Offloading is a popular way to overcome the resource and power constraints of networked embedded devices, which are increasingly found in industrial environments. It involves moving resource-intensive computational tasks to a more powerful device on the network, often in close proximity to enable wireless communication. However, many Industrial Internet of Things (IIoT) applications have real-time constraints. Offloading such tasks over a wireless network with latency uncertainties poses new challenges. In this paper, we aim to better understand these challenges by proposing a system architecture and scheduler for real-time task offloading in wireless IIoT environments. Based on a prototype, we then evaluate different system configurations and discuss their trade-offs and implications. Our design showed to prevent deadline misses under high load and network uncertainties and was able to outperform a reference scheduler in terms of successful task throughput. Under heavy task load, where the reference scheduler had a success rate of 5%, our design achieved a success rate of 60%.

翻译：卸载是克服网络嵌入式设备（在工业环境中日益常见）资源与功耗限制的常用方法，其核心是将计算密集型任务迁移至网络中性能更强的设备（通常邻近部署以实现无线通信）。然而，许多工业物联网（IIoT）应用存在实时性约束。通过具有延迟不确定性的无线网络卸载这类任务带来了新的挑战。本文旨在通过提出面向无线工业物联网环境的实时任务卸载系统架构与调度器来深化对上述挑战的理解。基于原型系统，我们评估了不同系统配置，并探讨其权衡关系与潜在影响。实验表明，我们的设计在高负载及网络不确定性条件下可有效防止截止时间错失，并在成功处理任务吞吐量方面优于参考调度器。在参考调度器成功率仅为5%的重任务负载场景下，本设计实现了60%的成功率。