提出了系统设计全生命周期的网络生存期优化体系模型,该模型利用先验统计信息将不同的应用与优化算法统一起来,并以评估结果作为反馈调节网络使之达到网络生存期最大限度的优化；构建了一种优化体系的具体评估模型,利用网络能耗分布量化具体应用服务需求,使用网络能量分布度量网络服务能力,并通过量化结果计算网络能量浪费的上限；给出了一种网络密度调节方法,用以发现有利于生存期优化的网络密度分布规律,并对该方法的收敛性以及解的有效性进行了理论证明.模拟实验结果表明该评估模型和密度调节方法可以有效控制网络能耗分布,发现有利于延长网络生存期的密度规律,从而验证了网络生存期优化体系的有效性.%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.
展开▼
