Research On Optimization Method Of Rechargeable Wireless Sensor Networks

The information world and the physical world are bound up together tightly through the technologies of RWSN.However,the problem of energy supply of sensor nodes has always existed in the long term work of RWSN.For this reason,the working strategy of WCE,and RWSN trajectory fitting are introduced in this thesis,and electromagnetic induction is used as the wireless charging mode.Firstly,the PSO algorithm is used to optimize the working strategy of WCE,and the highest vacation time ratio of WCE can be achieved under the condition that all static nodes in the RWSN network work properly.Secondly,the LRMR algorithm is applied to the trajectory fitting of RWSN,which can reduce the transmission of the mobile node position information and restore the trajectory of mobile node accurately at the same time.The main work and innovation are as follows:(1)The establishment of RWSN model and its optimization model.Firstly,the topology model of RWSN is analyzed,and the basic model is established.Then aiming at the optimization problem of static node charging strategy in RWSN system,the RWSN optimization model based on PSO algorithm is achieved;aiming at the problem of mobile node trajectory fitting in RWSN system,the RWSN optimization model based on LRMR algorithm is obtained,which can reduce the amount of mobile node position information in the system.(2)Research on WCE working strategy based on PSO algorithm.Firstly,the PSO algorithm is improved and the inertia weight is adjusted adaptively,the simulation results of classical test functions show that the improved PSO algorithm can enhance the ability of global search and local convergence.Then the improved PSO algorithm is adopt to optimize the working strategy of WCE in RWSN system,recharge the static nodes in the network,and the highest staying time ratio of WCE's periodic operation is used as the optimization function.The simulation results show that the staying time ratio can be the highest in this way,and all static nodes in the whole charging period can work normally.(3)Research on RWSN mobile node trajectory fitting method based on LRMR algorithm.Firstly,improve the EALM algorithm commonly used in LRMR,that is,do local rough optimization for single matrix in the algorithm iteration process,and optimize the global results,and the simulation experiment results show that the speed of the algorithm can be increased on the premise of guaranteeing the accuracy of algorithm results.Then,the improved EALM algorithm is used to optimize the mobile node trajectory fitting method of RWSN mobile nodes,including the acquisition of sparse sampling matrix and the fitting of the original trajectory matrix.The simulation results show that the proposed method can reduce the location information transmission of mobile nodes and recover the trajectories of nodes accurately,and the SEALM algorithm has a better effect.