A Distributed Clustering Based Energy Management Scheme for Heterogenous Wireless Sensor Network

K. A. P, D. Ravi
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Abstract

The Internet of Things (IoT) is an emerging paradigm that offers a wide array of benefits for real-world applications. An IoT system is supported by a network of heterogeneous sensor nodes that collect information about the environment over time. The non-rechargeable batteries and energy constraints limit the network's lifespan. For this reason, controlling energy dissipation is one of the most important considerations when designing communication protocols for sensor networks. The clustering scheme is one of the most efficient ways to help networks be more energy-efficient. However, the majorities of existing protocols do not handle energy distribution among heterogeneous sensor nodes well and are inappropriate. The purpose of this paper is to emphasize cluster head selection criteria and to propose an energy management clustering mechanism that takes heterogeneity into account. A dense deployment of heterogeneous multi-level nodes is considered in the proposed scheme to improve the nodes' stability and power efficiency. The threshold probability for selecting optimal CH nodes is determined by an energy-balanced weighted parameter. The proposed scheme is implemented on a numerical computing tool MatLab. In terms of alive nodes, dead nodes, packets sent to the base station, and processing time, the simulation provides efficient results. When compared to similar existing approaches, the proposed scheme was more successful in terms of network lifetime, stability, delay, and packet delivery.
一种基于分布式聚类的异构无线传感器网络能量管理方案
物联网(IoT)是一种新兴的范例,为现实世界的应用提供了广泛的好处。物联网系统由异构传感器节点网络支持,这些节点随时间收集有关环境的信息。不可充电电池和能量限制限制了网络的使用寿命。因此,控制能量耗散是设计传感器网络通信协议时最重要的考虑因素之一。集群方案是帮助网络提高能源效率的最有效方法之一。然而,现有的大多数协议不能很好地处理异构传感器节点之间的能量分配,是不合适的。本文的目的是强调簇头选择标准,并提出一种考虑异质性的能源管理聚类机制。该方案考虑了异构多级节点的密集部署,以提高节点的稳定性和功耗效率。选择最优CH节点的阈值概率由能量平衡加权参数确定。该方案在数值计算工具MatLab上实现。在活节点、死节点、发送到基站的数据包和处理时间方面,仿真得到了有效的结果。与现有的类似方法相比,该方案在网络生存期、稳定性、延迟和数据包传输方面取得了更大的成功。
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