一种基于遗传算法的通信网拓扑优化方法

A Method for Optimizing Communication Network Topology based on Genetic Algorithm

研究通信网可靠性问题,以对等结构的通信网为研究对象,从拓扑结构角度出发,构建了通信网可靠性优化模型,提出了基于改进的遗传算法来求解该模型。针对基于自然连通度的目标函数,设计了变量编码,改进了选择操作,定义了交叉操作和变异操作。实验表明,随着迭代次数的增加,自然连通度值呈上升趋势,网络拓扑结构由“分散外围”至“较密核心-外围”。仿真分析优化后通信网的结构属性,验证了通信网拓扑优化模型,并采用遗传算法求解了模型的有效性和可行性。网络拓扑结构优化后,改变了网络度分布,其中度小节点数增加,而度大节点数减少。在随机攻击与蓄意攻击下,经过算法优化后的通信网可靠性都有提升。

This paper explores the reliability of communication network.Taking the communication network of peer-to-peer structure as the research object,from the perspective of topological structure,the reliability optimization model of communication network is constructed,and an improved genetic algorithm is proposed to solve the model.For the objective function based on natural connectivity,it designs variable coding,improves the selection operation,and defines the crossover operation and mutation operation.Experiments indicate that as the number of iterations increases,the natural connectivity value shows an upward trend,and the network topology changes from“dispersed periphery”to“closer core-periphery”.The simulation analyzes the structural attributes of the optimized communication network,and verifies the effectiveness and feasibility of the communication network topology optimization model and the use of genetic algorithm to solve the model.After the network topology is optimized,the network degree distribution is changed,in which the number of low-degree nodes increases,while the number of high-degree nodes decreases.The reliability of the communication network after the optimization of the algorithm proposed in this paper is improved under both random and deliberate attacks.