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

Negar Erfaniantaghvayi, Zhongyuan Zhao, Kevin Chan, Gunjan Verma, Ananthram Swami, Santiago Segarra

TL;DR

The paper tackles latency challenges in backpressure routing for wireless multi-hop networks with mixed streaming and bursty traffic, where traditional BP suffers from the last-packet problem. It introduces Ant-BP, a fully distributed scheme that fuses shortest-path biased backpressure (SP-BP) with ant colony optimization (ACO) routing, enabling FIFO-based multi-commodity link sharing through pheromone-guided decisions derived from a virtual SP-BP routing phase. The authors show that Ant-BP substantially improves end-to-end latency and delivery ratios over SP-BP and baseline ACO schemes while preserving SP-BP throughput at low-to-medium traffic loads, and it demonstrates robustness to mismatched virtual traffic configurations. The work provides a practical routing framework that leverages virtual routing to enhance performance under mixed traffic without sacrificing throughput, with potential extensions to continuous route maintenance and mobility scenarios.

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.

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

TL;DR

The paper tackles latency challenges in backpressure routing for wireless multi-hop networks with mixed streaming and bursty traffic, where traditional BP suffers from the last-packet problem. It introduces Ant-BP, a fully distributed scheme that fuses shortest-path biased backpressure (SP-BP) with ant colony optimization (ACO) routing, enabling FIFO-based multi-commodity link sharing through pheromone-guided decisions derived from a virtual SP-BP routing phase. The authors show that Ant-BP substantially improves end-to-end latency and delivery ratios over SP-BP and baseline ACO schemes while preserving SP-BP throughput at low-to-medium traffic loads, and it demonstrates robustness to mismatched virtual traffic configurations. The work provides a practical routing framework that leverages virtual routing to enhance performance under mixed traffic without sacrificing throughput, with potential extensions to continuous route maintenance and mobility scenarios.

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.
Paper Structure (12 sections, 12 equations, 3 figures)

This paper contains 12 sections, 12 equations, 3 figures.

Table of Contents

  1. Introduction
  2. System model
  3. Per-Neighbor Queueing System
  4. Per-Commodity Virtual Queueing System
  5. Ant Backpressure
  6. Virtual SP-BP Routing for Pheromone Establishment
  7. Virtual Traffic Configuration
  8. Numerical Experiments
  9. Test Setup and Benchmarks
  10. Performance under Mixed Traffic
  11. Throughput under Streaming Traffic
  12. Conclusions and Future Work

Figures (3)

  • Figure 1: The system diagram of Ant Backpressure routing: queueing system design, operations, and timelines.
  • Figure 2: The average (a) end-to-end latency and (b) delivery ratio of tested routing policies as a function of bursty flow load $L_b$ in 10 random instances of wireless networks of 100 nodes under mixed traffic setting with a constant streaming load $L_s=2.0$. (c) The average delivery ratio of tested routing schemes in wireless networks of 100 nodes under mixed traffic with different loads shown in the x-axis. For Ant-based schemes, routing policies are established based on virtual traffic flows of $(1.0, 1.0)$ and $(1.0, 10.0)$ for the left and right sides, respectively.
  • Figure 3: Average network throughput (network-wide number of packets delivered per time slot) of routing schemes on wireless networks with 100 nodes under all streaming traffic as a function of traffic load $L_s$.