Abstract: In this paper, a lifetime optimizing scheme is proposed to combine different applications, network service, network deployment and optimizing algorithms together. The deployment of network can be guided by this scheme through placing more nodes where higher service quality is needed. In this way, the wasted energy can be reduced efficiently. The statistic model is employed to unify different applications and optimizing algorithms in this scheme, thus application requirements and network service ability are quantified. To give a concrete scenario validating the feasibility of this scheme, an assessment method is presented based on the energy of the network nodes, with the upper bound of wasted energy being calculated. A quantization process of network density called density iterative process(DIP) is put forward subsequently to find out the distribution law of the network density which will provide wider space for lifetime optimizing. Theorems in this paper show that if the relaying function can be approximated to simple functions of initial relaying function and the network density, our quantization process DIP can get convergence. And furthermore, it is proved that DIP will get uniform convergence when the initial strength of serving request is not a constant function. Simulations also show that this process can get convergence and the solution can make the energy of different network regions burnt evenly and thus prolong the lifetime of WSN.