Network Coding with Random Packet-Index Assignment for Data Collection Networks

TL;DR

This paper introduces NeCoRPIA, a decentralized network coding method where packet indices are randomly assigned, simplifying packet identification in data collection networks with mobile and unreliable devices.

Contribution

The paper proposes a novel decentralized packet index assignment method for network coding, along with a decoding algorithm for index collisions and a theoretical performance analysis.

Findings

Decoding complexity and error probability are characterized theoretically.

Simulation results confirm the theoretical analysis.

NeCoRPIA reduces header length compared to COPE-based protocols.

Abstract

This paper considers a data collection network consisting of uncoordinated, heterogeneous, and possibly mobile devices. These devices use medium and short-range radio technologies, which require multi-hop communication to deliver data to some sink. While numerous techniques from managed networks can be adapted, one of the most efficient (from the energy and spectrum use perspective) is \emph{network coding} (NC). NC is well suited to networks with mobility and unreliability, however, practical NC requires a precise identification of individual packets that have been mixed together. In a purely decentralized system, this requires either conveying identifiers in headers along with coded information as in COPE, or integrating a more complex protocol in order to efficiently identify the sources (participants) and their payloads. This paper presents a novel solution, Network Coding with Random Packet Index Assignment (NeCoRPIA), where packet indices in NC headers are selected in a decentralized way, by simply choosing them randomly. Traditional network decoding techniques apply directly when all original packets have different indices. When this is not the case, i.e., in case of collisions of indices, a specific decoding algorithm is proposed. A theoretical analysis of its performance in terms of complexity and decoding error probability is described. Simulation results match well the theoretical results. Comparisons of NeCoRPIA header lengths with those of a COPE-based NC protocol are also provided.