摘要
针对布谷鸟搜索算法在认知车载网中频谱分配收敛速度低的问题,提出了一种基于萤火虫算法的频谱分配方法。该方法考虑种群所获得的平均收益值,将频谱分配变量映射为萤火虫位置信息,并将车载网络的吞吐量转化为萤火虫的亮度值,采用萤火虫算法离散频谱分配变量并进行迭代寻优。数值结果表明,基于萤火虫算法的认知车载网络频谱分配方式的收敛速度快,且种群的平均收益值高于遗传算法和布谷鸟算法。
To solve slow convergence of cuckoo search algorithm for spectrum allocation in cognitive vehicle network, a new method based on firefly algorithm is proposed. In this method, the average benefit value of population is considered,the spectrum allocation variable is mapped into firefly location information, and the vehicle network throughput is converted into the firefly’s brightness value. Moreover, it utilizes firefly algorithm to discrete spectrum allocation variable and performs iterative optimization. The numerical analysis shows that the spectrum allocation of cognitive vehicle network based on firefly algorithm has a fast convergence speed, and the average benefit value is higher than that of genetic algorithm and cuckoo algorithm.
作者
朱丹
邱斌
肖海林
倪菊
ZHU Dan;QIU Bin;XIAO Hailin;NI Ju(School of Information and Communication,Guilin University of Electronic Technology,Guilin,Guangxi 541004 China;College of Information Science and Engineering,Guilin University of Technology,Guilin,Guangxi 541004,China;Library,Guilin University of Electronic Technology,Guilin,Guangxi 541004,China;College of Physics and Electronic Information Engineering,Wenzhou University,Wenzhou,Zhejiang 325035,China)
出处
《计算机工程与应用》
CSCD
北大核心
2019年第2期67-71,共5页
Computer Engineering and Applications
基金
国家自然科学基金(No.61261018
No.61472094)
广西自然科学基金杰出青年基金(No.2014GXNSFGA118007)
2018年浙江省重点研发计划(No.2018C01059)
关键词
认知车载网
萤火虫算法
频谱分配
cognitive vehicular network
firefly algorithm
spectrum allocation
