马斯:在多访问边缘计算中,用于资源分配和网络切片的多代理代理关键方法
1Department of Computer Software, Hanyang University, Seoul 04763, Republic of Korea.
Sensors (Basel, Switzerland)
|December 17, 2024
概括
本研究引入了一种新的多代理主体关键资源调度 (MAARS) 算法,用于优化多访问边缘计算 (MEC) 网络中的资源分配和网络切片,显著提高任务完成率.
科学领域:
- 计算机科学 计算机科学
- 电信工程 电信工程 电信工程
- 人工智能的人工智能
背景情况:
- 多访问边缘计算 (MEC) 网络在资源分配和网络切片方面面临挑战,以满足各种服务需求.
- 在核心和边缘网络中有效管理资源对于最大限度地提高任务完成率至关重要.
研究的目的:
- 开发一种新的算法,以优化MEC网络中的资源分配和网络切片.
- 提高动态MEC环境中用户计算任务的任务完成率.
主要方法:
- 提出了一种多个代理人关键资源调度 (MAARS) 算法,集成多个代理人深度决定性政策梯度 (MADDPG) 和软代理人关键 (SAC).
- 该算法将问题分解为高效的核心到边缘切片 (ECS) 和自主资源切片 (ARS) 进行协作和动态资源管理.
主要成果:
- 与基准算法 (基于启发式,DQN,A2C) 相比,MAARS在模拟中表现出更高的性能.
- 关键绩效指标有所改善,包括任务完成率,资源利用率和融合速度.
结论:
- MAARS算法提供了一个可扩展和高效的框架,用于资源优化和MEC中的网络切片.
- 这项研究为现实世界MEC部署提供了实际好处,并建立了新的绩效基准.
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