Aimed at the shortages of traditional large-scale network topology discovery model in network performance, integrity and real-time performance, when acquiring topology information. According to the characteristics of easy expansion and fast convergence with OSPF protocol, a network topology discovery model OTDM is proposed, based on OSPF. The model adopts passive monitoring to obtain network topology information. After obtaining the link state update (LSU) packet in the OSPF protocol, the Router LSA and Network LSA is analysed to obtain the regional network topology. Then Summary Network LSA is analysed, obtained through boundary routing, to obtain the interregional network topology. So a complete network topology is obtained. The experimental results show that the model can accurately and completely acquire large-scale network topology, which can make up for the shortages of existing large-scale network topology discovery technology.

Abstract. Spam is a major problem of the Internet, because it can cause pollution and waste of resources in the network environment. Therefore,spam filtering is necessary. After spam filtering methods study, presents a support vector machine and artificial immune system combines filtration methods and filtration methods using MATLAB simulation experiments.

Abstract. According to the traditional spam filtering method effectively identify unknown characteristics and variability of the ability is not strong, according to the basic principle of biological immune system and multi agent technology proposed based on immune multi-agent spam filtering model. The model can realize the information exchange of each Agent, enhance the whole model "memory" mechanism, and effectively extract the information and variation characteristics of spam. Spam experimental simulation results show that the model and other models compared has better performance, can effectively improve the correct rate of spam model characteristics and reduce the false alarm rate.