The sensor node reporting plays a important role in the propose of wireless sensor networks. In addition to coverage, shape and region is also important in WSN to limit the power utilization which is taken as the current research work for successful sensor network structure. Neighbor Position Verification strategy with the help of fully distributed cooperative scheme enabled each node to acquire the neighbor locations but did not acquire data aggregation accuracy during node exploitation. Decentralized inference process using Decentralized Power Iteration algorithm permitted every representative to track the algebraic sensor network connectivity but was not effective in deploying the sensor nodes with higher throughput ratio. To dynamically deploy the nodes in sensor network, Two Dimensional Gaussian distribution based Dynamic Node Deployment model is developed in this paper. The 2D-GDDNE model initially identifies the directional position based on the angle measurement of the sensor node location. The angle measurement points of the sensor nodes are compute using 2-D Statistical Triangulation algorithm. The identified directional position further places the animatedly deployed sensor nodes with Gaussian distribution model. The Gaussian distribution is performed on the 2D sensor network spaces to accurately deploy the sensor nodes with higher data aggregation accuracy. Simulation work is carried out on computing the experimental value on the factors such as node deployment efficiency, throughput level and data aggregation accuracy rate on deployed node. © 2016 IEEE.