C4O:在 WSN 中使用 coati 优化算法进行基于链的合作聚类

Preet Kamal Singh, Harmeet Singh, Jaspreet Kaur
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引用次数: 0

摘要

为了向低功耗物联网设备提供传感服务,无线传感器网络(WSN)将专门的传感器组织成网络。由于传感器节点的电池很难更换或充电,因此能源使用是 WSN 最重要的设计问题之一。对于能量受限的网络来说,聚类技术对保护电池寿命至关重要。通过有策略地选择簇头(CH),可以平衡网络的负载,从而减少能量消耗,延长系统寿命。虽然聚类技术在文献中得到了广泛应用,但基于链的聚类概念尚未得到探讨。因此,在本文中,我们采用了基于链的聚类架构来进行网络数据传播。此外,在 CH 选择方面,我们采用了 coati 优化算法,该算法是最近提出的,与其他优化算法相比有显著改进。在这种方法中,选择 CH 时考虑的参数包括能量、节点密度、距离和网络的平均能量。仿真结果表明,在网络寿命、稳定期(第一个节点死亡)、传输速率和网络电力储备方面,基于集群的路由竞争算法都有极大的改进。
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C4O: chain-based cooperative clustering using coati optimization algorithm in WSN
In order to provide sensing services to low-powered IoT devices, wireless sensor networks (WSNs) organize specialized transducers into networks. Energy usage is one of the most important design concerns in WSN because it is very hard to replace or recharge the batteries in sensor nodes. For an energy-constrained network, the clustering technique is crucial in preserving battery life. By strategically selecting a cluster head (CH), a network's load can be balanced, resulting in decreased energy usage and extended system life. Although clustering has been predominantly used in the literature, the concept of chain-based clustering has not yet been explored. As a result, in this paper, we employ a chain-based clustering architecture for data dissemination in the network. Furthermore, for CH selection, we employ the coati optimisation algorithm, which was recently proposed and has demonstrated significant improvement over other optimization algorithms. In this method, the parameters considered for selecting the CH are energy, node density, distance, and the network’s average energy. The simulation results show tremendous improvement over the competitive cluster-based routing algorithms in the context of network lifetime, stability period (first node dead), transmission rate, and the network's power reserves.
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