无线传感器网络簇形成与簇头选择的节能算法

Ravinder M, Vikram Kulkarni
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引用次数: 1

摘要

传感器和执行器技术的进步与数据通信相结合,正在提高不同应用的控制和自动化领域的标准。基于IEEE 802.15.4的家庭区域网络(HAN)被认为适用于智能电网应用中的高级计量基础设施。本文研究了无线传感器网络在汉能通信中的应用。传感器数据通过簇头(CH)传送到接收器。本文提出的工作是在可用的集群节点中确定适当的CH。在此基础上,提出了一种针对异构WSN的高效簇形成和簇头选择算法(EEA-CFCHS)。该方法考虑了WSN网络中所有不同类型节点的能量退化阈值。每个CH和集群节点根据阈值进入下一轮。每一轮结束时计算CH剩余能量。如果剩余的能量小于阈值,网络开始构建一个新的集群并选举一个新的CH。降低了能耗,大大增加了稳定周期。在该算法中,MATLAB仿真显示了如何提高网络的生存期。与ESRA和P-SEP协议相比,EEA-CFCHS可将WSN的稳定周期提高42%,将网络寿命提高72%,将网络寿命提高62%,将网络寿命提高73.16%。
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Energy-Efficient Algorithm for Cluster Formation and Cluster Head Selection for WSN
Advancements in sensors and actuator technology incorporated with data communication are enhancing the standards of control and automation areas for different applications. The Home area network (HAN) is based on IEEE 802.15.4 is considered for applications like Advanced metering infrastructure in Smart grid applications. In this paper, Wireless Sensor Network is considered for HAN. The sensor data is communicated to the sink via Cluster heads (CH). The work proposed in this paper is identifying a proper CH, among the available cluster nodes. Based on the above we are proposing a novel algorithm Energy-Efficient Algorithm for Cluster formation and Cluster Head selection (EEA-CFCHS) for heterogeneous WSN. The proposed methodology takes into account the energy degeneracy threshold value for all different kinds of nodes in a WSN network. Each CH and cluster nodes proceed to the following round based on the threshold value. Each round ends with a calculation of the CH residual energy. The network begins building a new cluster and electing a new CH, if the amount of energy left is less than the threshold value. The energy consumption is lowered as a result, and the stability period is greatly increased. In this algorithm, the simulation in MATLAB shows how to improve the network's lifetime. When compared to the ESRA and P-SEP protocols, the EEA-CFCHS for WSN improves the stability period by 42 %, 72% the network lifespan by 62%, and the network lifetime by 73.16%.
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