Symmetric Allocations for Distributed Storage
Derek Leong, Alexandros G. Dimakis, Tracey Ho

TL;DR
This paper investigates optimal data storage allocation in distributed systems, demonstrating that spreading storage evenly across nodes is asymptotically optimal under certain conditions, with explicit solutions provided for various scenarios.
Contribution
It proves the asymptotic optimality of symmetric storage allocations and derives explicit optimal solutions for different cases, addressing a complex nonconvex optimization problem.
Findings
Maximally spreading storage is asymptotically optimal.
Explicit optimal symmetric allocations are derived for multiple cases.
Performance gap of symmetric allocation vanishes asymptotically.
Abstract
We consider the problem of optimally allocating a given total storage budget in a distributed storage system. A source has a data object which it can code and store over a set of storage nodes; it is allowed to store any amount of coded data in each node, as long as the total amount of storage used does not exceed the given budget. A data collector subsequently attempts to recover the original data object by accessing each of the nodes independently with some constant probability. By using an appropriate code, successful recovery occurs when the total amount of data in the accessed nodes is at least the size of the original data object. The goal is to find an optimal storage allocation that maximizes the probability of successful recovery. This optimization problem is challenging because of its discrete nature and nonconvexity, despite its simple formulation. Symmetric allocations (in…
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