Guo Wenzhong, Hong Wei, Zhang Bin, Chen Yuzhong, Xiong Naixue
College of Mathematics and Computer Science, Fuzhou University, Fuzhou 350116, China.
School of Computer Science, Colorado Technical University, Colorado Springs, CO 80907, USA.
Sensors (Basel). 2014 Sep 11;14(9):16972-93. doi: 10.3390/s140916972.
Mobile security is one of the most fundamental problems in Wireless Sensor Networks (WSNs). The data transmission path will be compromised for some disabled nodes. To construct a secure and reliable network, designing an adaptive route strategy which optimizes energy consumption and network lifetime of the aggregation cost is of great importance. In this paper, we address the reliable data aggregation route problem for WSNs. Firstly, to ensure nodes work properly, we propose a data aggregation route algorithm which improves the energy efficiency in the WSN. The construction process achieved through discrete particle swarm optimization (DPSO) saves node energy costs. Then, to balance the network load and establish a reliable network, an adaptive route algorithm with the minimal energy and the maximum lifetime is proposed. Since it is a non-linear constrained multi-objective optimization problem, in this paper we propose a DPSO with the multi-objective fitness function combined with the phenotype sharing function and penalty function to find available routes. Experimental results show that compared with other tree routing algorithms our algorithm can effectively reduce energy consumption and trade off energy consumption and network lifetime.
移动安全是无线传感器网络(WSN)中最基本的问题之一。对于一些失效节点,数据传输路径将受到损害。为了构建一个安全可靠的网络,设计一种优化能量消耗和聚合成本的网络寿命的自适应路由策略至关重要。在本文中,我们解决了无线传感器网络的可靠数据聚合路由问题。首先,为确保节点正常工作,我们提出了一种提高无线传感器网络能量效率的数据聚合路由算法。通过离散粒子群优化(DPSO)实现的构建过程节省了节点能量成本。然后,为了平衡网络负载并建立可靠的网络,提出了一种具有最小能量和最长寿命的自适应路由算法。由于这是一个非线性约束多目标优化问题,本文提出了一种结合表型共享函数和惩罚函数的多目标适应度函数的离散粒子群优化算法来寻找可用路由。实验结果表明,与其他树形路由算法相比,我们的算法能够有效降低能量消耗,并在能量消耗和网络寿命之间进行权衡。