Application of novel swarm intelligence algorithm for congestion control in structural health monitoring

Vijayalakshmi Senniappan, J. Subramanian, A. Thirumal
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引用次数: 4

Abstract

Buildings today are a complex integration of structures, systems and technology. Sensors are increasingly being installed in buildings to gather data about the various factors which helps to monitor the health of the structural components. Energy efficiency and network congestion are the most common issues faced by the sensor nodes. The proposed piece of work, uses a bio inspired swarm intelligence algorithm to improve the energy efficiency of the sensor nodes and mitigates congestion by forming clusters. The proposed method employes Biography Based Krill Herd algorithm for improving the network performance. The results of the proposed method, when compared with other classical evolutionary optimizations, has shown an increase of 42.11% of the network lifetime.
新型群智能算法在结构健康监测中的应用
今天的建筑是结构、系统和技术的复杂集成。越来越多的传感器被安装在建筑物中,以收集有关各种因素的数据,这些因素有助于监测结构部件的健康状况。能源效率和网络拥塞是传感器节点面临的最常见问题。提出的一项工作,使用生物启发的群体智能算法来提高传感器节点的能量效率,并通过形成集群来缓解拥塞。该方法采用基于传记的Krill Herd算法来提高网络性能。结果表明,与其他经典的进化优化方法相比,该方法的网络寿命提高了42.11%。
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