This paper is based on the premise that the power-efficiency and time-scheduling of wireless sensor networks would be optimized.Analytical models are established on the performances about the time scheduling of both the nodes themselves and their coordination which aims to enhance the network integrity.The optimal frontier of the portfolios that comes from nodes power consummation and time-power tradeoff are presented by utilizing the mean-variance model.Hereafter,the paper presents the heuristic conclusions involved in the arrangement of time-scheduling,keeping the network equilibrium,and making full use of the power endowment.

The paper preseats an efficient way to improve the network coverage by artificially deploying the critical Sink nodes.Thus,a study is made to find the best Sink node with the practical swarm optimizer(PSO) algorithm.Simulation shows that PSO algorithm is an easier and reliable way to improve the capability and integrity of networks.

This paper designs evaluation method based on the grey theory which aims at evaluate the usage of Wireless Sensor Networks in rail traffic. With the features of the facts that: The requested data sizes for assessment via grey theory method are not big, distribution rules of the data samples arc not obliged,and the evaluation workload is small, we use grey theory to verify each index mark in current evaluation system. Hereafter, the detailed assessment example is taken out to prove that the index mark getting from this method has practical significance and performs efficiently.

Due to the fact that it plays an important role to improve the connectivity and coverage of Wireless Sensor Networks, it is considered to be efficient to improve the coverage by artificially deploying the critical Sink nodes. In this paper, we use Particle Swarm Optimizer algorithm to find out the best position of sink nodes deployment in the whole network area and then optimize the Wireless Sensor Network by adding sink nodes after generating a quantity of nodes to constitute Wireless Sensor Networks at random. Hereafter, by simulation based on a random network to prove that : (1) intelligent algorithms are worthy of considering and efficiently to be utilized in the network topological deployment and keeping the network integrity, (2) the Partial Swarm Optimization is much algorithmically easier and reliable, (3) Intelligent computation is a kind of optimal methodology to improve the network integrity.