Method and arrangement for data clustering

1. A method in a network node for determining input information for creation of a data traffic clustering model, wherein data traffic via the network node comprises a plurality of user data flows of known data categories, the method comprising:

obtaining data descriptors of the data flows, wherein the data descriptors describe physical parameters of the data flows;

obtaining flow information of the data flows; and

determining clustering model input information based on the obtained data descriptors and the obtained flow information, wherein the determining comprises at least one of:

determining constraints on data samples from data flows with the same categories, wherein the constraints are determined on data samples of at least one of:

data flows that originate from different source IP addresses and are destined for a same destination IP address;

data flows that originate from a same source IP address and a same source port of the IP address; and

data flows with different flow information but with a same source IP address; and

selecting a subset of the data descriptors by:

calculating values of required bandwidths of various processing resources for calculation of the data descriptors, and calculating values of content information of a respective data descriptor of each data flow;

comparing the values of required bandwidths and the values of content information with bandwidth and content information thresholds, respectively; and

selecting the subset of the data descriptors based on the comparing; and

transmitting data indicative of the clustering model input information to another network node for creation of a data traffic clustering model based on the clustering model input information.

2. The method of claim 1 , wherein the flow information of the data flows comprises port-related flow information, IP address-related flow information, or both, of the data flows.

3. The method of claim 1 , wherein constraints determined between data samples from data flows with the same data categories comprise information obtained from deep packet inspection of the data flows.

4. The method of claim 1 , wherein the constraints determined between data samples from data flows with the same data categories comprise data descriptors of the data flows.

5. The method of claim 1 , wherein the selection of the subset of the data descriptors is based on the comparing of the content information, enabling an optimized clustering model accuracy.

6. The method of claim 1 , wherein the selection of the subset of the data descriptors is based on the comparing of the required bandwidths, enabling an optimized data profiling processing performance.

7. The method of claim 1 , wherein determining clustering model input information comprises determining user activity information based on user input for defining clusters.

8. A network node for determining input information for creation of a data traffic clustering model for data traffic passing via the network node, where the data traffic comprises data flows of known data categories, the network node comprising:

an input port configured to:

obtain data descriptors of the data flows, wherein the data descriptors comprise physical parameters of the data flows; and

obtain flow information of the data flows; and

a processing circuit configured to determine clustering model input information based on the obtained data descriptors of the data flows and based on the obtained flow information of the data flows from the input port, and further configured to perform at least one of:

determining constraints on data samples from data flows with the same categories, wherein the constraints are determined on data samples of at least one of:

data flows that originate from different source IP addresses and are destined for a same destination IP address;

data flows that originate from a same source IP address and a same source port of the IP address; and

data flows with different flow information but with a same source IP address; and

selecting a subset of the data descriptors by:

calculating values of required bandwidths of various processing resources for calculation of the data descriptors, and calculating

values of content information of a respective data descriptor of each data flow;

comparing the values of required bandwidths and the values of content information with bandwidth and content information thresholds, respectively; and

selecting the subset of the data descriptors based on the comparing; and

an output port configured to transmit data indicative of the clustering model input information to another network node for creation of a data traffic clustering model based on the clustering model input information.

9. The network node of claim 8 , wherein the input port is further configured to obtain port-related flow information, IP address-related flow information, or both, of the data flows.

10. The network node of claim 8 , wherein the processing circuit is configured to select the subset of the data descriptors based on the comparing of the content information, enabling an optimized clustering model accuracy.

11. The network node of claim 8 , wherein the processing circuit is configured to select the subset of the data descriptors based on the comparing of the required bandwidths, enabling an optimized data profiling processing performance.

12. The network node of claim 8 , wherein the network node is any one of a base station, a serving general packet radio service support node, a gateway general packet radio service support node, a broadband remote access server, and a digital subscriber line access multiplexer.