Least-recently-used (LRU) caching and its variants have conventionally been used as a fundamental and critical method to ensure fast and efficient data access in computer and communication systems. Emerging data-intensive applications over unreliable channels, e.g., mobile edge computing and wireless content delivery networks, have imposed new challenges in optimizing LRU caching in environments prone to failures. Most existing studies focus on reliable channels, e.g., on wired Web servers and within data centers, which have already yielded good insights and successful algorithms. Surprisingly, we show that these insights do not necessarily hold true for unreliable channels. We consider a single-hop multi-cache distributed system with data items being dispatched by random hashing. The objective is to design efficient cache organization and data placement that minimize the miss probability. The former allocates the total memory space to each of the involved caches. The latter decides data routing and replication strategies. Analytically, we characterize the asymptotic miss probabilities for unreliable LRU caches, and optimize the system design. Remarkably, these results sometimes are counterintuitive, differing from the ones obtained for reliable caches. We discover an interesting phenomenon: allocating the cache space unequally can achieve a better performance, even when channel reliability levels are equal. In addition, we prove that splitting the total cache space into separate LRU caches can achieve a lower asymptotic miss probability than organizing the total space in a single LRU cache. These results provide new and even counterintuitive insights that motivate novel designs for caching systems over unreliable channels.

中文翻译：

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在不可靠通道上缓存最佳分布式LRU的违反直觉的特征

过去，最近最少使用（LRU）缓存及其变体已被用作一种基本且至关重要的方法，以确保在计算机和通信系统中快速有效地访问数据。在不可靠通道上的新兴数据密集型应用程序（例如，移动边缘计算和无线内容交付网络）在优化易发生故障的环境中的LRU缓存方面提出了新的挑战。现有的大多数研究都集中在可靠的渠道上，例如，有线Web服务器和数据中心内的渠道，这些渠道已经产生了很好的见识和成功的算法。令人惊讶的是，我们表明这些见解不一定适用于不可靠的渠道。我们考虑一种单跳多缓存分布式系统，其中数据项是通过随机散列调度的。目的是设计有效的缓存组织和数据放置，以最大程度地降低未命中率。前者将总内存空间分配给每个涉及的缓存。后者决定数据路由和复制策略。通过分析，我们描述了不可靠的LRU缓存的渐近遗漏概率，并优化了系统设计。值得注意的是，这些结果有时是违反直觉的，与获得可靠缓存的结果有所不同。我们发现了一个有趣的现象：即使在通道可靠性级别相同的情况下，不平等地分配缓存空间也可以实现更好的性能。另外，我们证明，与在单个LRU缓存中组织总空间相比，将总缓存空间划分为单独的LRU缓存可以实现更低的渐近丢失概率。