Hierarchical optimization strategies for sensor network deployment

The objective of this research is to develop a new hierarchical design framework for balanced coordinated algorithms addressing sensor network deployment problems in network systems as a means to enhance dissemination of network resources so that optimal responses to network damages and threats by the weapons of mass destruction (WMD) will be achieved and recovery of the network can be significantly improved. In particular, this research will involve a two-stage hierarchical algorithm design in which the first stage is a network topology design for cascaded resilience in the network while the second stage is an optimal weight design for network graphs characterizing efficiency based on the graph topology obtained in the first stage. We convert the first stage design into a multi-objective optimization problem and the second stage design into a constrained optimization problem. To solve both proposed optimization problems, we develop a modified particle swarm optimization (PSO) based stochastic algorithm to approximate optimal solutions of the multi-objective optimization problem and a semistable optimal control approach to solve the constrained optimization problem. The overall method combines control theory, distributed algorithms, and optimization together to improve network resource allocation and damage mitigation under WMD attacks and other adversary conditions.