Research On Routing Technology Joint With Resource Allocation In Cognitive Wireless Mesh Network

Wireless mesh network is a new architecture of wireless network, and has the advantages of high speed, high bandwidth, high reliability, easy deployment, high scalability and so on, making it have received extensive attention in the field of research in recent years. Cognitive radio technology allows users to use the idle spectrum opportunistically, which has alleviated the shortage of spectrum resources effectively. Cognitive wireless mesh network combines the superiorities of both wireless mesh network and cognitive radio technology, having great potential to improve resource utilization and network capacity and so on. In this thesis, a routing optimization technology with joint resource allocation is in-depth researched according to the characteristics of cognitive wireless mesh network.For the routing issue in cognitive wireless mesh network, a routing model joint with channel assignment and power control based on SINR interference model is proposed. To minimize network latency, a single pathway routing optimization algorithm based on ant colony algorithm and particle swarm optimization algorithm is presented. Using the nested optimization method, the outer layer is used to find the single-path routing path by using ant colony algorithm, and the inner layer is used to do channel allocation and power control by using particle swarm. With the goal of maximizing the network traffic flow, a multi-path routing optimization algorithm based on bacterial foraging algorithm and linear programming is proposed. The outer layer finds the suitable channel and power of node with bacterial foraging algorithm. The inner layer computes the multi-path routing path by using linear programming to prevent link failure. A series of experimental results validate the effectiveness of the proposed algorithms.To further improve network transmission performance, a resource allocation and dynamic routing optimization mechanism based on network flow forecasting in cognitive wireless mesh network is proposed. By monitoring the route flow require in real time, it can save the data with timestamp, the data is used to forecast the network route flow require in a short time of future. While allocating resource, all the route flow require including the real route flow require and the forecasted flow require needs to be satisfied, and the resource allocation and routing selection is conducted based on the route flow require. Further, a discrete simulation system of resource allocation and dynamic routing based on route flow require forecasting is presented. The result of experiments shows that the proposed mechanism in this thesis can improve the network transmission performance of network significantly and satisfy the dynamic network route flow require.