Abstract
Wireless networks are now the most widely used kind of communication. For instance, internet services in homes, businesses, cafés, and e-markets. As a result, it has to be safeguarded against vindictive users who attempt to compromise its authenticity and privacy. Information delivered via these wireless networks also need traffic management. This study describes a method for managing wireless network congestion that makes use of machine learning and fuzzy logic. The following are some of the factors that must be taken into account for the congestion control decision mechanism:Transmission energy, queue length, receiver distance, transmission speed, and allocated cost. A desired outcome for congestion management may be identified and its effectiveness assessed using machine learning technologies once these parameters are reviewed using fuzzy logic.