Research On Clustering And Cooperative Routing In Ad Hoc Network

Ad hoc networks have the characteristics of multi-hop communication and with no any existing network infrastructure. The features of limited resource and bandwidth and highly dynamical topologies bring the new challenge on networking structure and routing protocol. This paper focus on clustering algorithm and routing protocol.Firstly, a clustering algorithm based on Probability Degree (PD) is proposed by using Markov process. The algorithm forecasts the next time connectivity of the link between two random nodes based on that of current time, the node of the highest link connectivity probability is selected as the Cluster Head. The simulation results show that the number of clusters of PD is less than that of Highest Connectivity Degree algorithm (HD), without overlapping nodes so that maintenance cost is effectively decreased. The number of cluster members shows minor differences, so it illustrates that PD algorithm has higher efficiency and without increasing the burden of Cluster Head, although the clustering number decreases. The problem of regroup and out-of-sequence of data packet in real-time multimedia transmission is due to the mobility and highly dynamic topological of Ad hoc networks. Using the UDP protocols, a scheme of real-time multimedia communication in Ad hoc networks based on Probability Degree clustering is given.And then, with the improvement in the intelligence of Unmanned Aerial Vehicle (UAV), it is possible to organize the Ad hoc network with UAV nodes. In addition, the Ad hoc network needs the neighbor nodes' cooperation to forward packets, but it is contrary to the personal benefit of a node, such as power and bandwidth. The research of cooperative communication between UAV nodes is promising. Take the actual situation of UAV-Ad hoc network into account, six main indicators were considered: remaining capacity, sending rate, transmitting rate, transmission speed, transmission quality, and anti interference. By Analytical Hierarchy Process (AHP) to calculate the indicators weights, using Hopfield neural network to evaluate nodes action indicators, and then the nodes' category and the corresponding operation were deduced. Cooperative Communication Strategy in UAV-Ad hoc Network based on Hopfield neural network was given. It could consider various indicators, and effectively manages the network nodes. Training is simple and does not need a large number of samples. In addition, the network response time is very short. Experimental results show that evaluation results consist with the indicators' weights.Finally, based on the valuation results by Hopfield neural network, Cooperative Communication Routing (CCR) was proposed. CCR can protect the nodes which are lack of electricity; when there is more than one path to the same destination, it selects the path which include the least selfish nodes even no selfish nodes in routing lookup. The reliability of data transmission is strengthened. The results of simulation experiment show that the unreliable transmission path rate of the CCR becomes better than that of Dynamic Source Routing Protocol (DSR) with the increase of the network scale.