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软件定义无线网络的负载均衡算法
引用本文:陈铸,严朝阳,吴广富,王林. 软件定义无线网络的负载均衡算法[J]. 重庆邮电大学学报(自然科学版), 2021, 33(1): 28-33. DOI: 10.3979/j.issn.1673-825X.201904220161
作者姓名:陈铸  严朝阳  吴广富  王林
作者单位:中国电子科技集团公司第十研究所 成都628007;重庆邮电大学 移动通信技术重点实验室 重庆400065;重庆邮电大学 移动通信技术重点实验室 重庆400065;重庆邮电大学 移动通信技术重点实验室 重庆400065
基金项目:重庆市教委科学技术研究项目(KJQN201800642);博士研究生高端人才培养项目(BYJS2016009);国家自然科学基金(61701059,61671096);重庆市基础科学与前沿技术研究项目(cstc2017jcyjBX0005);重庆市科技创新领军人才(cstc2018kjcxljrc0084);重庆市重点产业共性关键技术创新专项(cstc2017zdcy-zdyf0607)
摘    要:在传统无线局域网中,终端往往优先选择信号强的接入点.诸如会议室、商场、机场等存在大量终端的公共场所,极有可能造成部分接入点负载过重.基于软件定义无线网络(software defined wireless network,SDWN),综合考虑终端占用带宽、当前接入点负载和当前终端接收信号强度指示等影响因素,提出周期性地检查各接入点的负载状态,将超载接入点下的候选终端重关联至轻载接入点,从而使整个控制器下所有接入点都达到均衡状态.实验结果表明,随着负载平衡因子持续降低,软件定义无线网络中不同接入点的负载逐渐趋于均衡,从而提高了系统平均吞吐率.仿真结果表明,所提负载均衡算法相对于最强信号强度优先和最小负载优先的负载均衡算法,分别提高约8.3%和15.6%.

关 键 词:软件定义无线网络(SDWN)  负载均衡  资源分配  用户关联
收稿时间:2019-04-22
修稿时间:2020-05-20

Load balancing algorithm based on software defined wireless network
CHEN Zhu,YAN Zhaoyang,WU Guangfu,WANG Lin. Load balancing algorithm based on software defined wireless network[J]. Journal of Chongqing University of Posts and Telecommunications, 2021, 33(1): 28-33. DOI: 10.3979/j.issn.1673-825X.201904220161
Authors:CHEN Zhu  YAN Zhaoyang  WU Guangfu  WANG Lin
Affiliation:China Electronics Technology Group Corporation No. 10 Research Institute, Chengdu 628007, P. R. China;Chongqing Key Lab of Mobile Communications Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, P. R. China
Abstract:In traditional wireless local area networks, mobile terminals often select the access point (AP) with strong signal strength as the access object. However, in public places such as conference halls, shopping malls and airports where there are a large number of terminals, it is more likely that some access points will be overloaded. In this paper, based on the software defined network (SDWN), considering the factors such as the bandwidth occupied by the terminal, the load of the current access point and the received signal strength indication from the terminal to the AP, we first periodically check the load status of each AP, and then the candidate terminals under the overloaded access point are re-associated to the appropriate light-load access point, so that all APs under the whole controller can reach a balanced state. The simulation results demonstrate that with the decreasing of load balancing factor, the load of different APs in software defined wireless networks tends to be balanced gradually, thus the average system throughput may be improved greatly. The simulation results show that the proposed load balancing algorithm improves about 8.3% and 15.6% respectively, compared with the load balancing algorithm based on the strongest signal first and the least load first.
Keywords:software defined wireless network  load balancing  resource allocation  candidate users
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