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Utilizing Hardware Monitoring to Improve the Performance of Industrial Systems
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The drastically increasing use of Information and Communications Technology has resulted in a growing demand for network capacity. In this Licentiate thesis, we show how to monitor, model and finally improve network performance for large industrial systems. We also show how to use modeling techniques to move performance testing to an earlier design phase, with the aim to reduce the total development time of large systems. Our first contribution is a low-intrusive method for long-term hardware characteristic measurements of production nodes located at customer sites. Our second con- tribution is a technique to mimic the hardware usage of a production environment by creating a characteristics model. The cloned environment makes function test suites more realistic. The goal when creating the model is to reduce the system development time by moving late-stage performance testing to early design phases thereby improving the quality of the test environment. The third and final contribution is a network performance improvement where we dynamically trade computational capacity for a message round-trip time reduction when there are CPU cycles to spare. We have implemented an automatic feedback controlled mechanism for transparent message compression resulting in improved messaging performance between interconnected network nodes. Our mechanism continuously evaluates eleven compression algorithms on message stream content and network congestion level. The message subsystem will use the compression algorithm that provides the lowest messaging time. If the message content or network load change, a new evaluation is performed. We have conducted several case studies in an industrial environment and verified all contributions on a large telecommunication system manufactured by Ericsson. System engineers frequently use the monitoring and modeling functionality for debugging purposes in production environments. We have deployed all techniques in a complicated industrial legacy system with minimal impact. We show that we can provide not only a solution but a cost-effective solution, which is an important requirement for industrial systems.
