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首页> 外文期刊>Wireless personal communications: An Internaional Journal >Data Transmission Using K-Means Clustering in Low Power Wide Area Networks with Mobile Edge Cloud
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Data Transmission Using K-Means Clustering in Low Power Wide Area Networks with Mobile Edge Cloud

机译:使用移动边缘云的低功耗广域网中的K-means群集数据传输

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摘要

Low-power, long-range wireless communication has become important for IoT applications in wide space. A Low-Power Wide Area Network (LPWAN) has been proposed to support wireless communication. It provides very long communication distances with low data rates and uses a very simple transmission mechanism to deliver data packets over long distances. The simple transmission mechanism does not consider device characteristics according to generated data. If priority according to the device characteristics is considered during data transmission, the transmission efficiency of each service can be improved. Therefore, this paper proposes data transmission considering device characteristics. The proposed method employs a k-means clustering algorithm to classify devices according to the traffic characteristic. Each group of classified devices has different priority, and the wireless channel access time is determined by that priority. Using different channel access times according to priority allows end-devices to avoid collisions and improve transmission efficiency in LPWAN with long delay. The proposed method is compared to typical transmission methods in an LPWAN through the performance evaluation by computer simulations and its transmission efficiency is validated.
机译:低功耗,远程无线通信对宽空间的IOT应用变得重要。已经提出了低功耗广域网(LPWAN)来支持无线通信。它提供了具有低数据速率的非常长的通信距离,并使用非常简单的传输机制来提供长距离的数据包。简单的传输机制不考虑根据所生成的数据的设备特性。如果在数据传输期间考虑根据设备特性的优先级,则可以提高每个服务的传输效率。因此,本文提出了考虑设备特征的数据传输。该方法采用K-Means聚类算法来根据流量特性对设备进行分类。每组分类设备具有不同的优先级,并且无线信道访问时间由该优先级确定。根据优先级使用不同的通道访问时间允许终端设备避免在LPWAN中采用碰撞并提高LPWAN的传输效率。将所提出的方法与LPWAN中的典型传输方法进行比较,通过计算机模拟的性能评估,并且验证了其传输效率。

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