长春工程学院学报（自然科学版）2024，Vol.25Issue(1)：73-77,5.DOI:10.3969/j.issn.1009-8984.2024.01.014
FUCS:一种基于用户兴趣与特征融合的数据预处理缓存策略
FUCS:A Fusion of User Interests and Features-Based Data Preprocessing Caching Strategy
摘要
Abstract
In order to reduce the transmission delay of edge cloud fog cooperative networks and improve the storage utilization and prediction accuracy of caching devices,a fusion of user interests and features-based data preprocessing caching strategy(FUCS)is proposed.The K-means algorithm is used to preprocess the data to narrow down the computational domain,a feature fusion module is designed,and the Multi-Head Self-attention is adopted to adapt to the changing patterns of user interests.The simulation results show that the proposed strategy performs better in overall cache hit rate and can significantly reduce the average transmission delay of data,compared with traditional buffering strategies.关键词
边缘缓存/缓存延迟/内容缓存Key words
edge cache/cache latency/content cache分类
信息技术与安全科学引用本文复制引用
王金海,丁言..FUCS:一种基于用户兴趣与特征融合的数据预处理缓存策略[J].长春工程学院学报（自然科学版）,2024,25(1):73-77,5.基金项目
项目基金:国家自然科学基金面上项目(61972054)长春市科技发展计划重点研发项目(21ZY53)吉林省科技发展计划重点研发项目(20210201127GX)吉林省教育科学"十四五"规划课题(GH21364) （61972054）
