Efficient Interference Graph Estimation via Concurrent Flooding

TL;DR

This paper introduces a novel method for estimating interference graphs in wireless sensor networks by using concurrent flooding and power control, reducing measurement overhead and enabling practical scheduling.

Contribution

It proposes a new interference graph estimation technique that operates simultaneously with flooding using the same resources, improving efficiency in wireless sensor networks.

Findings

Feasibility demonstrated on COTS devices with controlled experiments.

Concurrent flooding with power control effectively estimates interference graphs.

Potential to enhance network scheduling algorithms with practical interference information.

Abstract

Traditional wisdom for network management allocates network resources separately for the measurement and data transmission tasks. Heavy measurement tasks may take up resources for data transmission and significantly reduce network performance. It is therefore challenging for interference graphs, deemed as incurring heavy measurement overhead, to be used in practice in wireless networks. To address this challenge in wireless sensor networks, we propose to use power as a new dimension for interference graph estimation (IGE) and integrate IGE with concurrent flooding such that IGE can be done simultaneously with flooding using the same frequency-time resources. With controlled and real-world experiments, we show that it is feasible to efficiently achieve IGE via concurrent flooding on the commercial off-the-shelf (COTS) devices by controlling the transmit powers of nodes. We believe that efficient IGE would be a key enabler for the practical use of the existing scheduling algorithms assuming known interference graphs.