Data replication in collaborative sensor network systems

When sensor networks overlap in their coverage areas, sensors in the common areas can be simultaneously shared among multiple networks. The shared sensors provide opportunities to support collaboration among sensor networks. Collaboration enriches functionality and enhances scalability and manageability of networked sensor systems, in particular those comprised of a large number of heterogeneous sensor networks deployed over a large area. Effective collaboration may require that various sensor networks share synchronized data replicas. In this paper, we propose a novel data replication mechanism suitable for the limited bandwidth of sensor networks. The scheme is comprised of off-line and in-line components and uses neural networks for scheduling of replication. Implementing a simple neural network requires minimal computational overhead feasible for use on a sensor node. To the best of our knowledge, this is the first scheme for synchronized replication in collaborative sensor network systems. Simulation results show that such neural-network-based approach provides near optimal scheduling and replication solutions while maintaining adaptability and low computational overhead