Distributed Storage Allocations for Optimal Delay

TL;DR

This paper investigates how to optimally allocate encoded distributed storage across mobile nodes to minimize recovery delay, considering success probability and expected delay, with solutions for symmetric allocations and practical evaluations.

Contribution

It provides a complete solution for optimizing recovery delay with symmetric storage allocations and analyzes the impact of coding and allocation strategies in mobile networks.

Findings

Optimal symmetric allocation differs for success probability and delay minimization.

Storage allocation significantly affects recovery delay performance.

Coding benefits depend on network conditions and storage strategies.

Abstract

We examine the problem of creating an encoded distributed storage representation of a data object for a network of mobile storage nodes so as to achieve the optimal recovery delay. A source node creates a single data object and disseminates an encoded representation of it to other nodes for storage, subject to a given total storage budget. A data collector node subsequently attempts to recover the original data object by contacting other nodes and accessing the data stored in them. By using an appropriate code, successful recovery is achieved when the total amount of data accessed is at least the size of the original data object. The goal is to find an allocation of the given budget over the nodes that optimizes the recovery delay incurred by the data collector; two objectives are considered: (i) maximization of the probability of successful recovery by a given deadline, and (ii) minimization of the expected recovery delay. We solve the problem completely for the second objective in the case of symmetric allocations (in which all nonempty nodes store the same amount of data), and show that the optimal symmetric allocation for the two objectives can be quite different. A simple data dissemination and storage protocol for a mobile delay-tolerant network is evaluated under various scenarios via simulations. Our results show that the choice of storage allocation can have a significant impact on the recovery delay performance, and that coding may or may not be beneficial depending on the circumstances.