Ant Backpressure Routing for Wireless Multi-hop Networks with Mixed Traffic Patterns

Our paper “Ant Backpressure Routing for Wireless Multi-hop Networks with Mixed Traffic Patterns” has been accepted to IEEE MILCOM 2024, and was presented by Negar Erfaniantaghvayi.

• Preprint available at https://arxiv.org/pdf/2408.12702
• Source code available at https://github.com/Negar-Erfanian/AntBackpressure

Related conference papers and code

• Delay-aware Backpressure Routing using Graph Neural Networks
• Enhanced Backpressure Routing with Wireless Link Features
• Biased Backpressure Routing using Link Features and Graph Neural Networks

Abstract

A mixture of streaming and short-lived traffic presents a common yet challenging scenario for Backpressure routing in wireless multi-hop networks. Although state-of-the-art shortest-path biased backpressure (SP-BP) can significantly improve the latency of backpressure routing while retaining throughput optimality, it still suffers from the last-packet problem due to its inherent per-commodity queue structure and link capacity assignment. To address this challenge, we propose Ant Backpressure (Ant-BP), a fully distributed routing scheme that incorporates the multi-path routing capability of SP-BP into ant colony optimization (ACO) routing, which allows packets of different commodities to share link capacity in a first-in-first-out (FIFO) manner. Numerical evaluations show that Ant-BP can improve the latency and delivery ratio over SP-BP and ACO routing schemes, while achieving the same throughput of SP-BP under low-to-medium traffic loads.

Key words: Wireless multi-hop networks, Backpressure routing, Max-Weight scheduling, Ant colony optimization