The Radio Access Network (RAN) plays a vital role in enabling mobile network connectivity using radio waves. Gaining a comprehensive understanding of RAN applications is crucial, and trace analysis provides valuable insights into their operations. Modern RAN applications can be deployed on different platforms and this can lead to the generation of different trace formats, which complicates the analysis process. Trace analysis and visualization tools, such as Trace Compass, can be used to ease the process, but for each new trace format the user often needs to create new code and visualizations. This is needed also when different trace formats generated by the same application contain similar information. To overcome this limitation, this thesis introduces an innovative approach to generalize the interpretation of traces, enabling to reuse existing analysis and visualization independently of the trace format. Moreover, a Domain Specific Language (DSL) is introduced to simplify the trace analysis procedure. The proposed thesis contributes to a generic approach for analyzing different trace formats, thereby facilitating the analysis of RAN applications deployed across diverse platforms. / Radio Access Network (RAN) spelar en viktig roll när det gäller att möjliggöra anslutning till mobilnät med hjälp av radiovågor. Att få en omfattande förståelse för RAN-applikationer är avgörande, och trace-analys ger värdefulla insikter i deras verksamhet. Moderna RAN-applikationer kan driftsättas på olika plattformar, vilket kan leda till att olika trace-format genereras, vilket komplicerar analysprocessen. Verktyg för trace-analys och visualisering, som Trace Compass, kan användas för att underlätta processen, men för varje nytt trace-format måste användaren ofta skapa ny kod och nya visualiseringar. Detta behövs även när olika traceformat som genereras av samma applikation innehåller liknande information. För att övervinna denna begränsning introducerar denna avhandling en innovativ metod för att generalisera tolkningen av trace-data, vilket gör det möjligt att återanvända befintlig analys och visualisering oberoende av traceformatet. Dessutom introduceras ett domänspecifikt språk (DSL) för att förenkla trace-analysförfarandet. Den föreslagna avhandlingen bidrar till en generisk metod för analys av olika trace-format, vilket underlättar analysen av RANapplikationer somanvänds på olika plattformar.

<p><em>With the advent of huge multicore processors, complex hardware, intermingled networks and huge disk storage capabilities the programs that are used in the system and the code which is written to control them are increasingly getting large and often much complicated. There is increase in need of a framework which tracks issues, debugs the program, helps to analyze the reason behind degradation of system and program performance. Another big concern for deploying such a framework in complex systems is to the footprint of the framework upon the setup. LTTng project aims to provide such an effective tracing and debugging toolset for Linux systems. Our work is to measure the effectiveness of LTTng in a Multicore Environment and evaluate its affect on the system and program performance. We incorporate Control and Data Flow analysis of the system and the binaries of LTTng to reach for a conclusion.</em></p>

<p>Debugging in real time is imperative for telecommunication networks with their ever increasing size and complexity. In event of an error or an unexpected occurrence of event, debugging the complex systems that controls these networks becomes an insurmountable task. With the help of tracing, it is possible to capture the snapshot of a system at any given point of time. Tracing, in essence, captures the state of the system along with the programs currently running on the system. LTTng is one such tool developed to perform tracing in both kernel space and user space of an application. In this thesis, we evaluate the effectiveness of LTTng and its impact on the performance on the applications traced by it. As part of this thesis we have formulated a comprehensive load matrix to simulate varying load demands in a telecommunication network. We have also devised a detailed experimental methodology which encompasses a collection of test suites used to determine the efficiency of various LTTng trace primitives. We were also able to prove that, in our experiments, LTTng’s kernel tracing is more efficient than User Space Tracing and LTTng’s User Space Tracing has a performance impact of around three to five percent.</p>

With the advent of huge multicore processors, complex hardware, intermingled networks and huge disk storage capabilities the programs that are used in the system and the code which is written to control them are increasingly getting large and often much complicated. There is increase in need of a framework which tracks issues, debugs the program, helps to analyze the reason behind degradation of system and program performance. Another big concern for deploying such a framework in complex systems is to the footprint of the framework upon the setup. LTTng project aims to provide such an effective tracing and debugging toolset for Linux systems. Our work is to measure the effectiveness of LTTng in a Multicore Environment and evaluate its affect on the system and program performance. We incorporate Control and Data Flow analysis of the system and the binaries of LTTng to reach for a conclusion.

Debugging in real time is imperative for telecommunication networks with their ever increasing size and complexity. In event of an error or an unexpected occurrence of event, debugging the complex systems that controls these networks becomes an insurmountable task. With the help of tracing, it is possible to capture the snapshot of a system at any given point of time. Tracing, in essence, captures the state of the system along with the programs currently running on the system. LTTng is one such tool developed to perform tracing in both kernel space and user space of an application. In this thesis, we evaluate the effectiveness of LTTng and its impact on the performance on the applications traced by it. As part of this thesis we have formulated a comprehensive load matrix to simulate varying load demands in a telecommunication network. We have also devised a detailed experimental methodology which encompasses a collection of test suites used to determine the efficiency of various LTTng trace primitives. We were also able to prove that, in our experiments, LTTng’s kernel tracing is more efficient than User Space Tracing and LTTng’s User Space Tracing has a performance impact of around three to five percent.

5G is becoming reality with companies rolling out the technology around the world. In 5G,the Radio Access Network (RAN) is moving from a monolithic-based architecture into a cloud-based microservice architecture for the purpose of simplifying deployment and manageability,and explore scalability and flexibility. Thus, the transition of functionalities from a proprietaryhardware-based system into a more distributed and flexible virtualized system is ongoing. Insuch systems, legacy methods performance monitoring is relevant, wheresystem tracingplaysan important role. System tracing is important for the purpose of performance analysis of anygiven system. However, current tools were designed thinking about monolith architectureswhere, therefore, in new distributed architectures, new tracing tools need to be developed. System tracing often requires special permissions to be executed in applications running ina virtualized third-party environment. Unfortunately, not all applications running in a dis-tributed virtualized environment can be given such special access, at the risk of compromis-ing security and stability of the system. However, tracing data needs to be also collected fromapplications running in such environments. This thesis addresses the challenge of remotely configuring and controlling the system tracingtool with the example of LTTng in applications that run as part of a distributed virtualizedenvironment with Kubernetes. We explore the problem of remotely controlling and configuringsystem tracing as well as to optimize data collection. The main outcome is a tool able to re-motely control and configure system tracing tools. In addition, a proof-of-concept is presentedwith working demos for basic system tracing commands. It was discovered that a relay-based solution can be exposed outside the cluster via node-portwhich can relay incoming requests on-wards to any number of microservices. However, dis-covery of these microservices that are running system tracing tools is critial. Service discoverymechanism’s were brought forth and introduced to the system for the purpose of disoveringmicroservices with system tracing tools. Tracing data that is saved locally can be extracted bythe user through the relay-based solution or sent directly to any remote system using LTTngrelay daemon functionality. Comparison between directly executing commands in a bash shelland the remote CLI was measured. It has been concluded that the overall the response timeof both Linux and LTTng commands that are sent through the remote CLI is 1.96 times longerthan directly executing these commands in a bash shell. This was accounted to the fact thatcommands sent over the network traffic within the kubernetes cluster which is the cost ofremotely being able to control and configure system tracing tools. This being said, there arestill many steps that can be taken to improve the solution and to develop a more productionready solution.i