Fountain Codes Based Distributed Storage Algorithms for Large-scale Wireless Sensor Networks

TL;DR

This paper introduces two fully distributed algorithms using Fountain codes and random walks for efficient data dissemination and storage in large-scale wireless sensor networks, enabling data recovery from a small subset of nodes.

Contribution

The paper presents novel distributed algorithms that do not require nodes to know global network parameters, improving robustness and scalability in sensor networks.

Findings

Algorithms are computationally simple and scalable.

Extensive simulations validate the effectiveness of the proposed methods.

Analysis shows low communication and encoding complexity.

Abstract

We consider large-scale sensor networks with n nodes, out of which k are in possession, (e.g., have sensed or collected in some other way) k information packets. In the scenarios in which network nodes are vulnerable because of, for example, limited energy or a hostile environment, it is desirable to disseminate the acquired information throughout the network so that each of the n nodes stores one (possibly coded) packet and the original k source packets can be recovered later in a computationally simple way from any (1 + \epsilon)k nodes for some small \epsilon > 0. We developed two distributed algorithms for solving this problem based on simple random walks and Fountain codes. Unlike all previously developed schemes, our solution is truly distributed, that is, nodes do not know n, k or connectivity in the network, except in their own neighborhoods, and they do not maintain any routing tables. In the first algorithm, all the sensors have the knowledge of n and k. In the second algorithm, each sensor estimates these parameters through the random walk dissemination. We present analysis of the communication/transmission and encoding/decoding complexity of these two algorithms, and provide extensive simulation results as well