Wireless Sensor Network Deployment And Statistical Analysis

A common deployment strategy for wireless sensor networks(WSN)is to locate sensors based on probability distributions.Some sensor distributions provide an advantage in redundancy,which helps ensure network viability even if multiple sensor nodes are lost in a network attack.Proper initial sensor deployment can greatly reduce the threat of denial of service(DoS)attacks.Although some probability distributions are significantly better than others,how to choose the best sensor distribution as a defense measure is still unknown.In view of the fact that the distribution parameters do not change in the short-term research process,the method of parameter estimation in statistics is used to calculate the results of the point estimation and interval estimation of the distribution parameters for samples of different sizes,which ensures the high accuracy of the distribution parameters and provides theoretical support for the sensor deployment staff.At the same time,the current research mainly focuses on the selection of routing protocols and parameter setting under the existing distribution.This paper adopts the prior distribution and posterior distribution knowledge of bayes estimation,applies bayes gaussian distribution and bayes uniform distribution to network deployment,and studies their parameter correction.For the deployment problem of sensor network under DoS attack,we get the bayesian estimate of distribution parameter real-time correction.The relationship between coverage and distribution parameters under DoS attack is discussed,and the deployment scheme of nodes is obtained on the premise of guaranteeing coverage performance.This deployment strategy provides a decision support system for high coverage,energy efficient sensor distribution.Simulation results show that this routing protocol and sensor deployment can substantially improve WSN performance and network life during network attack.The rest of this paper is organized as follows:In chapter 1,the threats of wireless sensor network(WSN)and denial of service(DoS)attacks are introduced in detail,and some relevant research background is selected to propose our innovative deployment strategy.The second chapter describes WSN routing protocol and the preliminary knowledge of statistics applied in this paper.Chapter 3 describes the principal(AB)based model and how it is implemented.The fourth chapter calculates the bayes gaussian distribution and the parameter correction of the bayes uniform distribution.The case study in chapter 5 illustrates how to use the model to understand temporal network performance.Chapter 6 uses multi-objective functions and pareto frontiers to optimize energy considerations.Chapter 7 summarizes the whole paper.