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

机译:用于物联网网络基站配置的空间特征意识到遗传算法

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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.
机译:网络配置最大化IOT中的传感器设备的访问数量,而受到有限的有效基站是一个重要的主题。传统遗传算法的弱点主要在于,不考虑空间特征,即基站的几何分布,是基站的几何分布。一种新颖的遗传算法,其中考虑了基站的空间特征,提出了获得物联网中基站的最佳子集。基于空间特性指定交叉操作和突变操作。已经进行了实验以证明该网络配置的算法。

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