Performance measurements and modeling of database servers

In this paper we present some experiments on the MySQL database server. The objective of the experiments was to investigate the high load dynamics for varying relation sizes and requests. We show that the dynamics for SELECT (read) requests can be modeled as a modified M/M/1 system, whereas, the dynamics for UPDATE (write) are completely different. Our results can be used for designing control and optimization algorithms for database servers

Application of Control Theory to a Commercial Mobile Service Support System

The Mobile Service Support system (MSS), which Ericsson AB develops, handles the setup of new subscribers and services into a mobile network. Experience from deployed systems show that traffic monitoring and control of the system will be crucial for handling overload situations that may occur at sudden traffic surges. In this paper we identify and explore some important control challenges for this type of systems. Further, we present analysis and experiments showing some advantages of proposed solutions. First, we develop a load-dependent server model for the system, which is validated in testbed experiments. Further, we propose a control design based on the model, and a method for estimation of response times and arrival rates. The main contribution of this paper is that we show how control theory methods and analysis can be used for commercial telecom systems. Parts of our results have been implemented in commercial products, validating the strength of our work

A computational complexity-aware model for performance analysis of software servers

Queueing models are routinely used to analyze the performance of software systems. However, contrary to common assumptions, the time that a software server takes to complete jobs may depend on the total number of active sessions in the server. In this paper, we present a queueing model that explicitly takes into account the time, taken by algorithms in the server, that varies with the user population. The model analytically predicts the response time and the "saturation number" of such systems. We validate our model with simulation and further demonstrate its usefulness by suggesting a heuristic technique to "discover" the complexity of algorithms in server software, solely from response time measurement. We applied the discovery technique to a Web-server test-bed, and found that we can identify the asymptotic behavior of processing time as a function of the user population with a fair amount of accuracy. The results show that this promises to be one of the many "black-box analysis" techniques, often found necessary in the real world.© IEE