Computation Offloading with Online Matching Algorithm in Mobile Edge Computing Networks

Abstract

Mobile edge computing (MEC) distributes computation and storage resources to network edges, which enables computation-intensive and latency-critical applications for resource-constrained devices. In a MEC network, computation offloading decision plays a critical role, which allocates specific computation nodes (CNs) for different tasks. However, few existing works consider the practical scenario in which different tasks have different arrival time and relative computation deadlines. In this paper, the computation offloading problem with dynamic service requests is considered, and at the same time we assume different computation tasks have different response deadlines and computation deadlines. Taking the quality of service (QoS) requirements of all users and the utility constraints of tasks and CNs into consideration, the service-oriented and CN- oriented optimization problem are formulated, respectively. Next the online matching game is introduced to model the dynamic association between the tasks and CNs, and then the rank based final acceptation (RBFA) matching algorithm is proposed to solve the problems. Finally, we validate the effectiveness of the proposed algorithm through the simulation results.