Average age of information optimization in Mobile Edge Computing Networks

Huiji Zheng; Sicong Yu; Xinyuan Qiu; Xiaolong Cui; Li Zhu

doi:10.1117/12.2639193

15 July 2022 Average age of information optimization in Mobile Edge Computing Networks

Huiji Zheng, Sicong Yu, Xinyuan Qiu, Xiaolong Cui, Li Zhu

Proceedings Volume 12258, International Conference on Neural Networks, Information, and Communication Engineering (NNICE 2022); 1225820 (2022) https://doi.org/10.1117/12.2639193
Event: International Conference on Neural Networks, Information, and Communication Engineering (NNICE 2022), 2022, Qingdao, China

Abstract

Age of Information(AoI) is a novel metric to measure freshness of data in status update scenarios proposed by academia in recent years. Real-time applications need to transmit data packets for status update to the target node as soon as possible. However, due to the data density, the limited computing capacity of edge devices and the influence of the environment, the problems of intensive computation and high delay are caused. Mobile edge computing (MEC) is a new computing mode that extends cloud computing power closer to the user, where computing offloading and other technologies promise to solve those problems. We mainly studies the AoI optimization in MEC networks, in which data freshness and offloading strategy play an important role. Firstly, we propose the average AoI minimization problem for MEC network scenarios, and propose a multi-agent deep reinforcement learning(DRL) algorithm called Federated Multi-Agent Actor-Critic (Fed-MAAC). Federated learning is used to train agents to improve algorithm performance and data security. At the same time, we conducted experiments in gym, a popular simulation environment in reinforcement learning, and compared Fed-MAAC with baseline algorithm. The simulation results show that this algorithm is superior to other algorithms in average AoI optimization performance.

Citation Download Citation

Huiji Zheng, Sicong Yu, Xinyuan Qiu, Xiaolong Cui, and Li Zhu "Average age of information optimization in Mobile Edge Computing Networks", Proc. SPIE 12258, International Conference on Neural Networks, Information, and Communication Engineering (NNICE 2022), 1225820 (15 July 2022); https://doi.org/10.1117/12.2639193

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KEYWORDS

Sensors

Data modeling

Clouds

Environmental sensing

Data centers

Computer simulations

Data processing

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