Research On WSN Routing Algorithm And Application Based On Bionic Optimization

In recent years,wireless sensor networks(WSNs)have been widely used in some fields where humans cannot access to or work in.WSNs sensor nodes can replace humans to collect and process required information.In WSNs,routing optimization and network lifetime are the highlight spots of attention.Routing optimization refers to finding an optimal path solution that satisfies the constraints under the circumstances of specific network and routing requirements,thereby improving the overall network routing quality and effectively allocating and managing network resources.However,the exhaustion of node energy or the failure caused by unexpected conditions will cause dynamic changes in the network topology.If some key nodes in the network fail,it will cause partial network paralysis,which will affect communication transmission and network life.As a bionic optimization algorithm based on the natural phenomenon of Brownian motion,ITO's algorithm has the ability to combine local exploration with global optimization.Compared with other intelligent algorithms,the ITO algorithm,as a new bionic optimization algorithm,has a unique adaptive ability,which can flexibly adjust the algorithm's search ability through changes in particle radius and ambient temperature.Based on the ITO algorithm,this paper designs a new path weight update rule by improving the combination of drift and wave processes and introducing new learning strategies.This rule makes the algorithm more suitable for solving the problems of dynamic topology and increasing network life in WSNs.Combined with the laboratory cloud platform vending machine system,the energy clustering protocol has been improved to address the problems of different models of vending machines and location changes.Through hierarchical clustering of three-level energy nodes,the overall topology of WSNs can be reduced when frequent dynamic topologies occur.Impact of network performance.Secondly,combined with the improved ITO algorithm to improve the performance of WSNs dynamic topology,the calculation of high-quality routing paths is completed in a short time according to the Quality of Service metrics.The simulation results show that,on the basis of ensuring system stability,the algorithm greatly reduces the end-to-end average delay and average node energy consumption of WSNs,and performs well in dynamic topology networks.The main research work of this paper is as follows:(1)On the basis of consulting a large number of domestic and foreign literature,analyze the existing problems of existing routing optimization algorithms in solving WSN routing problems,and the advantages and disadvantages of ITO's algorithm.It is found that the existing routing algorithms are difficult to adapt to the dynamic topology change of WSNs,and most of the clustering algorithms cannot guarantee the overall network life and low energy consumption of the nodes on the basis of adapting to the dynamic topology,and provide quality of service.(2)Aiming at the problem that the ITO algorithm solves the multi-constrained Qo S routing optimization problem in WSNs,the convergence rate is too slow,and it is easy to fall into the local optimal solution,which leads to the low success rate of the algorithm.An improved ITO algorithm based on multi-strategy collaborative optimization is proposed.algorithm.By improving the combination of drift and fluctuation process,this algorithm proposes a new cooperative updating strategy,introduces dual cognitive strategy and multi-elite guided learning strategy,and designs a new path weight updating rule.This rule makes the intensity of drift particles and wave particles in the algorithm change flexibly according to individual fitness,and is adaptive.(3)Based on the improved ITO algorithm,the energy clustering model is introduced to make the WSN routing algorithm based on bionic optimization applied to the control of vending machine system on the cloud platform of our laboratory and realize the control of vending machine self-organizing network.Compared with other clustering methods,it significantly reduces the number and time of computing nodes,and speeds up the WSNs response time.Secondly,combining with the improved ITO algorithm to solve the dynamic topology problem of WSNs,the search of the optimal path is completed according to the Qo S metrics,which not only guarantees the response time and end-to-end delay of WSNs,but also further improves the energy consumption of nodes and improves the overall network life.(4)The WSN routing algorithm is applied to the self-organizing network of vending machines,which eliminates the trouble of large numbers of traditional vending machines,frequent inspection and maintenance of personnel,and high complexity,which reduces the work intensity of operating personnel.At the same time,it solves the problem that the traditional network and routing algorithms use wired communication,which causes high application costs.