基于个人计算机的智能家居边缘计算系统
发布时间：2018-11-06 19:52
【摘要】：考虑边缘计算的作用与智能家居的需求,以节约计算资源及提高计算资源利用率为前提,将边缘计算应用于智能家居环境,基于个人计算机平台构建智能家居边缘计算系统。利用现有的虚拟化、容器等技术将多种云服务汇聚到个人计算机平台,形成本地的辅助计算单元,为用户提供边缘计算服务。通过服务管理程序与智能网关的协同工作,设计节能调度算法,实现系统节能管理。测试结果表明,在计算资源有限的情况下,该系统相比单纯使用云计算系统可提供更高的服务质量及更好的扩展性,且易于部署和管理。
[Abstract]:Considering the role of edge computing and the demand of smart home, the edge computing is applied to the environment of smart home on the premise of saving computing resources and improving the utilization rate of computing resources, and the edge computing system of intelligent home is constructed based on personal computer platform. By using the existing virtualization, container and other technologies, various cloud services are converged to personal computer platforms to form local auxiliary computing units to provide edge computing services for users. Through the cooperation of service management program and intelligent gateway, the energy saving scheduling algorithm is designed to realize the energy saving management of the system. The test results show that the system can provide higher quality of service, better scalability and easier deployment and management than using cloud computing system in the case of limited computing resources.
【作者单位】： 上海交通大学计算机科学与工程系;
【基金】：国家自然科学基金(61202026,61332001,61502302)
【分类号】：TN929.5;TP391.44;TU855
[Abstract]:Considering the role of edge computing and the demand of smart home, the edge computing is applied to the environment of smart home on the premise of saving computing resources and improving the utilization rate of computing resources, and the edge computing system of intelligent home is constructed based on personal computer platform. By using the existing virtualization, container and other technologies, various cloud services are converged to personal computer platforms to form local auxiliary computing units to provide edge computing services for users. Through the cooperation of service management program and intelligent gateway, the energy saving scheduling algorithm is designed to realize the energy saving management of the system. The test results show that the system can provide higher quality of service, better scalability and easier deployment and management than using cloud computing system in the case of limited computing resources.
【作者单位】： 上海交通大学计算机科学与工程系;
【基金】：国家自然科学基金(61202026,61332001,61502302)
【分类号】：TN929.5;TP391.44;TU855
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