Computing at the edge is increasingly important as Internet of Things (IoT) devices at the edge generate massive amounts of data and pose challenges in transporting all that data to the Cloud where they can be analyzed. On the other hand, harnessing the edge data is essential for offering cognitive applications, if the challenges, such as device capabilities, connectivity, and heterogeneity can be overcome. This paper proposes a novel three-tier architecture, called EdgeSphere, which harnesses resources of the edge devices, to analyze the data in situ at the edge. In contrast to the state-of-the-art cloud and mobile applications, EdgeSphere applications span across cloud, edge gateways, and edge devices. At its core, EdgeSphere builds on Apache Mesos to optimize resources usage and scheduling. EdgeSphere has been applied to practical scenarios and this paper describes the engineering challenges faced as well as innovative solutions.

翻译：随着物联网设备在边缘产生海量数据，将所有数据传输至云端进行分析面临诸多挑战，边缘计算的重要性日益凸显。另一方面，若能克服设备能力、连接性与异构性等挑战，利用边缘数据对于实现认知应用至关重要。本文提出一种名为EdgeSphere的新型三层架构，该架构通过整合边缘设备资源，实现在边缘侧对数据进行原位分析。相较于当前主流的云与移动应用，EdgeSphere应用可横跨云端、边缘网关及边缘设备。其核心基于Apache Mesos构建，以优化资源利用与任务调度。EdgeSphere已在实践场景中得到应用，本文阐述了所面临的工程挑战及相应的创新解决方案。