- Partner: SANREN
- Students: Lungisani Ndlovu (TUT), S’thel’esihle Khuluse (UKZN)
- Project Lead: Daniel Bar-Lev
- Project Mentors: Gary Bezuidenhout
- Year: 2017/2018
The increased complexity in network structures means that manual troubleshooting is becoming impractical and extremely expensive. Therefore there is growing demand for monitoring tools that can troubleshoot, predict and attend to network deficiencies independently.
Network administrators find themselves inundated with automated communication from remote points to monitoring equipment and lack the requisite capabilities to predict and respond based on this information. Possible solutions that have emerged, have been the exploration of Big Data Analytics coupled with Deep Learning methods to identify trends in service behaviour, telemetry data and patterns in issues experienced by Networks.