Optimization of the RFID network in IoT through Hybrid Genetic Algorithmz

Salu George Thandekkattu, Kalaiarasi M
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引用次数: 0

Abstract

Several cutting-edge technologies, like as Radio Frequency Identification (RFID) optimization and sensors, are enabling the Internet of Things (IoT). Using a unique code connected with tags, this radio frequency identification technology allows the sensor to read from a distance without requiring sight contact. Optimal tag coverage, cost efficiency, and quality of service needs are all important considerations when deploying RFID networks. We investigated optimization approaches for RFID in Internet of Things (IoT) devices in this paper. RFID optimization saves processing time, hardware costs, and improves efficiency. Random search strategies based on Artificial Intelligence (AI) are more suited than deterministic methods that are difficult to solve in polynomial time. In this paper, we present a hybrid algorithm that combines PSO and GA features to improve the efficiency of an IoT network system.
基于混合遗传算法的物联网RFID网络优化[j]
一些尖端技术,如射频识别(RFID)优化和传感器,正在使物联网(IoT)成为可能。使用与标签连接的独特代码,这种射频识别技术允许传感器从远处读取而不需要视觉接触。在部署RFID网络时,最佳标签覆盖、成本效率和服务质量需求都是重要的考虑因素。本文研究了物联网(IoT)设备中RFID的优化方法。RFID优化节省了处理时间,硬件成本,并提高了效率。基于人工智能(AI)的随机搜索策略比难以在多项式时间内解决的确定性方法更适合。在本文中,我们提出了一种结合PSO和GA特征的混合算法,以提高物联网网络系统的效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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