Telecom Network Analyser
Machine data in Telecom domain encompasses all data generated by machines such as data emanating from base stations, mobile devices, remote infrastructure, networks, sensors, applications, services and so on.
The future of Telecom demands Automated, and more Optimized Network Monitoring to match with speed at which Telecom industry is growing with evolved business models, higher data rates and Network Innovations. Real-time Network Intelligence is the way-to-go.
Our Application ‘Telecom Network Analyser’ is a POC Splunk based Big Data Application to be enhanced and used for large-scale Network Performance Monitoring of Telecom Equipments in 3G/4G/LTE Networks.
Generic Use Cases
- Analysis of GSM/LTE/4G Network data at BTS/eNodeB & BSC/RNCs for performance and capacity fine tuning.
- Real time analysis of Radio network bandwidth spikes, downtime and dropped call information and troubleshooting
- Summary providing high level data snapshots, detail inspection and trend analysis of faults over time
- To generate dashboards and form searches which give complete log analysis of the Mobile Switch's real time search analysis, working, compliance, fault detection, etc.
- Telecom Network Analyser - Splunk Enterprise SDK based Application
- Python based Auto Upload Script for Counter Data Collection
- R-script for Predictive Analytics using Time Series Algorithm
- Auto upload & Storage of BSC Counter data
- Descriptive Visualizations of Network Status and Health
- Predictive Analysis of KPI Trends
- Statistical Analysis of KPI Data
- Support for Daily, Hourly, Weekly Data records
- Weak Cells Detection
Full Installation Read me documentation is provided in the the zip attached along with this submission.
Demo Data and Extra info
We are providing a sample Counter Data file (A20140101.0045-20140101.0100_BSC#30.csv) received from the Network Equipments(BSCs) every 15 mins. Also attached is the XML file (STAT_CS_CALL_REL_BS.xml) required for parsing the Counter Data using Python Scripts. In actual deployment the data is collected directly from the BSCs and is uploaded to Splunk.
- Splunk Enterprise 6.2
- Python 2.7
- Splunk SideView Utils App
Future Enhancement Possibilities for LTE Network
- Dynamic Dashboard indications on KPI
- All KPI which are getting tracked should be visible on Dashboard
- Data collection from all the eNodeBs spread across multiple LSM
- There can be multiple LSM in the network
- Historic Data Analysis
- In addition to run time data analysis, data need to be made available for historic analysis
- Trouble detection , prediction and Localization based on KPI Trend Analysis
- KPI Trend Analysis may be made available for trouble prediction and detection
- Contributors for each KPI may be made available to localize the trouble makers
- Manageability of tool by Operations team
- Tool should be simple such that Network operators can define and monitor KPI Parameters
- Scalability for future revisions
- Tool should be able to take care of adapting new statistics counters while defining KPIs
This app is being created by Ashish Kumar Yadav,Saket Kumar & Neha Bandi from L&T Technology Services. For more information about this App and more work we do in Splunk, please contact us at Splunk.Solutions@lnttechservices.com OR email@example.com.