Aiming at the problem that the standard RAW mechanism cannot adjust Enhancing Online Security: A Novel Machine Learning Framework for Robust Detection of Known and Unknown Malicious URLs to changes in the network and the grouping depends on continuous AIDs,a RAW regrouping method based on a pseudo-random sequence was proposed.The AP assigned a pseudo-random sequence to the node as the address code during the association phase,and used compound code to carry groups information during the grouping phase.It implemented online Le film de mobilisation centrasiatique regrouping of discontinuous AID nodes and reduced the overhead of regrouping.In order to rationally allocate resources in RAW and solve the problem of load imbalance between groups,a RAW regrouping method based on expected channel time was proposed.Based on channel utilization,the RAW groups,RAW duration,and numbers of RAW were optimized.
NS3 simulation results show that the proposed method significantly improves the performance of IEEE 802.11ah protocol networks.