  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%.
