Energy Optimization In Rechargeable Sensor Network

Due to its promising development and tremendous economic value, Wireless Sensor Network has received much attention in recent years. Its applications span from National Defense, Wildlife Observation to Smart Healthcare and other industries. However, restricted by limited battery capacity of nodes, the stability of WSN is much challenged in long-term observation. The emerging Wireless Charging technology-based Rechargeable Sensor Network provides a solution to the issues brought by restricted battery capacity in traditional WSN.In Rechargeable Sensor Networks, one of current highlighted research topics is how to charge efficiently and reduce energy consumption of the entire system. In this thesis, we discuss the overall energy optimization when charging the nodes by using wireless charging device. The main work and contributions are summarized as follows:Energy optimization of Rechargeable Sensor Networks with multiple sinks:In a scenario where communication radius and data processing ability of node are much restricted, we build a Rechargeable Sensor Network model with multiple sinks. We study an energy optimization problem how to design dynamic data routing and charging strategy in order to minimize the entire system consumption under this network model. We design a low-complexity algorithm to compute the best charge positions, charge times and the dynamic data routing. Finally, through a simulation of a specific network, we demonstrate the availability and feasibility of our method.Energy optimization of Rechargeable Delay-Tolerant Sensor network:With wireless charging technology applied in Delay-Tolerant Wireless Sensor Network, we build a model of this network. We study an energy optimization problem how to design dynamic delay-tolerant data routing and charging strategy in order to minimize the entire system consumption under this network model. Further, we turn this energy optimization problem to a LP problem that can be solved by linear programming solver. Finally, through a simulation of a specific network, we demonstrate the availability and feasibility of our method.Energy optimization of UAV-based Rechargeable Sensor network:By introducing UAV to charge nodes, we build a model of UAV-based Rechargeable Sensor network. We study an energy optimization problem how to design charging strategy, path planning and charging position selection in order to minimize UAV work time. We prove that this problem is a NP-hard problem, and design a greedy algorithm to solve the energy optimization problem under this network model. Finally, we verify the efficacy of the algorithm via contrast simulation.