Energy Holes Detection And Energy Supplement Strategy In WSN

One of the prominent problems in Wireless Sensor Networks(WSN)is how to reduce the energy consumption of WSN nodes to extend the lifetime.There are many problems that lead to the short lifetime of the network,among which the formation of energy hole is one of the main reasons.There are many factors to form a hole in the energy.The most important thing is the principle and deployment of WSN:the lower node carries out the data transmission to the upper node in a multi hop manner,while the parent node receives the data of multiple nodes at the same time when it receives the data from the lower node.This leads to more energy consumption when parent nodes collect and send data than the lower nodes when they collect and send data.It can be seen that the closer the SINK area is,the easier energy hole is.In order to solve the problem of energy cavitation caused by the excessive energy consumption of nodes in the near SINK region,a mathematical model is designed to describe the situation of data transmission in the ideal situation.At the same time,by improving the traditional data traffic transfer algorithm,a kind of network traffic can be designed for a specific scale.A data transfer algorithm for solving the problem.The strategy is based on the measured value of real experiment,that is,the energy consumed by the unit byte and the full MTU byte is basically the same.This shows that the energy consumed by the entire network can be adjusted by controlling the amount of data sent by each node,thus alleviating the formation of energy holes to prolong the WSN lifetime.On the basis of the network traffic mathematical model,according to the previous experimental data,it is found that the energy consumed by the received data is about 60%of the energy consumed by the data,and the sending unit bytes are close to the energy consumed by the full frame data,so the amount of data can be sent from the control by the method of data aggregation.The energy consumption of the whole network is controlled by the angle.The minimum cost maximum flow is used to optimize the proposed mathematical model,so that it can describe the network more intuitively.The model of the minimum cost maximum flow is a convex optimization model.According to the convex optimization model,the difficulty is not high,the time and the number of iterations all belong to the convergent range,and the solution is global optimal.Secondly,the branch and bound method in operational research is used to plan the data transmission flow in the network.The traditional branch and bound method is improved according to solving large-scale problems.On the basis of the original optimization problem,the improved branch and bound method can effectively converge to the faster solution of the more large-scale problem,the time and the number of iterations,and ensure that the solution is global optimal.The four parameters are compared with the existing policies in terms of lifetime,total network energy consumption,energy utilization,and the sum of residual nodes in the network.The results show that our strategy outperforms the existing optimization strategies,which can effectively alleviate the formation of energy holes and extend the lifetime of WSN.