Adaptive Broadcast Suppression for Trickle-Based Protocols

TL;DR

This paper introduces an adaptive extension to the Trickle broadcast suppression algorithm, enabling nodes in low-power wireless networks to better handle varying network densities and improve overall protocol robustness.

Contribution

The paper proposes adaptive-k, a novel extension to Trickle, allowing nodes to locally adjust suppression parameters based on network density, enhancing fairness and performance.

Findings

Improved load distribution across nodes

Reduced end-to-end delays in network communication

More robust performance across different topologies

Abstract

Low-power wireless networks play an important role in the Internet of Things. Typically, these networks consist of a very large number of lossy and low-capacity devices, challenging the current state of the art in protocol design. In this context the Trickle algorithm plays an important role, serving as the basic mechanism for message dissemination in notable protocols such as RPL and MPL. While Trickle's broadcast suppression mechanism has been proven to be efficient, recent work has shown that it is intrinsically unfair in terms of load distribution and that its performance relies strongly on network topology. This can lead to increased end-to-end delays (MPL), or creation of sub-optimal routes (RPL). Furthermore, as highlighted in this work, there is no clear consensus within the research community about what the proper parameter settings of the suppression mechanism should be. We propose an extension to the Trickle algorithm, called adaptive-k, which allows nodes to individually adapt their suppression mechanism to local node density. Supported by analysis and a case study with RPL, we show that this extension allows for an easier configuration of Trickle, making it more robust to network topology.