摘要:随着大数据、机器学习等技术的发展，网络流量与任务的计算量也随之快速增长.研究人员提出了内容分发网络（CDN）、边缘计算等平台技术，但CDN只能解决数据存储，而边缘计算存在着难以管理和不能跨集群进行资源调度等问题.容器化技术广泛应用在边缘计算场景中，但目前，边缘计算采取的容器编排策略普遍比较低效，导致任务的计算延迟仍然过长.提出了功能分发网络FDN （function delivery network），一方面为用户提供了访问边缘计算资源的统一接口和容器化的计算平台，无需进行繁琐的计算资源配置；另一方面，FDN平台优化系统的资源利用和任务的计算延迟，能将任务所需的容器编排到合适的边缘计算集群.开发了一种基于启发式的容器编排策略，实现了跨集群的容器编排功能，进一步优化了执行的计算延迟.基于Openwhisk软件实现了FDN，并在中国移动的网络中部署了该系统，而且对FDN和容器编排策略进行测试.实验结果表明，FDN计算平台能够降低任务的计算延迟；同时，启发式容器编排策略的性能相比传统的算法有了较大的提升.



Abstract:With the development of big data and machine learning, the network traffic and data computation are growing fast. Researchers developed the content network delivery (CDN), edge computing, etc. for these challenges. Nevertheless, the CDN only addresses the data storage, and it is still challenging to manage and schedule resources among edge clusters in edge computing. Containerization has been widely employed in edge computing, but the current container orchestrators utilize the inefficient orchestration schemes, which leads to high computation latency. Thisstudy proposes the function delivery network (FDN). On the one hand, FDN provides the interface and containerization computation platform for users to access the edge computing resources. On the other hand, FDN optimizes the resource utilization and computation latency by orchestrating the containers to the appropriate edge clusters. Moreover, a heuristic container orchestrating algorithm is developed that enables the inter-cluster container orchestrating. The FDN system is implemented based on Openwhisk and the FDN system is deployed in China Mobile network, and the FDN system is evaluated. The results show that the proposed FDN system can decrease the task computation latency, and the heuristic container orchestration algorithm outperforms the traditional container orchestration schemes.



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