A cellular multi-objective genetic algorithm for optimal broadcasting strategy in metropolitan MANETs

Mobile ad-hoc networks (MANETs) are composed of a set of communicating devices, which are able to spontaneously interconnect without any pre-existing infrastructure. In such scenario, broadcasting becomes an operation of capital importance for the own existence and operation of the network. Optimizing a broadcast strategy in MANETs is a multi-objective problem accounting for three goals: reaching as many stations as possible, minimizing the network utilization, and reducing the makespan. In this paper, we study the fine-tuning of broadcast strategies by using a cellular multi-objective genetic algorithm (cMOGA) that computes a Pareto front of the solutions to empower a human designer with the ability of choosing the preferred configuration for the network. We define two formulations of the problem, one with three objectives and another one with two objectives plus a constraint. Our experiments using a complex and realistic MANET simulator reveal that using cMOGA is a promising approach to solve the optimum broadcast problem.