Benedek Kovács MsC in Information Technology (2005), PhD in Maths and Computing Sciences (2012) at Budapest University of Technology and Economics (BUTE). He has joined Ericsson in 2005 as a System Tester focusing on Robustness, Performance, Dimensioning and Characteristics of single network nodes. He has researched overload control for IMS and has written Characteristics Specifications for UDC systems. Today, he works as a System Engineer for Telecommunication Network Solutions focusing on novel technologies that enable Superior Network Performance.
The complexity of mobile networks is continuously increasing, meshing whole countries, including several network functions and interfaces between them. Ericsson is one of the biggest manufacturers of network functions like radio base stations, user databases and application servers. All these functions run a software logic that handles signaling protocols, maintaining user and service information and communicates with peer functions in a standardized way. Despite the well-defined functional roles and signaling protocols, testing every node and every interface between them individually does not necessarily imply that the network as a whole behaves as requested. Therefore, network level testing of signaling sequences are necessary and useful. Automation of such a testing requires big data technology, the support of multiple protocols and smart techniques to correlate signaling messages captured on different network interfaces.
Scaling up test solutions in parallel with complexity growth requires the raise of abstraction level from entity to holistic view. Apply the concept of troubleshooting in test solutions, meaning that it is no longer the aim to identify and observe faults but it is also the aim to automatically filter the relevant data to the tester. In order to provide high quality and 99.999% availability, system stability should be frequently tested with high load. Typically the 72 hours weekend test can generate more terabytes of data which cannot be analyzed manually. This requires the application of big data technology in real-time performance testing and a new approach to focus on the most important information instead of collecting all the traffic and analyze without any automation.
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