Research On Path Planning Algorithms In Wireless Sensor Network Based On Chaotic Ant Colony

Wireless Sensor Network(WSN),as the cutting-edge technology of this century,can monitor real-time data in specific areas,greatly expanded human perception capabilities.Therefore,it is widely used in practical fields with different needs.However,the monitoring area is often in a poor environment and the wireless charging technology has not been fully developed,the node energy in the network cannot be replenished in time.Therefore,designing an effective paths planning algorithm to reduce node energy consumption has become the core research in this field.This paper takes the routing path as the research object,which combined with the unique ergodicity,adaptability and high precision of the chaotic ant colony algorithm,the following specific research is performed on the problems of excessive path length,imbalanced network energy consumption and low solution accuracy:(1)Area Routing Chaotic Ant Colony(ARCAC)algorithm is proposed.The algorithm first takes sectors as the unit,which can select each hop node that takes into account both the remaining energy and path length.It introduces potential and entropy factors to enhance the perceptual ability within the population based on the chaotic ant colony algorithm,which avoiding the population to fall into the local maximum,and effectively improving the accuracy of the solution.Finally,the solution set is re-optimized by adaptive perturbation and the two-way direction selection strategy to ensure the current optimal path life cycle.However,the overall convergence rate of the ambassador population is slow due to initial calculations.(2)Chaotic Max-min Ant Colony(CMAC)algorithm is proposed.Aiming at the problem of slow convergence speed in ARCAC.Based on the maximum and minimum ant colony algorithm,the algorithm first obtains a stagnant local optimal solution set on the basis of ensuring the path fitness;secondly,sets a two-dimensional Tent map as a chaos generator.The uniqueness of the solution set is searched in combination with chaotic characteristics,so as to jump out of the local optimum and improve the accuracy of the solution.Finally,the cross-replacement strategy is used to ensure the life cycle of the current optimal path and reduce the energy consumption caused by redundant iterations.(3)In order to verify the effectiveness of the two algorithms,they are applied to different WSN path planning models for analysis.In the C/S multi-hop model,ARC AC respectively extends the network life cycle by nearly 0.83%and 6.71%,compared with CMAC and other similar algorithms.To better analyze the performance of routing paths,reduce the high-energy performance of data transmission in the C/S multi-hop model.In the mobile agent model,CMAC has prolonged the network life cycle by nearly 5.42%and 7.16%respectively,compared with ARC AC and other similar algorithms.Simulation results show that in a small WSN environment,two types of algorithms can effectively control the node energy consumption and path length.So,they can extend the life cycle,and both have certain optimization effects.But in terms of overall performance,CMAC is superior to ARCAC.Figure[22]table[13]reference[92]...