Counterintuitive Characteristics of Optimal Distributed LRU Caching Over Unreliable Channels

Abstract

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.