计算机科学
人气
GSM演进的增强数据速率
移动边缘计算
边缘计算
移动计算
移动设备
主管(地质)
移动电话技术
计算机网络
分布式计算
作者
Jie Liang,Dali Zhu,Haitao Liu,Heng Ping,Ting Li,Hangsheng Zhang,Liru Geng,Yinlong Liu
标识
DOI:10.1109/lcomm.2020.3030329
摘要
With the rapid growth of social network traffic, the design of an efficient caching strategy is crucial in the social content-centric network (SocialCCN). In order to design a more comprehensive popularity prediction caching strategy, in this letter, we proposed a novel architecture that integrates mobile edge computing (MEC) in SocialCCN (MeSoCCN) and proposed multi-head attention based popularity prediction caching strategy in MeSoCCN. Firstly, we proposed a multi-head attention based popularity prediction model (MAPP) that considers multi-dimensional features including history and future popularity, social relationships, and geographic location to predict content popularity. Then, we design a caching strategy based on the prediction results of MAPP. The simulation results show that the proposed MAPP model achieves lower predictive error and the proposed predictive caching strategy improves cache hit rate and reduces hop redundancy in the network.
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