On Simple Back-Off in Unreliable Radio Networks

TL;DR

This paper demonstrates that simple back-off strategies are effective for local and global broadcast in radio networks with unreliable links when modeled with constraints mimicking real-world fading, bridging theory and practice.

Contribution

The paper introduces new constraints to the dual graph model that better reflect real network behavior, showing simple back-off strategies become efficient under these conditions.

Findings

Simple back-off strategies are effective under the new constraints.

Efficiency degrades as constraints are reduced, with near-optimal lower bounds.

Results provide theoretical support for practical success of simple algorithms.

Abstract

In this paper, we study local and global broadcast in the dual graph model, which describes communication in a radio network with both reliable and unreliable links. Existing work proved that efficient solutions to these problems are impossible in the dual graph model under standard assumptions. In real networks, however, simple back-off strategies tend to perform well for solving these basic communication tasks. We address this apparent paradox by introducing a new set of constraints to the dual graph model that better generalize the slow/fast fading behavior common in real networks. We prove that in the context of these new constraints, simple back-off strategies now provide efficient solutions to local and global broadcast in the dual graph model. We also precisely characterize how this efficiency degrades as the new constraints are reduced down to non-existent, and prove new lower bounds that establish this degradation as near optimal for a large class of natural algorithms. We conclude with a preliminary investigation of the performance of these strategies when we include additional generality to the model. These results provide theoretical foundations for the practical observation that simple back-off algorithms tend to work well even amid the complicated link dynamics of real radio networks.