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-
Anomaly Detection Overview
==========================
Anomaly Detection (AD) is an Xapp in the Traffic Steering O-RAN use case,
-which uses the following Xapps:
+which perfrom the following tasks:
-#. AD, which iterates per second, fetches UE data from .csv files and send prediction to Traffic Steering
+#. Data will be inserted into influxDB when xApp starts. This will be removed in Future when data will be coming via KPIMON to influxDB.
+#. AD, which iterates per 10 mili-second, fetches UE information from databse and send prediction to Traffic Steering
#. Traffic Steering send acknowldgement back to AD.
Expected Input
--------------
-The AD Xapp expects a prediction-input in following structure:
-
-UEPDCPBytesDL UEPDCPBytesUL UEPRBUsageDL UEPRBUsageUL S_RSRP S_RSRQ S_SINR N1_RSRP N1_RSRQ N1_SINR N2_RSRP N2_RSRQ N2_SINR UEID ServingCellID N1 N2 MeasTimestampRF
+The AD Xapp expects input in following structure:
- 300000 123000 25 10 -43 -3.4 25 -5 -6.4 20 -68 -9.4 17 12345 555011 555010 555012 30:17.8
-
+ {
+ 'du-id' : 1003,
+ 'nrCellIdentity' : "c3/B13",
+ 'prb_usage' : 23.0,
+ 'rsrp' : 84.0,
+ 'rsrq' : 65.0,
+ 'rssinr':65.0,
+ 'targetTput' : 0.1,
+ 'throughput' : ,
+ 'ue-id' : "Waiting passenger 1",
+ 'x' : -556,
+ 'y' : -1160,
+ 'measTimeStampRf' : "2021-05-12T07:43:51.652"
+ }
Expected Output
---------------
-The AD Xapp should send a prediction for Anomulous UEID along with timestamp
+The AD Xapp should Detect Anomulous UE's and send those UE's information
as a JSON message via RMR with the following structure:
{
- "UEID" : 12371,
- "MeasTimestampRF" : "2020-11-17 16:14:25.140140"
- }
-
-
+ 'ue-id' : "Waiting passenger 1",
+ 'measTimeStampRf' : "2021-05-12T07:43:51.652",
+ 'du-id' : 1003,
+ 'Degradation': "RSRP RSSINR"
+ }
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Code Review / ric-app / ad.git / blobdiff