Utilizing Hardware Monitoring to Improve the Quality of Service and Performance of Industrial Systems

The drastically increased use of information and communications technology has resulted in a growing demand for telecommunication network capacity. The demand for radically increased network capacity coincides with industrial cost-reductions due to an increasingly competitive telecommunication market. In this thesis, we have addressed the capacity and cost-reduction problems in three ways. Our first contribution is a method to support shorter development cycles for new functionality and more powerful hardware. We reduce the development time by replicating the hardware utilization of production systems in our test environment. Having a realistic test environment allows us to run performance tests at early design phases and therefore reducing the overall system development time. Our second contribution is a method to improve the communication performance through selective and automatic message compression. The message compression functionality monitors transmissions continuously and selects the most efficient compression algorithm. The message compression functionality evaluates several parameters such as network congestion level, CPU usage, and message content. Our implementation extends the communication capacity of a legacy communication API running on Linux where it emulates a legacy real-time operating system. Our third and final contribution is a framework for process allocation and scheduling to allow higher system performance and quality of service. The framework continuously monitors selected processes and correlate their performance to hardware usage such as caches, floating point unit and similar. The framework uses the performance-hardware correlation to allocate processes on multi-core CPUs for minimizing shared hardware resource congestion.We have also designed a shared hardware resource aware process scheduler that allows multiple processes to co-exist on a CPU without suffering from performance degradation through hardware resource congestion. The allocation and scheduling techniques can be used to consolidate several functions on shared hardware thus reducing the system cost. We have implemented our process scheduler as a new scheduling class in Linux and evaluated it extensively. We have conducted several case studies in an industrial environment and verified all contributions in the scope of a large telecommunication system manufactured by Ericsson. We have deployed all techniques in a complicated industrial legacy system with minimal impact. We have shown that we can provide a cost-effective solution, which is an essential requirement for industrial systems.