首页> 外文期刊>International journal of computer science and network security >Adaptive Parameters of an Enhanced Backoff Method by Using an Artificial Neural Network Between mobiles in an Industrial Domain
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Adaptive Parameters of an Enhanced Backoff Method by Using an Artificial Neural Network Between mobiles in an Industrial Domain

机译:工业领域中移动设备之间使用人工神经网络的增强型退避方法的自适应参数

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The purpose of this study is to discuss the exchanges between mobiles moving in an industrial environment. A simulation approach has been chosen in order reach this study. This novel method aimed to minimize the exchange time between mobiles within an 802.11 cell. The optimization of this time was carried out by modifying the binary exponential aspect of the Backoff algorithm as a first phase, where as a second phase this modified and enhanced BEB method was supported by a Neural Network Function to give us precise output parameters. Those outputs will be learned by the Neural Network Function and will be used in the NS2 simulation to get the new results of the time delay to compare them with the standard BEB method results.
机译:这项研究的目的是讨论在工业环境中移动的移动设备之间的交换。为了进行这项研究,选择了一种仿真方法。这种新颖的方法旨在最大程度地减少802.11小区内移动设备之间的交换时间。此时间的优化是通过将Backoff算法的二进制指数方面修改为第一阶段来进行的,其中在第二阶段中,此修改和增强的BEB方法得到了神经网络功能的支持,从而为我们提供了精确的输出参数。这些输出将通过神经网络功能学习,并将用于NS2仿真中以获得新的延时结果,并将其与标准BEB方法结果进行比较。

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