基于分布式算法在WSN中的能耗最小化优化研究

Optimization of energy minimization algorithm based on distributed in WSN

如何有效利用节点能量并延长网络的生存期是研究无线传感器网络的一个核心问题.在已有的集中式算法的基础上,提出了一种分布式优化的方法,使无线传感网络中无损数据收集时的能量消耗最小化,此方法主要是通过将传输功率和压缩传输速率进行合理的配置来实现,运用拉格朗日对偶分解法,可以把能量最小化这个问题分解为能够被传感节点本身分布式解决的子问题.通过仿真结果可得,分布式算法相比集中式算法能使目标函数更快收敛从而达到能耗最小化.

How to use node energy effectively and prolong the network lifetime is the core issue in the research of wireless sensor network.In this paper,we propose a distributed optimization algorithm that minimizes the energy consumption of lossless data gathering wireless sensor networks by allocating variable transmit power and data compression/transmission rate to each sensor node. Using the Lagrange duality,we decompose the convex energy consumption minimization problem into subproblems,which can be solved by the sensor nodes distributively. A distributed algorithm based on the simulation results can be concluded that compared with the centralized algorithm to minimize energy consumption of the objective function so as to achieve faster convergence.