A Cooperative Partial Computation Offloading Scheme for Mobile Edge Computing Enabled Internet of Things

TLDR

Latency‑sensitive applications are increasingly limited by delay constraints, and partial computation offloading offers a promising way to run them on mobile devices, yet most studies focus only on cloud or MEC alone. This study aims to investigate the cooperation between cloud computing and MEC for computation offloading in IoT. The authors formulate single‑user offloading as a branch‑and‑bound solvable problem and multi‑user offloading as an NP‑hard MILP, then propose an iterative heuristic MEC‑resource‑allocation algorithm to decide offloading dynamically. Simulations show that the proposed algorithm reduces execution latency and improves offloading efficiency compared to existing schemes.

Abstract

With the evolutionary development of latency sensitive applications, delay restriction is becoming an obstacle to run sophisticated applications on mobile devices. Partial computation offloading is promising to enable these applications to execute on mobile user equipments with low latency. However, most of the existing researches focus on either cloud computing or mobile edge computing (MEC) to offload tasks. In this paper, we comprehensively consider both of them and it is an early effort to study the cooperation of cloud computing and MEC in Internet of Things. We start from the single user computation offloading problem, where the MEC resources are not constrained. It can be solved by the branch and bound algorithm. Later on, the multiuser computation offloading problem is formulated as a mixed integer linear programming problem by considering resource competition among mobile users, which is NP-hard. Due to the computation complexity of the formulated problem, we design an iterative heuristic MEC resource allocation algorithm to make the offloading decision dynamically. Simulation results demonstrate that our algorithm outperforms the existing schemes in terms of execution latency and offloading efficiency.