Research On Cognitive Network QoS Technology Based On Strategy Of End-Link Cooperation

The development of computer network is evolved from independent network structure to a autonomous multi-domain network. Working mode of network element is no longer"the isolated island", but evolves into distributed cooperation. The appearance of cognitive network embodies this idea incisively and vividly. Compared with traditional network, cognitive network takes end-to-end QoS guarantee of service as a goal, which should owe to swarm of cognitive network element. Each member of swarm effects together, observes real-time network condition, unifies the network history situation simultaneously and predicts future network status. In order to meet special requirements of service transportation and improve integral network performance, they configure, adjust and optimize themselves depending on given strategies.Firstly, QoS guarantee of service for cognitive network end-to-end is considered as goals, and a model based on cooperative strategy of ends and links is proposed. The model considers end-link cooperation idea of cognitive network as a basic, and it implement service transportation for cognitive network with control method of the distributed-centralized combination. Next, profiting from the idea of closed-loop feedback in control theory, an active buffer management algorithm user-oriented is given. It provides different level of users for different service. At the same time, a preliminary study for the implement of scheduled weigh in routers with multi-queue is given. Finally, the algorithm is implemented in a simulation environment and an experiment platform. Related service is deployed at the platform, and a comprehensive analysis on QoS guarantee of service is given. Results show that the monitor and control model, which is based on resource allocation algorithm, can assure different level user's service, and meanwhile related key technology satisfies special demands of cognitive network, and consequently all these enable the deployment of this monitor at cognitive network in future.