How to Cache Important Contents for Multi-modal Service in Dynamic Networks: A DRL-based Caching Scheme
arxiv(2024)
摘要
With the continuous evolution of networking technologies, multi-modal
services that involve video, audio, and haptic contents are expected to become
the dominant multimedia service in the near future. Edge caching is a key
technology that can significantly reduce network load and content transmission
latency, which is critical for the delivery of multi-modal contents. However,
existing caching approaches only rely on a limited number of factors, e.g.,
popularity, to evaluate their importance for caching, which is inefficient for
caching multi-modal contents, especially in dynamic network environments. To
overcome this issue, we propose a content importance-based caching scheme which
consists of a content importance evaluation model and a caching model. By
leveraging dueling double deep Q networks (D3QN) model, the content importance
evaluation model can adaptively evaluate contents' importance in dynamic
networks. Based on the evaluated contents' importance, the caching model can
easily cache and evict proper contents to improve caching efficiency. The
simulation results show that the proposed content importance-based caching
scheme outperforms existing caching schemes in terms of caching hit ratio (at
least 15
of hops (up to 27
reduction).
更多查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要