ICBC has obtained a patent for network congestion control. This technology can effectively and quickly suppress network congestion and improve network stability and efficiency.
Network congestion is a common problem that causes network transmission to slow down and may even cause the network to crash. This ICBC patent provides a new solution that can monitor network traffic and adjust network transmission parameters in real time to avoid network congestion.
This technology can identify bottlenecks and congestion points in the network by analyzing network traffic data, and then automatically adjust parameters such as transmission rate and packet size to optimize network transmission efficiency. This automatic adjustment method can quickly respond to network changes and avoid the tediousness and inaccuracy of manual adjustment.
ICBC’s network congestion control patent has high practical value and market prospects. It can be widely used in various network environments, such as corporate internal networks, data centers, cloud computing, etc., to improve network stability and efficiency, reduce network operating costs, and bring better network experience to users.
The method by which ICBC obtained the patent for network congestion control:
1. Network congestion control method based on cache space: This method obtains the occupancy status of the cache space and the round-trip time of business data. Delay to quickly suppress network congestion. When it is determined that the transmission network is in a congested state, the near-end service equipment can be allowed to implement a congestion control policy.
2. Network congestion control method based on business priority: This method identifies the priority of business data and transmits high-priority business data first, thereby avoiding network congestion.
3. Network congestion control method based on traffic scheduling: This method schedules network traffic to avoid excessive concentration of traffic in the network, thereby reducing network congestion.
4. Network congestion control method based on deep learning: This method uses deep learning technology to predict and analyze network traffic, discover network congestion trends in advance, and take corresponding measures for prevention and control.
5. Network congestion control method based on collaborative control: This method uses collaborative work between multiple network devices to simultaneously deal with network congestion problems. For example, when a certain network device detects congestion, it can send congestion signals to other devices, triggering a collaborative control mechanism to jointly solve the congestion problem.
6. Network congestion control method based on dynamic thresholds: This method monitors and controls network traffic by setting dynamic thresholds. When the traffic exceeds the threshold, the congestion control mechanism is triggered to limit further growth of traffic.
7. Network congestion control method based on load balancing: This method distributes traffic to multiple paths or servers to avoid overloading of a single path or server, thereby reducing the degree of network congestion.