Research on Application of BP Neural Network Based on Genetic Algorithm in Heartbeat Mechanism

Huan Qiao, Zhaohua Long
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Abstract

In view of the current instant messaging applications developed based on the Android platform that all use the traditional heartbeat mechanism, which has the problem of greatly consuming client CPU and power, a method for dynamically adjusting the heartbeat interval is proposed. This method uses genetic algorithm to optimize the BP neural network model to predict the current network congestion, and then dynamically adjusts the heartbeat interval according to the prediction result combined with the dichotomy. Use the development tool Android Studio to develop an instant messaging application App based on the Android operating system, and test the fixed heartbeat and the above-mentioned adaptive scheme respectively. The experimental results show that the adaptive scheme can make the application find the optimal heartbeat interval for the current network faster. Which can reduce the consumption of client CPUand power.
基于遗传算法的BP神经网络在心跳机制中的应用研究
针对目前基于Android平台开发的即时通讯应用均采用传统的心跳机制,存在占用客户端CPU和功耗较大的问题,提出了一种动态调整心跳间隔的方法。该方法利用遗传算法对BP神经网络模型进行优化,预测当前网络拥塞情况,然后根据预测结果结合二分类动态调整心跳间隔。使用开发工具Android Studio开发一个基于Android操作系统的即时通讯应用App,并分别对固定心跳和上述自适应方案进行测试。实验结果表明,该自适应方案可以使应用程序更快地找到当前网络的最佳心跳间隔。这样可以减少客户端cpu和功耗的消耗。
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