Optimizing parameters of a mobile ad hoc network protocol with a genetic algorithm

Mobile ad hoc networks are typically designed and evaluated in generic simulation environments. However the real conditions in which these networks are deployed can be quite different in terms of RF attentution, topology, and traffic load. Furthermore, specific situations often have a need for a network that is optimized along certain characteristics such as delay, energy or overhead. In response to the variety of conditions and requirements, ad hoc networking protocols are often designed with many modifiable parameters. However, there is currently no methodical way for choosing values for the parameters other than intuition and broad experience. In this paper we investigate the use of genetic algorithms for automated selection of parameters in an ad hoc networking system. We provide experimental results demonstrating that the genetic algorithm can optimize for different classes of operating conditions. We also compare our genetic algorithm optimization against hand-tuning in a complex, realistic scenario and show how the genetic algorithm provides better performance.