Wireless Network AI Traffic Management
Deployed BQN platform's artificial intelligence optimization solution to enhance
wireless network service stability and achieve efficient traffic management.
Customer Status
- Using separated wired and wireless networks
- Rapidly increasing trend in wireless traffic usage
- Need for systematic traffic management via AI-based QoS
- Urgent need to improve service stability and Quality of Experience (QoE)
Deployment Goals
- Secure wireless network stability and improve operational convenience
- Enhance user perceived speed and guarantee quality
- Secure bandwidth by controlling non-business traffic
- Realize AI operational automation for network traffic management
BQN Operation Mechanism
TCP Optimization & Acceleration
Minimizes response latency and maximizes data transfer efficiency to expand effective bandwidth.
Automatic Congestion Management (ACM)
Machine learning-based Plug-N-Play operation detects and optimizes network congestion in real-time.
AI-based QoS
Regulates Windows updates and streaming loads, and automatically controls unnecessary sites like Webtoons.
Proven by Data
Overwhelming Speed Improvement
Operational Benefits
-
Maximize Network Availability
Delivers performance beyond physical line limits through TCP optimization
-
Automated Failure Prevention
Machine learning ACM manages congestion 24/7 to improve stability
-
Infrastructure Cost Reduction
Eliminates unnecessary bandwidth waste through traffic blocking and control
"AI Network Optimization System, BQN Platform"
The BQN platform is configured in-line between the UTM and the backbone switch,
analyzing, optimizing, and accelerating traffic for all users connected through wireless APs in real-time.