Access Control Strategy of Heterogeneous Wireless Networks Based on DFNN for Smart Distribution Grid

According to the requirements of smart distribution grid (SDG), an access control strategy based on dynamic fuzzy neural network (DFNN) in heterogeneous wireless networks for SDG is proposed to improve the quality of service (QoS) of the communication business of SDG. A neural network system is built in heterogeneous access control model of SDG with the objective of taking the equal blocking probability of access networks as system parameter to enforce learning process, which has better dynamic adaptability for load balancing of the fuzzy neural network. Due to such problem that neural network generate too many rules that may influence the result in input layer, rules are added automatically through calculating completeness of current system rules by DFNN, and rules also can be deleted dynamically by computing the importance of all rules, which make system rules work effectively without redundancy. The simulation results show that proposed DFNN obviously decrease the blocking probability of access networks by comparing with that of MLB algorithm. At the same time, DFNN simplify the structure of neural network and enforce the importance of rules with FNN algorithm, which has lower access blocking ratio and better balance effect.