Predictive caching at the wireless edge using near-zero caches
Predictive caching at the wireless edge using near-zero caches
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DOI：
10.1145/3397166.3409126
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发表时间：
2020-10
期刊：
影响因子：
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通讯作者：
Sherif ElAzzouni;Fei Wu;N. Shroff;E. Ekici
中科院分区：
文献类型：
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作者：
Sherif ElAzzouni;Fei Wu;N. Shroff;E. Ekici
本文研究了预测缓存对无线网络时延的影响。我们探讨了在缓存通常非常小、比目录大小小一个数量级的无线终端用户处进行缓存的可能性。我们开发了一种预测性多播和缓存方案，其中无线小区中的基站(BS)主动多播流行内容以供最终用户缓存，并在请求时本地访问。我们分析了这种联合组播和缓存对时延性能的影响。我们的分析使用了在缓存消失假设下的重流量理论的一种新的应用，表明预测性缓存从根本上改变了渐近的吞吐量-延迟比例。当网络在接近满载时运行时，这又转化为模拟比按需单播基线的延迟提高数倍。我们强调了系统中一个基本的延迟-内存权衡，并确定了正确的内存扩展，以充分受益于网络组播收益。
In this paper, we study the effect of predictive caching on the delay of wireless networks. We explore the possibility of caching at wireless end-users where caches are typically very small, orders of magnitude smaller than the catalog size. We develop a predictive multicasting and caching scheme, where the Base Station (BS) in a wireless cell proactively multicasts popular content for end-users to cache, and access locally if requested. We analyze the impact of this joint multicasting and caching on the delay performance. Our analysis uses a novel application of Heavy-Traffic theory under the assumption of vanishing caches to show that predictive caching fundamentally alters the asymptotic throughput-delay scaling. This in turn translates to a several-fold delay improvement in simulations over the on-demand unicast baseline as the network operates close to the full load. We highlight a fundamental delay-memory trade-off in the system and identify the correct memory scaling to fully benefit from the network multicasting gains.