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

Abstract

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, ifthe number ofautonomous 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.

A Bio-inspired Approach to Self-organization of Mobile Nodes in Real-Time Mobile Ad Hoc Network Applications

“…The fga is run by each mobile node as a standalone topology control application to uniformly distribute mobile nodes in an unknown terrain [14,16,17]. Compared to other techniques, our ga-based approach presents encouraging results by converging towards a uniform node distribution as shown in [15].…”

“…In our earlier work, we introduced an FGA [14,16,17] inspired by repulsive forces in physics [12]. In our fga, each mobile node is applied a force by its near neighbors (i.e, the nodes located within its communication range, R com ), which should sum up to zero at the equilibrium.…”

“…In this framework, a force-based ga (fga) [17] is constructed as a decentralized topology control mechanism among active running software agents to achieve a uniform deployment of autonomous nodes over an unknown geographical area. Using only local neighborhood information, a ga guides each mobile node to select a fitter speed and movement direction among an exponentially large number of choices, converging towards a uniform node distribution.…”

Markov Chain Analysis of Self-organizing Mobile Nodes

“…fga is used by each mobile node as a standalone topology control application in [42,43,50] to obtain uniform distribution of mobile nodes in a manet. The experimental results for behavior of our gabased algorithm for dynamic environments (e.g., malfunction and obstacles) are given in [39,44].…”

Handling equality constraints with agent-based memetic algorithms

“…Wireless mobile nodes adjust their speed and direction using a genetic algorithm, where each mobile node exchanges its genetic information (of speed and direction) encoded in its chromosomes with the neighboring nodes. The improved version of FGA is presented in [70].…”