Adaptive Black Hole Coverage Strategy Combining Optimization Mechanism and Variable Spiral Strategy in WSN
Aiming at the problems that black hole algorithm is prone to fall into local optimality during node deployment in wireless sen-sor network,which leads to uneven distribution of nodes and slow convergence rate in late period,an adaptive black hole algorithm based on fusion optimization mechanism and variable spiral strategy is proposed.Black hole population with optimal solution is established and black hole optimization mechanism is introduced.The star population is no longer optimized around a black hole in the iterative process.After multiple iterations,the black hole population is reduced,that is,the optimal solution is located in a more precise region,the algo-rithm is less likely to fall into a local optimum,and a local search is performed around the vicinity of the optimal solution,thus achieving a balance between global and local optimization capabilities.Secondly,the spiral shape in the process of star position updating is dynam-ically adjusted,and the spiral shape gradually decreases with the decreasing of the black hole population size,that is,the star can be mined in the area closer to the optimal solution to improve the optimization accuracy.Simulation results show that after the deployment of the improved black hole algorithm,the node coverage is improved and the overlap area and coverage blind area are significantly re-duced.Besides,the node travel distance is reduced.
万方数据
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