  Edge computing has been recently introduced as a way to bring computational
capabilities closer to end users of modern network-based services, in order to
support existent and future delay-sensitive applications by effectively
addressing the high propagation delay issue that affects cloud computing.
However, the problem of efficiently and fairly manage the system resources
presents particular challenges due to the limited capacity of both edge nodes
and wireless access networks, as well as the heterogeneity of resources and
services' requirements. To this end, we propose a techno-economic market where
service providers act as buyers, securing both radio and computing resources
for the execution of their associated end users' jobs, while being constrained
by a budget limit. We design an allocation mechanism that employs convex
programming in order to find the unique market equilibrium point that maximizes
fairness, while making sure that all buyers receive their preferred resource
bundle. Additionally, we derive theoretical properties that confirm how the
market equilibrium approach strikes a balance between fairness and efficiency.
We also propose alternative allocation mechanisms and give a comparison with
the market-based mechanism. Finally, we conduct simulations in order to
numerically analyze and compare the performance of the mechanisms and confirm
the theoretical properties of the market model.
