Radar network is a typical complex adaptive system (CAS). The command and control (C2) of radar network plays a big part in improving the quality of the acquired data and the anti-damage ability of radar network. On the basis of analyzingradar networkcombat process,a method based on Agent was proposed to establish command and control (C2) modelof radar network.The structure of the Agent was put forward and based on that, theadaptive C2 model was represented as a 6-tuple system.The simulation experimentwas made in the presumed background and the results showed that the modeling of adaptive command and control of radar network was implemented.

Worm infection is a critical problem for network application technology and security. In order to decrease the destruction of worm to network application technology, a worm containment method using benign worms was proposed, and an approach of high-fidelity modeling on packet-level of worm propagation and containment with benign worms was designed. The experiment results show that benign worms can contain the infection of malicious worms effectively, and the initial locality of worm, the delay time between the start time of benign worm and malicious worm, background traffic of the network will affect the propagation and containment of worms.

Network traffic is the key factor to describe the adaptive business of Internet. As Internet becomes key battlefield of cyber warfare, how to model the Internet traffic at the macro level has become a hot research topic in war simulation and cyber warfare. Focusing on the global undersea cable system which serves as the backbone of the Internet, this paper proposes an Internet traffic modeling method based on multi-commodity flow. This method can estimate the traffic demand between each pair of regions, generate traffic flow distribution in global undersea cable system, and support adaptive adjustment of Internet traffic according to damage situation of undersea cable system in a crisis. Finally, the method is validated by an example.