  Edge computing promises to offer low-latency and ubiquitous computation to
numerous devices at the network edge. For delay-sensitive applications, link
delays can have a direct impact on service quality. These delays can fluctuate
drastically over time due to various factors such as network congestion,
changing traffic conditions, cyberattacks, component failures, and natural
disasters. Thus, it is crucial to efficiently harden the edge network to
mitigate link delay variation as well as ensure a stable and improved user
experience. To this end, we propose a novel robust model for optimal edge
network hardening, considering the link delay uncertainty. Departing from the
existing literature that treats uncertainties as exogenous, our model
incorporates an endogenous uncertainty set to properly capture the impact of
hardening and workload allocation decisions on link delays. However, the
endogenous set introduces additional complexity to the problem due to the
interdependence between decisions and uncertainties. We present two efficient
methods to transform the problem into a solvable form. Extensive numerical
results are shown to demonstrate the effectiveness of the proposed approach.
