Dynamic Optimization of Secure Mobile Sensor Networks: A Genetic Algorithm

We propose a reduced-complexity genetic algorithm for secure and dynamic deployment of resource constrained multi-hop mobile sensor networks. Mobility and security are relatively expensive operations since they involve both communication and computation. Furthermore, these operations have to co-exist with optimal node and route assignments. The goal of this paper is to achieve optimal secure coverage and improved battery life using dynamic re-locatability. The genetic algorithm is used to adaptively configure optimal position and security attributes by dynamically monitoring network traffic, packet integrity, and battery usage. This results in minimization of the power consumption of the sensor system while maximizing the sensor objectives (coverage and exposure).