Research On Predictive Localization Algorithm Of Underwater Wireless Sensor Networks Based On Optimization Algorithm

With the increasing demand for the development and utilization of marine resources,underwater wireless sensor networks have received widespread attention from academia and industry.The main applications are underwater environmental observation,coastal monitoring,disaster prediction,seabed exploration,scientific exploration,commercial development,and military or terrorist incident detection.In the application of UWSNs,it is necessary to collect information such as water quality and obstacles in the detection area.Therefore,accurate location information of sensor nodes is required,which is also one of the performance indicators of underwater node localization algorithms.However,unlike land wireless sensor network nodes,underwater nodes are affected by ocean currents,making the entire network dynamic.Fortunately,the speed of objects in the underwater environment of offshore waters is semi-periodic,which means that the movement of underwater objects is predictable.Therefore,a scalable localization with mobility prediction for underwater sensor networks(SLMP)is proposed.However,the localization accuracy of the SLMP algorithm is insufficient and the calculation cost is too high.Therefore,it is very important to improve the localization accuracy of the predictive localization algorithm(1)First,introduce the basic concepts and basic theories related to UWSNs.Then,summarize the relevant theories of node localization technology.Finally,summarize the advantages and disadvantages and research directions of underwater node localization algorithms.(2)In order to solve the problems of low localization accuracy and higher complexity in the underwater mobile prediction localization algorithm.Therefore,an underwater mobile predictive localization algorithm based on modified backtracking search optimization algorithm(MP-MBSA)is proposed.The algorithm uses the MBSA algorithm to improve the localization accuracy of the anchor node.In the unknown node location stage,using the cooperation mechanism and the group mobility of underwater objects to prediction the location information of the unknown node.Experimental results show that,compared with some classic mobile predictive localization algorithms,the MP-MBSA algorithm improves the localization accuracy of the network and reduces the running time of the algorithm.(3)In order to further improve the localization accuracy of the network,an underwater mobile predictive localization algorithm based on the local topology and knowledge learning backtracking search optimization algorithm(MP-KLBSA-LoT)is proposed.First,an improved BSA algorithm that KLBSA-LoT algorithm is proposed.Then,the KLBSA-LoT algorithm is used to improve the localization accuracy of the anchor node.In the unknown node location stage,using the cooperation mechanism and the group mobility of underwater objects to prediction the location information of the unknown node.Experimental results show that,the MP-KLBSA-LoT algorithm obviously improves the localization accuracy of the network compared to some classic mobile predictive positioning algorithms,the running time of the algorithm is higher.