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

Abstract

Abstract. In this chapter, we study the applicability and effectiveness of an evolutionary computation approach to a topology control problem in the domain of mobile ad hoc networks (manets). We present formal and practical aspects of convergence properties of our force-based genetic algorithm, called fga, which is run by each mobile node to achieve a uniform spread. Our fga is suitable for manet environments since mobile nodes, while running the fga, only use local neighborhood information. An inhomogeneous Markov chain is used to analyze the convergence speed of our bio-inspired algorithm. To demonstrate our topology control algorithm's applicability to real-life problems and to evaluate its effectiveness, we have implemented a simulation software system and two testbed platforms. The simulation and testbed experiment results indicate that, for important performance metrics such as the normalized area coverage and convergence rate, the fga can be an effective mechanism to deploy mobile nodes with restrained communication capabilities in manets operating in unknown areas. Since the fga adapts to the local environment rapidly and does not require global network knowledge, it can be used as a real-time topology controller for realistic military and civilian applications.