  Edge computing (EC) is a promising paradigm providing a distributed computing
solution for users at the edge of the network. Preserving satisfactory quality
of experience (QoE) for users when offloading their computation to EC is a
non-trivial problem. Computation offloading in EC requires jointly optimizing
access points (APs) allocation and edge service placement for users, which is
computationally intractable due to its combinatorial nature. Moreover, users
are self-interested, and they can misreport their preferences leading to
inefficient resource allocation and network congestion. In this paper, we
tackle this problem and design a novel mechanism based on algorithmic mechanism
design to implement a system equilibrium. Our mechanism assigns a proper pair
of AP and edge server along with a service price for each new joining user
maximizing the instant social surplus while satisfying all users' preferences
in the EC system. Declaring true preferences is a weakly dominant strategy for
the users. The experimental results show that our mechanism outperforms user
equilibrium and random selection strategies in terms of the experienced
end-to-end latency.
