The solution that we propose for the analysis, classification and monitoring of IP traffic is focused on our product TRAMS.
Thanks to it, it can both characterize with quantitative data the use of network by applications /nodos [/ user], and detect anomalous situations in such use.
This way we get to optimize network planning (in terms of sizing and security, QoS and traffic control policies), improve the operation of the network (management availability, performance failures and including validation of the effectiveness of the policies implemented) and have the knowledge of the users in terms of their experience of their use of the network.
Advantages of the solution (supported by SCATI, TRAMS traffic analysis engine):
{slider High-Precision|closed}
The classification is based on high precision machine learning algorithms, able to adapt to the characteristics of the traffic through workouts.
{slider Very low computational cost}
Given that the normal operation of the system requires no inspection of the content of packages, unlike techniques DPI. This allows that you can install on computers in general purpose and low cost standard.
{slider High scalability}
Capable of processing high-capacity links traffic (> 100 Gb/s), by feeding of flows sampled. The sampling also reduces the load on the routers.
{slider Real-time monitoring}
Processing of information with frequencies up to 1 minute
{slider Low impact on network settings}
It is based on Netflow traffic accounting for widely deployed in teams of network operators and large enterprises.
{slider Respect for the principle of secrecy of correspondence}
Unlike fully DP-based solutions, it does not analyze the content of the information that makes up the classified traffic.
{slider Open integration}
With external OSS/BSS systems and Business Intelligence environments.
{/sliders}
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