论文标题
使用强化学习的HDF的智能复制管理
Intelligent Replication Management for HDFS Using Reinforcement Learning
论文作者
论文摘要
用于云计算的存储系统将大量商品计算机合并为一个大型存储池。与购买和维护大型机器相比，它在不可靠的，动态的网络上提供了高性能存储。在本文中，我们检查将加固学习（RL）应用于系统领域问题是否可行。我们的实验表明，RL模型是可比的，甚至超过了其他启发式方法，用于块管理问题。但是，我们的实验在可伸缩性和保真度方面受到限制。尽管我们的表述不是很实际，但将强化学习应用于系统领域，可以为现有启发式方法提供良好的替代方法。
Storage systems for cloud computing merge a large number of commodity computers into a single large storage pool. It provides high-performance storage over an unreliable, and dynamic network at a lower cost than purchasing and maintaining large mainframe. In this paper, we examine whether it is feasible to apply Reinforcement Learning(RL) to system domain problems. Our experiments show that the RL model is comparable, even outperform other heuristics for block management problem. However, our experiments are limited in terms of scalability and fidelity. Even though our formulation is not very practical,applying Reinforcement Learning to system domain could offer good alternatives to existing heuristics.
