Truthful Computation Offloading Mechanisms for Edge Computing

TL;DR

This paper introduces a truthful mechanism for computation offloading in edge computing that optimizes resource allocation, ensuring users report preferences honestly and improving latency performance.

Contribution

It presents a novel algorithmic mechanism design approach for truthful computation offloading, addressing preference misreporting and resource optimization in edge computing.

Findings

Mechanism ensures truthful preference reporting as a weakly dominant strategy.

Outperforms existing strategies in reducing end-to-end latency.

Achieves system equilibrium with optimized resource allocation.

Abstract

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.