Raptor Codes Based Distributed Storage Algorithms for Wireless Sensor Networks

TL;DR

This paper introduces two distributed storage algorithms based on Raptor codes for large-scale wireless sensor networks, enabling efficient data dissemination and recovery with minimal computational complexity.

Contribution

It proposes novel Raptor code-based algorithms for distributed storage in sensor networks, one with global knowledge and one without, improving data recovery efficiency.

Findings

Algorithms enable data recovery from any slightly larger subset of nodes.

Both algorithms are computationally simple and scalable.

Effective in large-scale wireless sensor networks.

Abstract

We consider a distributed storage problem in a large-scale wireless sensor network with $n$ nodes among which $k$ acquire (sense) independent data. The goal is to disseminate the acquired information throughout the network so that each of the $n$ sensors stores one possibly coded packet and the original $k$ data packets can be recovered later in a computationally simple way from any $(1+\epsilon)k$ of nodes for some small $\epsilon>0$. We propose two Raptor codes based distributed storage algorithms for solving this problem. In the first algorithm, all the sensors have the knowledge of $n$ and $k$. In the second one, we assume that no sensor has such global information.