Investigation about broadcast scheduling in fuzzy Hopfield network based on the Internet of things
Zheng Yan-Jie, Zheng Yan-Ling, Ma Qing-Yong · 2011
To overcome resource conflict occurred in data broadcasting among nodes which are shared and interferential each other on radio channels in sensor network, in the article we propose fuzzy Hopfield neural network(FHNN) in order to solve TDMA broadcast scheduling problem of wireless sensor network. We considered it as discrete energy minimization problem and mapped it into Hopfield neural network with the fuzzy c-means strategy to realize TDMA schedule for nodes in communication network. The fuzzy Hopfield neural network(FHNN) increases the convergence rate and decreases the processing time for broadcast scheduling problem. Simulation confirms that FHNN could be applied to the Internet of things which is covered everything all over the world. It could improve the visibility and control of the supply chain.