GCP: Gossip-based Code Propagation for Large-scale Mobile Wireless Sensor Networks

TL;DR

This paper introduces GCP, a gossip-based distributed algorithm for automatic software updates in large-scale mobile wireless sensor networks, balancing reliability, scalability, and load distribution.

Contribution

It presents a novel gossip-based code propagation method tailored for mobile sensor networks, improving load balancing and propagation speed without localization.

Findings

GCP achieves fast convergence in code dissemination.

GCP balances load effectively among sensors.

Simulation shows GCP outperforms traditional methods.

Abstract

Wireless sensor networks (WSN) have recently received an increasing interest. They are now expected to be deployed for long periods of time, thus requiring software updates. Updating the software code automatically on a huge number of sensors is a tremendous task, as ''by hand'' updates can obviously not be considered, especially when all participating sensors are embedded on mobile entities. In this paper, we investigate an approach to automatically update software in mobile sensor-based application when no localization mechanism is available. We leverage the peer-to-peer cooperation paradigm to achieve a good trade-off between reliability and scalability of code propagation. More specifically, we present the design and evaluation of GCP ({\emph Gossip-based Code Propagation}), a distributed software update algorithm for mobile wireless sensor networks. GCP relies on two different mechanisms (piggy-backing and forwarding control) to improve significantly the load balance without sacrificing on the propagation speed. We compare GCP against traditional dissemination approaches. Simulation results based on both synthetic and realistic workloads show that GCP achieves a good convergence speed while balancing the load evenly between sensors.