Energy Efficient Model And Simulation On WSN

WSN is a self-organizing network formed by a large number of micro sensor nodes through a variety of wireless communication protocols.Because WSN has the characteristics of small size and can be deployed in harsh environment,it has been used more and more widely in recent years,such as military,traffic,environment,disaster relief and so on.But sensors also have less power,so prolonging the work life of nodes and the entire sensor network is a very important goal.In the whole process of data collection,the nodes need to collect data,pass several nodes to the final sink node.So,in addition to standby,the consumption of electricity is mainly data acquisition,receiving other node data and sending data to the upper node.The energy of data acquisition is related to setting parameters,there is not much optimization space.But the energy consumption of receiving and sending data can be reduced by optimizing transmission strategy.In this paper,according to the principle of sensor data receiving and sending,and after actually measuring and verifying,from the perspective of reducing the energy consumption of receiving and sending data,two optimization strategies are proposed.The first is to minimize the number of data packets to reduce the number of sensor data transmission and reception.Based on the data aggregation strategy,an optimization model is proposed and the solution algorithm MinPackets is given.The complexity of this algorithm is low and can be solved in a short time.Taking into account the different requirements of different scenarios on time delay,the model is applied to the different cases of local synchronization with small delay and global synchronization with large delay.Finally,simulations and real node experiments are performed on the scheme.Experimental results show that the model can significantly reduce network energy consumption and improve network lifetime.The network lifetime can be increased by 10%-30%compared with the ShortestPathTree model in the same field.The second strategy is to maximize the number of leaf nodes to enhance thedegree of data aggregation.At the same time,considering the problem of a single optimization goal applied to the second strategy,an optimization model RES-WSN with adjustable performance and power consumption is proposed.With lower solution complexity,the problem can still be solved quickly when the problem scale reaches hundreds of nodes,providing a means for wireless sensor network reliability and power consumption(or between different life standards)to be flexibly adjusted.For the topological connection relations and flow distribution results obtained after the solution,a set of RPL-based deployment scenarios was proposed and implemented with the "multi-instance" approach and the extended DIO options,and the expansion was only carried out within the framework of the agreement.The experimental results show that the adjustment range of RES-WSN for reliability can reach 52.08%,and the adjustment range for energy consumption can reach 60.51%.Especially in the case of pure energy-saving target optimization,the network lifetime(standard 2)is comparable to the other.An extreme situation can be extended by up to 42.54%,which can be extended by 9.23%compared to the foreign study of the ShortestPathTree model.