Uniform distribution of mobile agents using genetic algorithms for military applications in MANETs

There has been increased research interest in providing uniform distribution of autonomous mobile nodes controlled by active running software agents over an unknown geographical area in Mobile Ad-hoc networks (MANETs). This problem becomes more challenging under the harsh and bandwidth limited conditions imposed by military applications. In this framework, the software agent running at the application layer for each autonomous mobile node adjusts its direction and speed by using local information from its neighbors. A genetic algorithm (GA) is used by each node to select the “fitter” speed and direction options among exponentially large number of choices converging towards a uniform distribution. For a military application example, consider that in the observed occurrence of a threat situation, if the number of autonomous mobile agents change with time (e.g., losing assets during an operation), the remaining agents should reposition themselves to compensate the lost in coverage and network connectivity. We implemented simulation software to evaluate the effectiveness of GAs within these types of military applications. The results show that GAs can be applied to autonomous mobile nodes and are an effective tool for providing a robust solution for network area coverage under restrained communication conditions.