The mobile cloud computing has become an emerging technology where the mobile computing is integrated with cloud computing to process the mobile data. Besides the advantages of mobile cloud computing, there are some issues which include power consumption, resource scarcity, quality of service, security and computational cost. In this paper, in order to minimize total power consumption with better performance, the neural network based optimization methods using artificial neural network and convolutional neural network models were implemented by varying variance and loudness. From the experimental results it is observed that, by using optimization in the neural network, the power consumption has been reduced by 53.68% and obtained improvement using convolutional neural network which further reduced the power consumption by 30.3% with minimum root mean square error compared with other algorithms.

移动云计算已成为一种新兴技术，其中移动计算与云计算集成在一起以处理移动数据。除了移动云计算的优势外，还有一些问题，包括功耗，资源稀缺性，服务质量，安全性和计算成本。为了使总功耗最小，性能更好，本文通过改变方差和响度来实现基于神经网络的优化方法，该方法采用了人工神经网络和卷积神经网络模型。从实验结果可以看出，通过在神经网络中使用优化，功耗降低了53.68％，并且通过卷积神经网络获得了改进，从而进一步降低了30％的功耗。