Open AccessAn Offloading Algorithm based on Markov Decision Process in Mobile Edge Computing System
Author(s) -
Bingxin Yao,
Boyu Wu,
Siyun Wu,
Jianping Yin,
Danggui Chen,
Limin Liu
Publication year - 2022
Publication title -
international journal of circuits, systems and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.156
H-Index - 13
ISSN - 1998-4464
DOI - 10.46300/9106.2022.16.15
Subject(s) - computer science , markov decision process , mobile edge computing , cloud computing , energy consumption , queue , enhanced data rates for gsm evolution , algorithm , markov process , real time computing , distributed computing , computer network , artificial intelligence , mathematics , engineering , statistics , operating system , electrical engineering
In this paper, an offloading algorithm based on Markov Decision Process (MDP) is proposed to solve the multi-objective offloading decision problem in Mobile Edge Computing (MEC) system. The feature of the algorithm is that MDP is used to make offloading decision. The number of tasks in the task queue, the number of accessible edge clouds and Signal-Noise-Ratio (SNR) of the wireless channel are taken into account in the state space of the MDP model. The offloading delay and energy consumption are considered to define the value function of the MDP model, i.e. the objective function. To maximize the value function, Value Iteration Algorithm is used to obtain the optimal offloading policy. According to the policy, tasks of mobile terminals (MTs) are offloaded to the edge cloud or central cloud, or executed locally. The simulation results show that the proposed algorithm can effectively reduce the offloading delay and energy consumption.