Infrastructure Deployment in Vehicular Communication Networks Using a Parallel Multiobjective Evolutionary Algorithm

TL;DR

This paper presents a multiobjective evolutionary algorithm to optimize roadside infrastructure placement in urban vehicular networks, balancing quality-of-service and cost, with real-world testing showing superior results.

Contribution

It introduces a novel multiobjective formulation and demonstrates its effectiveness over real urban data, outperforming existing algorithms.

Findings

Accurate trade-off solutions for infrastructure placement

Significant improvement over state-of-the-art algorithms

Validated with real urban traffic and communication scenarios

Abstract

This article describes the application of a multiobjective evolutionary algorithm for locating roadside infrastructure for vehicular communication networks over realistic urban areas. A multiobjective formulation of the problem is introduced, considering quality-of-service and cost objectives. The experimental analysis is performed over a real map of M\'alaga, using real traffic information and antennas, and scenarios that model different combinations of traffic patterns and applications (text/audio/video) in the communications. The proposed multiobjective evolutionary algorithm computes accurate trade-off solutions, significantly improving over state-of-the-art algorithms previously applied to the problem.