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首页> 外文会议>IEEE International symposium on Personal, Indoor, and Mobile Radio Communications >An in-network caching scheme based on betweenness and content popularity prediction in content-centric networking
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An in-network caching scheme based on betweenness and content popularity prediction in content-centric networking

机译：以内容为中心的网络中基于中间性和内容流行度预测的网络内缓存方案

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Content-centric Networking (CCN) is considered as a promising architecture to achieve reliable content distribution at large scale. One of the key research items of CCN is cache strategy, and most of the existing approaches consider little of the dynamicity of user interests. In this paper, we present a new cache policy, named as the betweenness and content popularity prediction (BEACON). Betweenness measures the importance of nodes in the whole network, and content popularity represents the user preference for service contents. By taking into account both network topology characteristics and flow distribution, the load of network and server is optimized. Moreover, we use the gray model to predict the content popularity, tracking the trend of user interest. The simulation results demonstrate that the BEACON scheme can effectively improve the cache hit rate, shorten access distance and reduce the delay of transmission.
机译：以内容为中心的网络（CCN）被认为是实现大规模可靠内容分发的有前途的体系结构。 CCN的关键研究项目之一是缓存策略，并且大多数现有方法都很少考虑用户兴趣的动态性。在本文中，我们提出了一种新的缓存策略，称为中间性和内容流行度预测（BEACON）。中间性衡量的是整个网络中节点的重要性，而内容的受欢迎程度则代表了用户对服务内容的偏好。通过同时考虑网络拓扑特征和流量分布，可以优化网络和服务器的负载。此外，我们使用灰色模型来预测内容的受欢迎程度，跟踪用户兴趣的趋势。仿真结果表明，BEACON方案可以有效提高缓存命中率，缩短访问距离，减少传输延迟。

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