Network design and optimization have seen significant advancements in recent years, with several trends shaping the landscape:
SDN separates the control plane from the data plane, allowing centralized management and automation of network resources. This results in greater flexibility, scalability, and efficiency.
This approach uses automation and machine learning to align network configurations with business intent, simplifying operations and enhancing network reliability.
Automating routine network tasks speeds up deployment, reduces human error, and improves overall network agility.
The rollout of 5G networks brings faster speeds, lower latency, and increased capacity, enabling new applications and services that require high bandwidth and connectivity.
By processing data closer to the source, edge computing reduces latency and improves performance for real-time applications, making it ideal for IoT devices and cloud services.
AI and machine learning algorithms can analyze network data in real time, predict failures, and optimize performance, enhancing network security and efficiency.
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