Zhang Ying, Yang Guangyuan, Zhang Bin
College of Information Engineering, Shanghai Maritime University, Shanghai 201306, China.
Sensors (Basel). 2020 Feb 18;20(4):1114. doi: 10.3390/s20041114.
When an industrial wireless sensor network (WSN) is seriously disturbed and intentionally attacked, sometimes it fails easily, even leading to the paralysis of the entire industrial wireless network. In order to improve the invulnerability of networks, in this paper, the scale-free network in complex networks is taken as the research object, and the industrial WSN with scale-free characteristics is modeled. Based on the advantages of the fireworks algorithm, such as strong searching ability and diversity of population, a so-called fireworks and particle swarm optimization (FW-PSO) algorithm is proposed, which can improve the global search ability and convergence speed effectively. The proposed FW-PSO algorithm is used to optimize the network topology and form a network with the largest natural connectivity, which can effectively promote the ability of network to resist the cascade failure problem. The dynamic invulnerability of the optimized network under highest-degree (HD) attack and lowest-degree (LD) attack strategies, as well as the static invulnerability under random attack, were evaluated respectively. Simulation experiments show that the industrial WSN optimized by FW-PSO can significantly improve the performance of the dynamic and static invulnerabilities compared with the initial network and the networks optimized by the other two existing algorithms.
当工业无线传感器网络（WSN）受到严重干扰和蓄意攻击时，有时会很容易出现故障，甚至导致整个工业无线网络瘫痪。为了提高网络的抗毁性，本文以复杂网络中的无标度网络为研究对象，对具有无标度特性的工业WSN进行建模。基于烟花算法搜索能力强、种群多样性等优点，提出了一种烟花与粒子群优化（FW - PSO）算法，该算法能有效提高全局搜索能力和收敛速度。将所提出的FW - PSO算法用于优化网络拓扑结构，形成具有最大自然连通性的网络，可有效提升网络抵抗级联故障问题的能力。分别评估了优化后的网络在最高度（HD）攻击和最低度（LD）攻击策略下的动态抗毁性以及在随机攻击下的静态抗毁性。仿真实验表明，与初始网络以及另外两种现有算法优化后的网络相比，经FW - PSO优化的工业WSN能显著提高动态和静态抗毁性的性能。
