摘要
为改善大规模Web3D场景的加载效率,提出一种基于DR(Dead reckoning)预测的大规模Web3D场景预加载机制,结合DR航迹预测的算法和基于历史路径的兴趣路径聚类算法,将航迹领域中路径预测和交通领域中路径聚类应用到虚拟场景加载领域中,提出一种Web3D场景的预加载机制。实验与研究表明,通过该算法实现的预加载机制可以显著地提高数据的传输效率,优化大规模Web3D场景的加载速度,有效地提高用户在Web3D场景中的漫游体验,为优化大规模Web3D场景的加载机制提出了新思路。
In order to improve the loading efficiency of large-scale Web3D scene,a mechanism based on DR prediction is proposed.It combines the DR track prediction algorithm and historical path-based interest path clustering algorithm to track the field.The medium path prediction and path clustering in the traffic domain are applied to the virtual scene loading field,and a preloading mechanism of the Web3D scene is proposed.Experiment results show that the preloading mechanism can significantly improve the data transmission efficiency,optimize the loading speed of large-scale Web3D scene,and effectively improve the roaming experience of users in Web3D scene.It provides a new way to the loading mechanism.
作者
张惠娟
郭欣琪
王冬青
贾金原
Zhang Huijuan;Guo Xinqi;Wang Dongqing;Jia Jinyuan(Tongji University,School of Software Engineering,Shanghai 201804,China)
出处
《系统仿真学报》
CAS
CSCD
北大核心
2020年第7期1341-1348,共8页
Journal of System Simulation
基金
国家自然科学基金重点项目(U19A2063)。
关键词
预加载
WEB3D
DR预测
路径聚类
preloading
Web3D
dead reckoning prediction
path clustering
