When Can Intelligent Helper Node Selection Improve the Performance of Distributed Storage Networks?
Imad Ahmad, Chih-Chun Wang · IEEE Transactions on Information Theory · 2017
The concept of distributed storage networks (DSNs) mostly follows two main modeling assumptions: Any k out of n surviving nodes should be able to reconstruct the protected file; and if one node fails, the replacement node can access d helper nodes to repair its content either functionally or exactly. Two major existing approaches for DSNs are the so-called regenerating codes (RCs) and locally repairable codes (LRCs), which have different design philosophies and focus on distinct applications. Instead of being limited by the framework of either RCs or LRCs, this work answers a fundamental question for general DSNs: For an arbitrarily given (n,k,d) value, whether there exists an intelligent helper node selection design that can strictly improve the storage-bandwidth tradeoff when compared with naive blind helper selection. Surprisingly, the answer is negative for a large set of (n,k,d) values. Namely, for those (n,k,d) values even the best helper selection design offers no gain over a blind solution. We call those (n,k,d) values indifferent-to-helper-selection (ITHS). The main contribution of this work is a necessary and sufficient condition that characterizes whether an (n,k,d) value is ITHS. As a fundamental study, this work assumes functional repair with unlimited computing power for encoding/decoding and focuses on the fundamental performance limits of intelligent helper selection. A new helper selection scheme, termed family helper selection, is proposed and used in the achievability analysis. For some scenarios, the proposed scheme is indeed optimal (as good as any helper selection one can design).