A swarm algorithm for collaborative traffic in vehicular networks

TL;DR

This study proposes a swarm intelligence based distributed congestion control strategy to maintain the channel usage level under the threshold of network malfunction, while keeping the quality-of-service of the VANET high.

Abstract

Vehicular ad hoc networks (VANETs) allow vehicles to exchange warning messages with each other. These specific kinds of networks help reduce hazardous traffic situations and improve safety, which are two of the main objectives in developing Intelligent Transportation Systems (ITS). For this, the performance of VANETs should guarantee the delivery of messages in a required time. An obstacle to this is that the data traffic generated may cause network congestion. Data congestion control is used to enhance network capabilities, increasing the reliability of the VANET by decreasing packet losses and communication delays. In this study, we propose a swarm intelligence based distributed congestion control strategy to maintain the channel usage level under the threshold of network malfunction, while keeping the quality-of-service of the VANET high. An exhaustive experimentation shows that the proposed strategy improves the throughput of the network, the channel usage, and the stability of the communications in comparison with other competing congestion control strategies.

Figures (10)

• Figure 1: Car A performs CVS communication.
• Figure 2: Simple deterministic VANET scenario.
• Figure 3: VANET in which nodes apply FBR.
• Figure 4: Swarm FREDY main software components.
• Figure 5: Complete flowchart of the Swarm FREDY algorithm.