Spatial Feature Aware Genetic Algorithm of Network Base Station Configuration for Internet of Things

Haobin Wang, W. Huangfu, Yaxi Liu, Cheng Gong, Yebing Ren, W. Liu
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引用次数: 1

Abstract

Network configurations, which maximize the accessed number of the sensor devices in IoT subjected to limited active base stations is an important topic. The weakness of traditional genetic algorithms mainly lies in that the spatial feature, i.e., the geometry distribution of base stations, is not considered. A novel genetic algorithm, in which the spatial feature of base stations is taken into account, to obtain the optimal subset of base stations in IoT is proposed. The crossover operation and the mutation operation are designated based on the spatial characteristic. Experiments have been conducted to prove the proposed algorithm for the network configuration.
面向物联网的网络基站配置空间特征感知遗传算法
如何在有限的有源基站条件下使物联网中传感器设备的接入数量最大化,是一个重要的网络配置问题。传统遗传算法的弱点主要在于没有考虑基站的空间特征,即基站的几何分布。提出了一种考虑基站空间特征的遗传算法,以获得物联网中最优基站子集。根据空间特征指定交叉操作和突变操作。实验证明了该算法在网络配置中的有效性。
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