Research On Wireless Charging And Dynamic Data Routing Strategy For Rechargeable 3-dimensional Wireless Sensor Networks

Wireless sensor networks are becoming increasingly prevalent in a wide range of areas such as in the desert, forest and canyon. Since the nodes are often completely freed from wire, they are usually powered by batteries. When the battery is depleted, the nodes will become invalid if the battery is not replaced or charged timely. Furthermore, these networks are situated in locations where may not be easily accessible. Therefore, it is extremely necessary to develop a strategy to supply energy to the nodes in wireless sensor networks. Reasonable routing scheme based on the energy supply strategy is also helpful to solve the problem.Due to this problem, it could be solved by recharging sensor nodes periodically through the wireless energy transfer technique which would make sensor nodes remain optional persistently. For 3-dimensional wireless sensor networks, an optimization problem was proposed with the objective of maximizing the ratio of the wireless charging device’s vacation time over the cycle time. According to the constraints of data flow and energy flow in the networks, the continuous time-varying model, the simplified continuous time-varying model were proposed successively. Because of the complexity of the simplified continuous time-varying model, the discrete (T+1)-phased nonlinear model and the solvable discrete (T+1)-phased linear model were proposed by variable substitution and variable discretization. Finally, it is proved that the optimal traveling path for the wireless charging device is the 3-dimensional shortest Hamilton cycle by reduction to absurdity. What’s more, seamless docking between initial charging cycle and the ordinary charging cycle is realized.After solving the last proposed model with 20 nodes,50 nodes and 100 nodes, the optimized charging and routing strategies were obtained. The ratio of the wireless charging device’s vacation time over the cycle time is 58.83%,27.27% and 23.58% for networks in different scales. The network lifetime has been extended indeed.