Cluster-based route convergence method based on network state graph model
To address the challenges of time-varying node connectivity and frequent link failures in tactical communica-tion networks under conditions of strong adversarial and high-mobility operations,which result in frequent route conver-gence and short effective transmission times,a cluster-based route convergence method based on network state graph model(OSPF-CSG)was proposed.Firstly,link states were obtained based on the statistical characteristics of Hello mes-sages,and node states were characterized using aggregated link state features to construct the network state graph model.Secondly,the neighbor state machine's state transition triggers were improved,and two new OSPF message types were developed to design an active/passive association mechanism for complete adjacency relationships.Finally,on this basis,a cluster head bootstrap algorithm,node clustering algorithm,and inter-cluster connection algorithm were proposed to achieve cluster-based routing convergence.Simulation results show that,in eight different network topologies and under different link damage conditions,OSPF-CSG achieves an average reduction of 82%in the total number of route conver-gences,a reduction in routing overhead by 70%on average,and an improvement in packet delivery rate by 60%on aver-age compared to the traditional OSPF protocol's route convergence algorithm.
network state graphnode clusteringroute convergenceOSPF protocol
万方数据
维普
