Qiu Shaoming, Zhao Jiancheng, Zhang Xuecui, Li Ao, Wang Yahui, Chen Fen
Communication and Network Laboratory, Dalian University, Dalian 116622, China.
North Automatic Control Technology Institute, Taiyuan 030006, China.
Sensors (Basel). 2023 Aug 31;23(17):7572. doi: 10.3390/s23177572.
Sensor nodes are widely distributed in the Internet of Things and communicate with each other to form a wireless sensor network (WSN), which plays a vital role in people's productivity and life. However, the energy of WSN nodes is limited, so this paper proposes a two-layer WSN system based on edge computing to solve the problems of high energy consumption and short life cycle of WSN data transmission and establishes wireless energy consumption and distance optimization models for sensor networks. Specifically, we propose the optimization objective of balancing load and distance factors. We adopt an improved sparrow search algorithm to evenly distribute sensor nodes in the system to reduce resource consumption, consumption, and network life. Through the simulation experiment, our method is illustrated, effectively reducing the network's energy consumption by 26.8% and prolonging the network's life cycle.
传感器节点广泛分布于物联网中，并相互通信以形成无线传感器网络（WSN），这在人们的生产生活中发挥着至关重要的作用。然而，WSN节点的能量有限，因此本文提出一种基于边缘计算的两层WSN系统，以解决WSN数据传输中高能耗和生命周期短的问题，并建立了传感器网络的无线能量消耗和距离优化模型。具体而言，我们提出了平衡负载和距离因素的优化目标。我们采用改进的麻雀搜索算法，使传感器节点在系统中均匀分布，以减少资源消耗、能耗和网络寿命。通过仿真实验，对我们的方法进行了说明，有效降低了网络能耗26.8%，并延长了网络生命周期。
