Research On Structure Optimization Of Topology Control Algorithm In Wireless Sensor Network

Wireless Sensor Network (WSN) is the integration of intelligent network information system for information collection, information processing and information transmission, and its biggest challenge are the limited power of sensor nodes. In various techniques in wireless sensor network, topology control technology directly affect each protocol and even the whole network performance, good topology control technology can reduce the node energy consumption and prolong the lifetime of the network. This paper mainly studies the Geographical Adaptive Fidelity (GAF), a kind of typical adaptive clustering algorithm of the topology control mechanism. And aiming at the shortcomings of the algorithm, two improved GAF algorithm is proposed. Paper’s main work includes:On the basis of GAF algorithm, put forward the improved GAF algorithm of dividing cells based on the optimal number of cluster heads. The improved algorithm according to the optimal number of cluster heads to divide the cell. In the cluster head selection stage, not only considering the residual energy of nodes and the distances from base station, but also taking into account the node throughput in the cluster head selection stage. Besides,by defining the cluster-head selection function to find the cluster head. And analysis the performance and simulation of improved GAF algorithm under the condition of different base station locations. The simulation results show that the improved GAF algorithm can effectively save energy and the simulation results is consistent with the theoretical analysis.On the basis of the above-mentioned improved algorithm, an improved algorithm based on intersecting circle structure is putted forward. The improved algorithm can increases the area of each cell and node single-hop coverage by using the intersecting circle structure model to divide cells. And choose the nodes in the overlap areas of intersecting circle as transfer nodes to achieve multi-hops routing between the cluster heads. In the cluster head selection stage, using the cluster-head selection function based on throughput and other conditions to choose the cluster head. And the two improved GAF algorithms are compared in terms of the performance through the simulation analysis. The simulation results show that the performance of the improved GAF algorithm based on intersecting circle structure is better than the improved GAF algorithm of dividing cells based on the optimal number of cluster heads.