Applying anti-flocking model in mobile surveillance systems

Abstract

This paper discusses the role of three mobility models namely, fully coordinated mobility, fully random mobility and emergent mobility models in improving area coverage and detection effectiveness of a set of mobile sensors in a mobile surveillance system. A novel anti-flocking algorithm that mimics solitary animal's social behavior is described. A multiagent-based system has been implemented to examine the efficiency of the different mobility model. The simulation results show that anti-flocking mobility model outperforms the fully random mobility model. This novel model provides additional features such as scalability, robustness and adaptivity comparing with fully coordinated mobility model.