Closed-Form Delay-Optimal Computation Offloading in Mobile Edge Computing Systems

TL;DR

This paper develops a delay-optimal computation offloading strategy for mobile edge computing systems, using a novel closed-form solution based on Markov decision processes and queue state information, applicable to multi-user scenarios.

Contribution

It introduces a closed-form multi-level water-filling offloading solution derived from an approximate MDP model, considering both local and remote queue states, extending to multi-user MEC systems.

Findings

Proposed scheme outperforms conventional methods in simulations.

Derived closed-form priority functions for different scenarios.

Extended the model from single to multiple MEC servers and MTs.

Abstract

Mobile edge computing (MEC) has recently emerged as a promising technology to release the tension between computation-intensive applications and resource-limited mobile terminals (MTs). In this paper, we study the delay-optimal computation offloading in computation-constrained MEC systems. We consider the computation task queue at the MEC server due to its constrained computation capability. In this case, the task queue at the MT and that at the MEC server are strongly coupled in a cascade manner, which creates complex interdependencies and brings new technical challenges. We model the computation offloading problem as an infinite horizon average cost Markov decision process (MDP), and approximate it to a virtual continuous time system (VCTS) with reflections. Different to most of the existing works, we develop the dynamic instantaneous rate estimation for deriving the closed-form approximate priority functions in different scenarios. Based on the approximate priority functions, we propose a closed-form multi-level water-filling computation offloading solution to characterize the influence of not only the local queue state information (LQSI) but also the remote queue state information (RQSI). A extension is provided from single MT single MEC server scenarios to multiple MTs multiple MEC servers scenarios and several insights are derived. Finally, the simulation results show that the proposed scheme outperforms the conventional schemes.