The topology control of work-face monitor network based on self-adapting online genetic PID
Abstract：In an allusion to the actual characteristics of the complexity of underground environment, the energy limitation of wireless nodes and the interruption of communication, and in order to solve the problems of network connectivity, link reliability and energy cost, a topology control algorithm for wireless sensor network（WSN） based on the self-adapting online genetic PID （PID of self-adapting online genetic algorithm, SAOGA-PID） in the underground workface was proposed. Based on the local mean algorithm （LMA）, we introduced biological intelligence algorithm and closed-loop control theory to overcome the shortcomings of slow convergence and instability of the existing topology control algorithm, and to improve the energy efficiency and convergence rate. The results show that, compared with the LMA through the close-loop con- trol theory and biological intelligence algorithm, the average start-up energy consumption of the nodes and the start-up energy consumption of all nodes were reduced by 84% and 60% 70%respectively. The time consumption was increased by 9.2%-12.7%, and the conver gence and the energy-effeciency were improved as well.
Keywords：self-adaptgenetic algorithm(GA)wireless sensor networktopology control
Publication Date：2012-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：7( 95-101 )