GHCC:基于分组和分层的移动边缘计算协同缓存

Dewang Ren, Xiaolin Gui, Wei Lu, Jian An, Huijun Dai, Xin Liang
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引用次数: 13

摘要

移动边缘计算(MEC)已经成为一种有前途的技术,可以解决指数级增长的数据流量所带来的挑战。它不仅支持移动用户卸载计算,还可以缓存和传递流行的内容给移动用户。在本文中,我们的目标是在MEC网络中设计新颖的内容缓存策略,以减少访问延迟并提高能源效率。首先,开发了基于mec的分布式内容分发网络,以支持本地用户的请求。在此基础上,基于用户的分布特征和mec的位置,提出了一种基于分组的分层协同缓存策略。仿真结果证明,在平均访问延迟、总能耗和内容多样性方面,我们的缓存策略比其他基准策略更有效。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
GHCC: Grouping-based and hierarchical collaborative caching for mobile edge computing
Mobile edge computing (MEC) has emerged as a promising technique to address the challenge arising from the exponentially increasing data traffic. It not only supports mobile users to offload computations but also caches and delivers popular contents to mobile users. In this paper, we aim at designing novel content caching strategies in MEC networks to reduce access latency and improve energy efficiency. First, the distributed content delivery network based on MECs is developed to support users' requests locally. Moreover, based on users' distribution characteristics and MECs' location, a grouping-based and hierarchical collaborative caching strategy is proposed. Simulation results prove that our caching strategy is more efficient than alternative benchmark strategies in terms of average access latency, total energy consumption and content diversity.
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