Joint caching and transmission in the mobile edge network: An multi-agent learning approach | |
Mi,Qirui1; Yang,Ning1; Zhang,Haifeng1; Zhang,Haijun3; Wang,Jun2 | |
2021-12-07 | |
会议日期 | 2021-12-7 |
会议地点 | Madrid, Spain |
英文摘要 | Joint caching and transmission optimization problem is challenging due to the deep coupling between decisions. This paper proposes an iterative distributed multi-agent learning approach to jointly optimize caching and transmission. The goal of this approach is to minimize the total transmission delay of all users. In this iterative approach, each iteration includes caching optimization and transmission optimization. A multi-agent reinforcement learning (MARL)-based caching network is developed to cache popular tasks, such as answering which files to evict from the cache and which files to storage. Based on the cached files of the caching network, the transmission network transmits cached files for users by single transmission (ST) or joint transmission (JT) with multi-agent Bayesian learning automaton (MABLA) method. And then users access the edge servers with the minimum transmission delay. The experimental results demonstrate the performance of the proposed multi-agent learning approach. |
内容类型 | 会议论文 |
源URL | [http://ir.ia.ac.cn/handle/173211/57248] ![]() |
专题 | 复杂系统认知与决策实验室_群体决策智能团队 |
通讯作者 | Yang,Ning |
作者单位 | 1.Institute of Automation, Chinese Academy of Sciences 2.University College London 3.University of Science and Technology Beijing |
推荐引用方式 GB/T 7714 | Mi,Qirui,Yang,Ning,Zhang,Haifeng,et al. Joint caching and transmission in the mobile edge network: An multi-agent learning approach[C]. 见:. Madrid, Spain. 2021-12-7. |
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