Space Bounds for Reliable Storage
Alexander Spiegelman, Yuval Cassuto, Gregory V. Chockler, Idit Keidar · 2016
We study the inherent space requirements of reliable storage algorithms in asynchronous distributed systems. A number of recent works have used codes in order to achieve a better storage cost than the well-known replication approach. However, a closer look reveals that they incur extra costs in certain scenarios. Specifically, if multiple clients access the storage concurrently, then existing asynchronous code-based algorithms may store a number of copies of the data that grows linearly with the number of concurrent clients. We prove here that this is inherent. Given three parameters, (1) the data size -- D bits, (2) the concurrency level -- c, and (3) the number of storage node failures that need to be tolerated -- f, we show a lower bound of Omega(min(f,c)D) bits on the space complexity of asynchronous distributed storage algorithms. Intuitively, this implies that the asymptotic storage cost is either as high as with replication, namely O(fD), or as high under concurrency as with the aforementioned code-based algorithms, i.e., O(cD).