摘要
为有效管理嵌入式系统,尤其是减少移动终端的电源功耗,设计一种更加精确的动态电源管理方案。在Linux平台上运行,基于API行为特点,利用BP神经网络算法进行应用类型预测,通过对应用类型的预测,提前对系统状态进行调整。实验结果表明,在不影响系统性能的前提下,该方案可有效降低功耗,实现对嵌入式设备电源的实时、动态管理。
In order to effectively manage embedded systems, especially reduce power consumption of the mobile terminal,this paper proposes a power management scheme,which is based on the design of a more refined dynamic power management scheme. It is based on Application Program Interface （ API ） behavioral characteristics, using BP neural network algorithm to predict the type of application,through the effective prediction of application types. It can adjust the system state in advance,without affecting system performance,effectively reducing power consumption,realize the power of real-time embedded devices and dynamic management.
出处
《计算机工程》
CAS
CSCD
北大核心
2015年第6期269-273,279,共6页
Computer Engineering
基金
国家自然科学基金资助重点项目(41231170-5)
国家级大学生创新基金资助项目(201210359016)
安徽省高校自然科学研究基金资助重点项目(KJ2010A272)
