Coverage And Routing Optimization Algorithms And Applications Study Based On Wireless Sensor Networks

Wireless sensor networks as one of the three future global high-tech, is one of the current research focuses. Wireless sensor network technology has been a hot research topic at the environment, especially traffic monitoring. Focus on the practical application of this subject, there are tremendous social benefits. In this paper, the structure of wireless sensor network nodes, the architecture and features of wireless sensor networks are introduced. The reason why it is suitable for monitoring wireless sensor networks is just decided by the characteristics of its own. It is through the introduction of wireless sensor networks to point out the two improved aspects-the improvements of the node coverage algorithm and the tree routing algorithm. Then it applied them to the traffic control system model. The optimized algorithm in the application of the traffic control system model is proved by OMNET++simulation software.First, this paper studies the improvements of the node coverage algorithm. It is mainly through the Derived formula of the SECA(the effective coverage of the nodes) and the RECA(the effective using of the nodes).The purpose is using the least amount of nodes as possible to maximize the coverage area, or in some measure region,to minimize the redundant nodes, thus to use the number of nodes as little as possible to reduce costs. The studies are based on full seamless coverage. Meanwhile, to link theory with practice application, in the dense regions, for the extension of the life of the network, the node density should be increased appropriately, because the energy consumption of the fast data transfer volume is huge. Secondly, this improved tree algorithm in the zigbee protocol, is mainly based on the systematic analysis of existing tree algorithm in the zigbee protocol,application scenarios,the requirements on the nodes and the algorithm results, particularly its strengths and weaknesses. Then a new tree algorithm is proposed. The new algorithm includes the calculation of the original tree algorithm and the method to calculate the address of the next hop node. The innovation of the new algorithm is:First, put forward in the new algorithm by adding a neighbor table. Then nodes in the search for the next hop node will take into account other nodes within a radius measured. Thereby it chooses the path with less hops and reducing energy consumption, especially reduces the energy consumption of closing to the root key node. Second, the node set minimum energy threshold. Then it can find a new path in time, and avoid prematurely depleting energy result in networks because of the repeated using of a path or node.Then, the research result on wireless sensor network improvements is applied into practice. The practical application of this model can basically respond to the main function of intelligent transportation. One of the hot issues in the traffic---the path optimization and adjustment of the traffic in urban road network is further studied. Its implementation of its functions is detailed as an example. In practice, it is not a direct application, but combined with the actual situation. Through the establishment of a road model, the improvements of the node coverage algorithm and the tree routing algorithm are applied. Then the practical application of the model is improved with reality. In the application of the improved node coverage algorithm, nodes should be separately covered under the effect of different node. In the application of the improved tree routing algorithm, it should be set according to actual conditions, taking also into account the actual cost such as the routing cost.Finally, the improvement of the model is proved by the OMNET++simulation software. First, the advantages of OMNET++applicable to this study are introduced. Secondly, the simulation system of the structure of this tree algorithm is described. Then, the improvements of the node coverage algorithm and the tree routing algorithm are simulated. The simulation results show the improvement in this paper could effectively save the network energy consumption and prolong network life.