Research And Simulated Implementation Of Trusted QoS Routing For Cognitive Networks

The internet has becoming an essential part of everyone’s daily life, as the information and communication technology developing so fast. However, the scale of the networks and the amount of the customers are increasing rapidly. Mobile internet devices are highly popular in our society. The internet is facing scalability, heterogeneous, dynamic, and many other challenges. Especially when the multimedia appears in the network as a new type of application, people desire that there is an appropriate Quality of Service. At the same time, network security event which increased year by year also greatly influence the use of the network. People are eager to have a secure and reliable network. Cognitive networks and trusted networks are proposed fro solving the above problems.This thesis researches the trustworthiness of the networks and QoS routing mechanisms. In this thesis, trusted QoS routing mechanisms are designed for cognitive networks which include the evaluation and control of trust of network nodes, unicast routing and multicast routing mechanisms. The evaluation and control of trust uses a sliding window and window sill as a dynamic evaluation mechanism. Through the analysis of behaviors of network nodes, trustworthiness can be extracted, so that it can be used for the routing later. This thesis references the basic theory of cognitive science and the intelligence of human immune system and artificial immune system. Cognitive behavior of networks is designed in immune organs and they are inserted into the network model to improve the performance of QoS routing. This thesis designs a random routing algorithm based on probability. It is an ingenious combination of cognitive behavior and routing algorithm which has good adaptability. In the initial phase of the networks, the algorithm can make the network traffic balance and avoid network congestion. As the network continues to run, the algorithm will find some nodes that appear better performance. Besides, the resources occupation rate is also considered, so that network traffic wouldn’t concentrate at a few links. In addition, this thesis introduces several intelligent optimation algorithms to optimize the initial routing results. With the help of these intelligent optimation algorithms, the final result can have better QoS performance. The trusted QoS routing mechanisms for cognitive networks presented in this thesis are implemented and simulated on the Microsoft Visual. Studio2008platform and compared with classical algorithms. The results show that the trusted QoS routing mechanisms are better at providing QoS and some other respects.