Research On Periodic Charging And Data Collection Planning For Maximizing Energy Utility Of Mobile Device

Data collection is the core task of Wireless Sensor Networks(WSNs),and the collection and transmission of data consume the energy of the sensor node.Due to the limited battery capacity of the sensor node,the sensor node will eventually die due to insufficient energy,which will affect data collection.The traditional energy-saving and energy-collecting methods have limitations,and the emerging wireless charging technology provides a new solution to address the energy shortage problem of WSNs.Sensor nodes with wireless energy harvesting device and Mobile Device(MD)are deployed in the WSNs to constitute the Wireless Rechargeable Sensor Networks(WRSNs).How to plan the traveling path to improve the energy utility of MD and achieve efficient charging and data collection to ensure the perpetual network operation is a research hotspot in WSNs.For scenarios where the sensor nodes are sparsely distributed,the MD uses a point-to-point method to charge and collect data for the sensor nodes,and to charge the sensor nodes while collecting the data of the sensor nodes.The effect of charging and data collection on MD path planning is considered.Under the premise of ensuring the perpetual network operation,the goal of maximizing the energy utility of the MD is to construct a periodic path planning problem for the mobile device.It is proved that the maximum objective value needs to be obtained when the cycle time is maximum,and it is proved that the problem is NP-Complete problem.Aiming at this problem,a multi-population discrete fireworks algorithm MFWA is designed to solve the problem.The rationality of the model is verified by experiments and the optimal solution is given.The experimental results show that the MFWA algorithm is superior to the DFWA algorithm in terms of convergence speed,stability,and adaptability.The point-to-point periodic charging and data collection planning proposed in this paper can effectively improve the energy utility of MD and ensure the perpetual network operation.For a scene where the sensor nodes in a part of the network are dense,the network is divided into multiple regions,and the mobile device uses a point-to-multipoint method to charge and collect data for the sensor nodes.The relationship between charging time,data collection time and cycle time is analyzed.The method for calculating the sojourn time of the mobile device in each cell is given.Under the premise of ensuring the perpetual network operation,aiming at maximizing the energy utility of the mobile device,the periodic path planning problem of mobile devices is constructed.The discrete fireworks algorithm based on population entropy PE-FWA is designed to solve the problem and gives the optimal solution.On this basis,according to the distribution of sensor nodes in the cell,an adjustment and optimization strategy for the anchor point of the mobile device is proposed,which further increases the energy utility of the mobile device.The experimental results show that the solution obtained by PE-FWA algorithm is better than the DFWA algorithm and MDSA algorithm,and the convergence and stability of PE-FWA algorithm are better than DFWA algorithm.The comparison of population entropy behavior shows that the PE-FWA algorithm better balances the preferences and diversity of the population.