The technology of QoS routing has become a great challenge in Wireless Mesh Networks (WMNs). There exist a lot of literatures on QoS routing in WMNs, but the current algorithms have some deficiencies, such as high com...The technology of QoS routing has become a great challenge in Wireless Mesh Networks (WMNs). There exist a lot of literatures on QoS routing in WMNs, but the current algorithms have some deficiencies, such as high complexity, poor scalability and flexibility. To solve the problems above, a multipath routing algorithm based on traffic prediction (MRATP) is proposed in WMNs. MRATP consists of three modules including an algo-rithm on multipath routing built, a congestion discovery mechanism based on wavelet-neural network and a load balancing algorithm via multipath. Simulation results show that MRATP has some characteristics, such as better scalability, flexibility and robustness. Compared with the current algorithms, MRATP has higher success ratio, lower end to end delay and overhead. So MRATP can guarantee the end to end QoS of WMNs.展开更多
Multipath routing mechanism is vital for reliable packet delivery, load balance, and flexibility in the open network because its topology is dynamic and the nodes have limited capability. This article proposes a new m...Multipath routing mechanism is vital for reliable packet delivery, load balance, and flexibility in the open network because its topology is dynamic and the nodes have limited capability. This article proposes a new multipath switch approach based on traffic prediction according to some characteristics of open networks. We use wavelet neural network （WNN） to predict the node traffic because the method has not only good approximation property of wavelet, but also self-learning adaptive quality of neural network. When the traffic prediction indicates that the primary path is a failure, the alternate path will be occupied promptly according to the switch strategy, which can save time for the switch in advance The simulation results show that the presented traffic prediction model has better prediction accuracy; and the approach based on the above model can balance network load, prolong network lifetime, and decrease the overall energy consumption of the network.展开更多
文摘The technology of QoS routing has become a great challenge in Wireless Mesh Networks (WMNs). There exist a lot of literatures on QoS routing in WMNs, but the current algorithms have some deficiencies, such as high complexity, poor scalability and flexibility. To solve the problems above, a multipath routing algorithm based on traffic prediction (MRATP) is proposed in WMNs. MRATP consists of three modules including an algo-rithm on multipath routing built, a congestion discovery mechanism based on wavelet-neural network and a load balancing algorithm via multipath. Simulation results show that MRATP has some characteristics, such as better scalability, flexibility and robustness. Compared with the current algorithms, MRATP has higher success ratio, lower end to end delay and overhead. So MRATP can guarantee the end to end QoS of WMNs.
基金the National Natural Science Foundation of China (60573141 and 60773041)Hi-Tech Research and Development Program of China (2006AA01Z201, 2006AA01Z439, 2007AA01Z478)+5 种基金the Natural Science Foundation of Jiangsu Province (BK2005146)High Technology Research Programme of Jiangsu Provinc (BG2006001)High Technology Research Programme of Nanjing (2007RZ127)Foundation of National Laboratory for Modern Communications (9140C1101010603)Key Laboratory of Information Technology processing of Jiangsu Province (kjs06006)The Young Teachers Program of Anhui Province (2006jql044)
文摘Multipath routing mechanism is vital for reliable packet delivery, load balance, and flexibility in the open network because its topology is dynamic and the nodes have limited capability. This article proposes a new multipath switch approach based on traffic prediction according to some characteristics of open networks. We use wavelet neural network （WNN） to predict the node traffic because the method has not only good approximation property of wavelet, but also self-learning adaptive quality of neural network. When the traffic prediction indicates that the primary path is a failure, the alternate path will be occupied promptly according to the switch strategy, which can save time for the switch in advance The simulation results show that the presented traffic prediction model has better prediction accuracy; and the approach based on the above model can balance network load, prolong network lifetime, and decrease the overall energy consumption of the network.
