无线传感器网络中的分布式遗传算法

Distributed Genetic Evolution in WSN

受地形、气候、电磁干扰、节点分布等多重因素的影响,传统无线传感器不能很好的适应现复杂多变的测控环境,特别是较大规模的无线传感网络的健壮性和协同能力受到了复杂环境的挑战。分布式遗传算法在成熟的遗传算法基础上扩展了分布式协同机制,在可接受的复杂度范围内,提升了算法的健壮性。在WSN中引入分布式遗传算法,显著增强了网络的分布式并行特性,提升了节点协同能力和网络自组织的健壮性。通过发光二极管灯亮频率实验、同构无线网络和异构无线网络下稳定性实验和动态自适应环境变化实验,证明了分布式遗传算法能够很好地解决WSN中节点的扩展限制问题,并且提升了WSN的多变环境适应能力。

Influenced by multiple factors such as terrain, climate, electromagnetic interference and node distribution, the traditional wireless sensor can＇t well adapt to the current complex measurement and control environment, especially the robustness of large - scale wireless sensor network and collaborative ability by complex environment challenge. Distributed genetic algorithm based on the mature genetic algorithm extends the distributed collaborative mechanism, and improves the robustness of the algorithm in the complexity of the acceptable range. The introduction of a distributed genetic algorithm in the WSN, has significantly enhanced the characteristics of distributed parallel network and improved the interoperability of network nodes and the robustness of the organization. By leds light frequency experiment, homogeneous and heterogeneous wireless network, wireless network stability experiment and dynamic adaptive environmental change experiment, it proves that the distributed genetic algorithm can effectively solve the limitation of the expansion of the WSN nodes, and finally improve the adaptability of the WSN in the changeful environment.