首页> 外文期刊>Wireless personal communications: An Internaional Journal >Energy Efficient Resource Scheduling Using Optimization Based Neural Network in Mobile Cloud Computing
【24h】

Energy Efficient Resource Scheduling Using Optimization Based Neural Network in Mobile Cloud Computing

机译:在移动云计算中基于优化的神经网络节能资源调度

获取原文
获取原文并翻译 | 示例
           

摘要

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.
机译:移动云计算已成为新兴技术,其中移动计算与云计算集成以处理移动数据。 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,服务质量,安全性和计算成本。 在本文中,为了使总功耗最小化,通过不同的方差和响度实现使用人工神经网络和卷积神经网络模型的神经网络的优化方法。 从实验结果观察到,通过在神经网络中使用优化,功耗降低了53.68%,并使用卷积神经网络获得改进,进一步将功耗降低了30.3%,与最小的根均线误差相比 其他算法。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号