Abstract
AbstractThe development of multimedia content continuously encourages the appearances of new multimedia applications. Meanwhile, Device to Device (D2D) is regarded as an important 5G technology that creates a direct connection between two mobile devices. We combine the content sharing traits in D2D network situations in response to the problem of massive amounts of multimedia content being distributed. As a result, in this paper, we provide a popularity‐based information mining and content placement strategy for blind popularity distribution in D2D scenarios. To analyze the cache hit performance in D2D networks under the presumption of deterministic content popularity, we first construct a D2D content caching framework. Then, we design a multiarm bandits model and suggest a single and multicache placement policy based on online learning for blind popularity in D2D networks. Finally, the experimental results demonstrate that the proposed method achieves better convergence and a better cache hit ratio than the other strategies.
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