Abstract: Disclosed are computerized systems and methods for a decision intelligence (DI)-based framework that automatically and/or dynamically provides mechanisms for managing, optimizing and configuring a WiFi network at a location. The framework provides network management utilizing edge processing capabilities to bridge local WiFi and cloud systems. The framework implements comprehensive device typing through multi-layered analysis combining passive monitoring, deep packet inspection and hybrid deterministic-probabilistic classification methods. State synchronization between local and cloud networks can be achieved through hierarchical data modeling and differential synchronization algorithms. The framework can implement advanced features that include automated channel optimization, QoS management, and security monitoring.

Abstract: Disclosed are computerized systems and methods for a decision intelligence (DI)-based framework that automatically and/or dynamically provides mechanisms for managing, optimizing and configuring a WiFi network at a location. The framework provides network management utilizing edge processing capabilities to bridge local WiFi and cloud systems. The framework implements comprehensive device typing through multi-layered analysis combining passive monitoring, deep packet inspection and hybrid deterministic-probabilistic classification methods. State synchronization between local and cloud networks can be achieved through hierarchical data modeling and differential synchronization algorithms. The framework can implement advanced features that include automated channel optimization, QoS management, and security monitoring.

Abstract: Disclosed are computerized systems and methods for a decision intelligence (DI)-based framework that automatically and/or dynamically provides mechanisms for managing, optimizing and configuring a WiFi network at a location. The framework provides network management utilizing edge processing capabilities to bridge local WiFi and cloud systems. The framework implements comprehensive device typing through multi-layered analysis combining passive monitoring, deep packet inspection and hybrid deterministic-probabilistic classification methods. State synchronization between local and cloud networks can be achieved through hierarchical data modeling and differential synchronization algorithms. The framework can implement advanced features that include automated channel optimization, QoS management, and security monitoring.

Abstract: Disclosed are computerized systems and methods for a decision intelligence (DI)-based framework that automatically and/or dynamically provides mechanisms for managing, optimizing and configuring a WiFi network at a location. The framework provides network management utilizing edge processing capabilities to bridge local WiFi and cloud systems. The framework implements comprehensive device typing through multi-layered analysis combining passive monitoring, deep packet inspection and hybrid deterministic-probabilistic classification methods. State synchronization between local and cloud networks can be achieved through hierarchical data modeling and differential synchronization algorithms. The framework can implement advanced features that include automated channel optimization, QoS management, and security monitoring.

Abstract: A computer-implemented packet detection method includes a source at a first address transmitting packets to a terminal at a second address without transmitting the packets to any intermediate address during the transmission, the terminal receiving the packets, the terminal reassembling the received packets; the terminal performing a process referring to the reassembled packets, and the terminal transmitting packets to a destination at a third address which is different from the first address without transmitting the adjusted packets to any intermediate address during the transmission. Without extra operations and packet traffic, the computer-implemented packet detection method can be applied to virus detection, malicious content detection, or some statistics.

Abstract: A computer-implemented packet detection method includes a source at a first address transmitting packets to a terminal at a second address without transmitting the packets to any intermediate address during the transmission, the terminal receiving the packets, the terminal reassembling the received packets; the terminal performing a process referring to the reassembled packets, and the terminal transmitting packets to a destination at a third address which is different from the first address without transmitting the adjusted packets to any intermediate address during the transmission. Without extra operations and packet traffic, the computer-implemented packet detection method can be applied to virus detection, malicious content detection, or some statistics.