基于兴趣度的云VR资源存储方法

The Method for Cloud VR Resource Storage Based on the Interest Measure

针对云上虚拟现实(VR)资源存储过程混乱和部分云存储空间使用不均衡等存储不当问题,提出一种基于兴趣度的云VR资源存储方法。该方法从虚拟现实资源本身关联度着手分析,定义了兴趣度指数,用于量化云VR资源的关联程度。通过兴趣度指数来构建资源放置组,有效减少了存储过程中的移动次数,并利用兴趣度指数改进的深度强化学习算法进行合理的对象存储设备选择,有效提高了云空间整体使用率。实验结果表明:该方法有效地优化了云VR资源存储过程,解决了资源存储不当的问题。

Aiming at the problems of improper storage such as the confusing virtual reality(VR)resource storage process on the cloud and uneven use of some cloud storage space,a method for cloud VR resource storage based on the interest measure is proposed.This method starts with the analysis of the relevancy of virtual reality resources themselves,and defines the interest index,and uses it to quantify the relevance of cloud VR resources.The interest index is used to build resource placement groups to effectively reduce the number of moves in the storage process,and the deep reinforcement learning algorithm improved by the interest index is used to select reasonable object storage devices,which effectively improves the overall utilization of cloud space.The experimental results show that the method effectively optimizes the cloud VR resource storage process and solves the problem of improper resource storage.