The importance of real-time wireless data transfer is rapidly increasing for Internet of Things (IoT) applications. For example, smart glasses worn by a doctor need to transmit real-time data to a hospital information system, which performs face detection and recognition, for real-time interaction with recognized patients within a certain deadline, which is ideally a few hundred milliseconds. Other emerging IoT applications, e.g., structural health monitoring, clinical monitoring, and industrial process automation, also require real-time wireless data transfer. Those applications have critical demands for real-time and energy-efficient communication through wireless medium. However, it is very challenging to support stringent timing constraints energy-efficiently through wireless medium due to its inherent unreliability and timing-unpredictability. Fortunately, heterogeneous radios are becoming increasingly available in modern embedded devices, offering new opportunities to use multiple wireless technologies to accommodate the needs of real-time applications. In this paper, we formulate the runtime radio selection and data partitioning for real-time IoT applications as an Integer Linear Programming (ILP) problem and present an optimal algorithm that makes quick and optimal decisions when selecting between two radios, a heuristic algorithm for the platforms with more radios, and a runtime algorithm that reduces deadline miss ratio when facing tight deadlines.

对于物联网（IoT）应用程序，实时无线数据传输的重要性正在迅速提高。例如，医生戴的智能眼镜需要将实时数据传输到医院信息系统，该系统执行面部检测和识别，以便在一定的期限（理想的几百毫秒）内与已识别的患者进行实时交互。其他新兴的物联网应用，例如结构健康监测，临床监测和工业过程自动化，也需要实时无线数据传输。这些应用对通过无线介质进行实时节能通信具有至关重要的要求。然而，由于其固有的不可靠性和时序不可预测性，通过无线介质高效地支持严格的时序约束非常具有挑战性。幸运的是，现代嵌入式设备中越来越多地使用异构无线电，这为使用多种无线技术来满足实时应用的需求提供了新的机会。在本文中，我们将实时物联网应用的运行时无线电选择和数据分区公式化为整数线性规划（ILP）问题，并提出了一个解决方案。在两个无线电之间进行选择时可以做出快速，最佳决策的最佳算法，具有更多无线电的平台的启发式算法以及在面临紧迫的期限时降低期限错率的运行时算法。