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Cache Partitioning and Caching Strategies for Device-to-Device Caching Systems

机译:用于设备到设备缓存系统的缓存分区和缓存策略

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摘要

The amount of traffic in wireless networks is increasing exponentially, and this problem can be mitigated using device-to-device (D2D) caching technology, which installs a cache on a mobile end device. Devices can reduce the cell load through self-offloading via content in their own cache and D2D offloading using content in others’ caches. However, especially in the early stage of D2D caching systems, a limited number of devices with a small storage might be used, and it is required to develop a caching scheme with excellent performance despite the small cache size. Regarding content popularity, which is common to most users, the preference probability values are not concentrated on some pieces of content, making it difficult to achieve satisfactory performance using a small cache. On the other hand, when considering individual users, content preferences may contain large values for specific content based on individual characteristics. In addition, the performance can be improved by considering short-term content preferences that reflect changes in content preferences over time or newly created content during peak hours. In this article, the hit ratio is divided into six parts considering self- and D2D offloading, common and individual user preferences, and little and large temporal changes in content preferences during peak hours. We also conceptually divide the cache of a helper into six areas in relation to the six parts of the hit ratio, and discuss cache partitioning and proactive caching strategies according to the environment.
机译:无线网络中的流量量呈指数增长,并且可以使用设备到设备(D2D)缓存技术来缓解该问题,该技术在移动端设备上安装高速缓存。设备可以通过在自己的缓存中通过内容和D2D卸载在其他人的高速缓存中的内容中通过自卸载来减少小区负载。然而,特别是在D2D缓存系统的早期阶段,可能使用具有小存储器的有限数量的设备,并且需要开发高速缓存大小的高度性能的缓存方案。关于大多数用户的内容流行度,偏好概率值不集中在某些内容上,使得难以使用小型缓存来实现令人满意的性能。另一方面,在考虑各个用户时,内容偏好可以基于各个特征对特定内容包含大值。另外,通过考虑在高峰时段期间反映内容偏好的变化或新创建的内容,可以通过考虑反映内容偏好的变化或新创建的内容来提高性能。在本文中,命中比率分为六个部分,考虑到自我和D2D卸载,常见和个人用户偏好,并且在高峰时段内的内容偏好的时间变化很小和大的时间变化。我们还在概念上将帮助者的缓存分为六个区域,与命中率的六个部分相比,并根据环境讨论缓存分区和主动缓存策略。

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