基于GSA算法的WVN资源映射数学模型  

Mathematical Model of Wireless Virtual Network Resource Mapping Based on GSA Algorithm

作　　者：王晓霞[1] 郑大钊[1] WANG Xiao-xia;ZHENG Da-zhao(College of Science,Qiqihar University,Heilongjiang Qiqihaer 161005,China)

机构地区：[1]齐齐哈尔大学理学院,黑龙江齐齐哈尔161005

出　　处：《计算机仿真》2022年第4期398-402,共5页Computer Simulation

基　　金：黑龙江省教育厅基本业务专项(135109228)。

摘　　要：由于传统方法没有从满足成本最小需求角度出发,建立虚拟网络映射目标,导致底层链路利用率较高,剩余带宽较低以及请求接受率不高的问题,于是研究基于GSA算法的无线虚拟网络资源映射数学模型。充分考虑无线虚拟网络资源映射成本、映射收益以及虚拟网络请求接受率建立数学模型,设置节点CPU资源约束、节点映射位置约束、链路带宽资源约束等约束作为约束条件。选取遗传算法与模拟退火算法结合的GSA算法,通过编码、参数初始化、模拟退火操作、选取种群、交叉与变异、退火操作六步骤求解所建立数学模型,实现无线虚拟网络资源的有效映射。实验结果表明,采用上述模型可降低移动网络运营商成本,虚拟网络请求接受率高于92%,提升了虚拟网络资源映射成功率。Because the traditional method does not establish the virtual network mapping target from the perspective of meeting the minimum cost demand, which leads to the problems of high underlying link utilization, low residual bandwidth and low request acceptance rate, the mathematical model of wireless virtual network resource mapping based on GSA algorithm is studied. Wireless virtual network resource mapping cost, mapping revenue and virtual network request acceptance rate were combined to found a mathematical model. Node CPU resource constraints, node mapping location constraints, and link bandwidth resource constraints were set up. The GSA algorithm combined with genetic algorithm and simulated annealing algorithm was selected to solve the established mathematical model through six steps: coding, parameter initialization, simulated annealing operation, population selection, crossover and mutation and annealing operation, so as to realize the effective mapping of wireless virtual network resources. The experimental results show that the model can reduce the cost of mobile network operators, and the request acceptance rate of virtual network is higher than 92%, which improves the success rate of virtual network resource mapping.

关 键 词：无线虚拟网络 资源映射 模拟退火操作 约束条件 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]