Research On UWSNs Coverage And Clustering Strategy Based On Multi-objective Spider Algorithm

Underwater wireless sensor networks(UWSNs)is a Self-organizing network structure that combined different nodes with the way of acoustic communication.Coverage monitoring is the basic task that needs to be completed.Because the sea water environment is extremely complex,it is difficult to supplement or replace the power supply.Therefore,it is not only to meet a certain coverage,but also to consider the energy consumption of the network,which is called the problem of energy saving.Obviously,in the essence of mathematics,this problem belongs to the multi-objective optimization problem.In view of the convergence and distribution of the existing multi-objective evolutionary algorithms need to be improved,in order to better solve the problem of energy conservation,this topic is studied from the following two aspects.Firstly,in order to improve the convergence and distribution of the multi-objective evolutionary algorithm,the clustering spider algorithm with good convergence performance on the single objective optimization problem is introduced,and a multi objective cluster spider algorithm is proposed with the NSGA-II multi-objective framework.First,according to the objective of multi-objective optimization,a new normalized fitness value calculation formula is proposed,and the non-dominated ranking and crowding distance are weighed,and the individual is evaluated effectively.Secondly,through the universal gravitation factor,we can improve the calculation method of the vibration perception ability,in order to balance the influence of individual fitness and distance on the individual performance.Thirdly,we improved the updating mode of the female and male population,and the convergence speed and population diversity of the equilibrium algorithm.Finally,an environment selection strategy based on cyclic cosine distance is proposed to update female and male populations.The test results on the ZDT and DTLZ test set show that compared with the 6 representative multi-objective evolutionary algorithms so far,the algorithm has better distribution and obvious convergence performance advantage.Secondly,UWSNs covering and clustering strategy is proposed based on Multi-objective Social Spider Optimization Algorithm.In order to close the actual coverage scene of the underwater wireless sensor network nodes and solve the problem of coverage and energy-saving,a covering mathematical model of 3D oriented perception model is set up in this paper,and a mulching and maintaining clustering algorithm based on multi-objective spider algorithm is proposed.The main contents of the algorithm include multi-objective optimization period and multi-objective decision period.Firstly,a function optimization model is established based on the energy consumption standard deviation and coverage rate of cluster head nodes,secondly,the multi-objective spider algorithm is applied to solve this problem,Finally,the optimal routing scheme is selected from the non-dominated solution set obtained by TOPSIS.The experimental results show that the algorithm balances the load and energy consumption of nodes and effectively prolongs network lifetime while maintaining good network coverage.