinese |
| Published |
甘肃省工业过程先进控制重点实验室,兰州730050%兰州理工大学电气工程与信息工程学院,兰州,730050
2016
兰州理工大学电气工程与信息工程学院,兰州730050 |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1000-3428 |
| DOI | 10.3969/j.issn.1000-3428.2016.03.021 |
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| Abstract | TP301.6; 为提高集成网络节点的部署效率,在考虑节点交叉覆盖及节点间干扰等约束条件下,基于改进人工蜂群算法,提出一种集成网络节点位置部署算法.基于网络节点的信号传输模型将节点部署问题转化为在保证节点高覆盖率与低干扰目标下的优化问题,利用改进人工蜂群算法对节点部署目标函数进行优化.仿真实验结果表明,该算法不但能够快速精确地找到全局部署最优位置,而且能够在保证射频标签最大覆盖率的前提下有效地降低节点间的干扰. |
|---|---|
| AbstractList | TP301.6; 为提高集成网络节点的部署效率,在考虑节点交叉覆盖及节点间干扰等约束条件下,基于改进人工蜂群算法,提出一种集成网络节点位置部署算法.基于网络节点的信号传输模型将节点部署问题转化为在保证节点高覆盖率与低干扰目标下的优化问题,利用改进人工蜂群算法对节点部署目标函数进行优化.仿真实验结果表明,该算法不但能够快速精确地找到全局部署最优位置,而且能够在保证射频标签最大覆盖率的前提下有效地降低节点间的干扰. 为提高集成网络节点的部署效率,在考虑节点交叉覆盖及节点间干扰等约束条件下,基于改进人工蜂群算法,提出一种集成网络节点位置部署算法。基于网络节点的信号传输模型将节点部署问题转化为在保证节点高覆盖率与低干扰目标下的优化问题,利用改进人工蜂群算法对节点部署目标函数进行优化。仿真实验结果表明,该算法不但能够快速精确地找到全局部署最优位置,而且能够在保证射频标签最大覆盖率的前提下有效地降低节点间的干扰。 |
| Author | 杨新华 薛健 王彦龙 |
| AuthorAffiliation | 兰州理工大学电气工程与信息工程学院,兰州730050 甘肃省工业过程先进控制重点实验室,兰州730050 |
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| Author_FL | YANG Xinhua XUE Jian WANG Yanlong |
| Author_FL_xml | – sequence: 1 fullname: YANG Xinhua – sequence: 2 fullname: XUE Jian – sequence: 3 fullname: WANG Yanlong |
| Author_xml | – sequence: 1 fullname: 杨新华 薛健 王彦龙 |
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| ClassificationCodes | TP301.6 |
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| Copyright | Copyright © Wanfang Data Co. Ltd. All Rights Reserved. |
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| DOI | 10.3969/j.issn.1000-3428.2016.03.021 |
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| DocumentTitleAlternate | Deployment Optimization of Integrated Network Node Based on Improved Artificial Bee Colony Algorithm |
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| EndPage | 120 |
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| Keywords | 改进人工蜂群算法 integrated network node deployment optimization 集成网络节点 Radio Frequency (RF) model 全局交叉机制 improved Artificial Bee Colony(ABC) algorithm 射频模型 global cross mechanism 部署优化 |
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| Notes | integrated network node; Radio Frequency（RF） model; deployment optimization; global cross mechanism; improved Artificial Bee Colony（ABC） algorithm 31-1289/TP YANG Xinhua;XUE Jian;WANG Yanlong; （ 1. College of Electrical and Information Engineering,Lanzhou University of Technology,Lanzhou 730050, China; 2. Key Laboratory of Gansu Advanced Control for Industrial Processes,Lanzhou 730050,China） In order to improve the deployment efficiency of the integrated network nodes,an integrated network node location deployment algorithm is proposed based on the improved Artificial Bee Colony（ ABC） algorithm when considering the cross coverage of nodes and interference between nodes. In the deployment algorithm,the deployment problem of network nodes which is based on the signal model is converted into the optimization problem of ensuring high coverage and lowinterference of nodes,and the improved ABC algorithm is used to optimize the objective function of node deployment. Simulation results showthat the algorithm can not onl |
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| PublicationTitle | 计算机工程 |
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| PublicationYear | 2016 |
| Publisher | 甘肃省工业过程先进控制重点实验室,兰州730050%兰州理工大学电气工程与信息工程学院,兰州,730050 兰州理工大学电气工程与信息工程学院,兰州730050 |
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| Snippet | 为提高集成网络节点的部署效率,在考虑节点交叉覆盖及节点间干扰等约束条件下,基于改进人工蜂群算法,提出一种集成网络节点位置部署算法。基于网络节点的信号传输模型将节点... TP301.6; 为提高集成网络节点的部署效率,在考虑节点交叉覆盖及节点间干扰等约束条件下,基于改进人工蜂群算法,提出一种集成网络节点位置部署算法.基于网络节点的信号传输模... |
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| SubjectTerms | 全局交叉机制 射频模型 改进人工蜂群算法 部署优化 集成网络节点 |
| Title | 基于改进人工蜂群算法的集成网络节点部署优化 |
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