Research On Dynamic Power Allocation Based Pay-on-demand Charging Scheduling Scheme In Wireless Sensor Networks

Wireless sensor networks have been widely used in various application scenarios in real life,nevertheless,the problem of energy supply for sensor devices has been a bottleneck in the development of wireless sensor networks.In recent years,wireless rechargeable sensor networks have received increasing attention from researchers.To ensure the long-term reliable operation of the system,wireless rechargeable sensor networks use wireless energy transfer technology to provide continuous power supply for rechargeable sensor devices.Unlike the conventional charging models for wireless rechargeable sensor networks,this work considers a fine-grained pay-as-you-go charging service model based on dynamic power allocation.In this model,all charging stations in the network are deployed and operated by a Charging Service Provider(CSP),which provides long-range wireless charging services to the sensor devices in the network periodically according to the charging demand of the users.Finally,users pay the corresponding charging service fees to the CSP according to the requested charging service time.On the basis of the above charging service model,how to establish a reasonable charging payment calculation model for devices,and how to realize the cooperative charging scheduling of charging stations to balance the relationship between charging completion time,charging service cost and charging utility on demand are the focus of this work.The research of this work mainly includes:(1)The dynamic power allocation-based charging utility optimization problem in wireless rechargeable sensor networks is investigated by first constructing an integer programming model based on charging completion time and charging service cost constraints and proving the NP hardness of the problem.Then the objective problem is converted into an equivalent budget constraint-based submodular function maximization problem by constructing a non-negative and monotonically nondecreasing submodular function.Further based on the constructed submodular function,the charging strategy of each charging station is obtained using a greedy strategy to obtain the final solution,and the approximation ratio of the solution is proved.Finally,it is demonstrated through extensive simulation experiments that the algorithm proposed in this work has significant advantages in charging utility optimization compared to other comparative methods.(2)The optimization problem of time and cost tradeoff based on dynamic power allocation in wireless rechargeable sensor networks is investigated.First,this work considers the charging service cost optimization problem under the charging completion time constraint by modeling it as a typical linear programming problem and using the simplex method to find the optimal solution in polynomial time.Then,this work considers the adaptive tradeoff between charging completion time and charging service cost as the objective to study the dynamic power allocation based time and cost adaptive tradeoff optimization problem,proves the NP-hard of the problem,and uses an efficient ant colony optimization algorithm to solve the problem.Finally,the effectiveness and superiority of the algorithm used in this work are verified by extensive simulation experiments.