A large amount of alarms considerably complicate the root-cause analysis in telecom networks, thus a new alarm filtering algorithm was proposed to minimize the interference on the analysis. Firstly, a quantitative analysis for the alarm data, e.g., the quantity distribution and the average duration, was conducted, and the concepts of alarm impact and high-frequency transient alarm were defined. Subsequently, the importance of each alarm instance was evaluated from four perspectives:the amount of the alarms, the average duration of the alarms, the alarm impact, and the average duration of the alarm instance. Accordingly, an alarm filtering algorithm with O ( n) computation complexity in principle was proposed, where n is the number of alarms under analysis. Single-factor experimental analysis show that the compression ratio of the alarm data has a positive correlation with the alarm amount of a specific alarm element, the average duration of the alarms, the alarm impact, and the duration of the alarm instance; further, the accuracy of the proposed algorithm is improved by 18 percentage points at most compared with Flexible Transient Flapping Determination (FTD) algorithm. The proposed algorithm can be used both for off-line analysis of historical alarm data and for on-line alarm filtering.

In recent years, the complexity of conducting schedulability experiments increases with the rapid development of real-time scheduling research. In general, schedulability experiments are time-consuming in the absence of standardized and modularized experiment tools. Moreover, since the source codes are not publicly available, it is difficult to verify the reported results in the literature, and to reuse and extend the experiments. In order to reduce the repeative work and help the vertification, a basic schedulability experiment framework was proposed. This experiment framework generated task systems through random distribution, and then tested their schedulability, and based on the framework, a novel open-source schedulability platform called SET-MRTS (Schedulability Experiment Toolkit for Multiprocessor Real-Time Systems) was designed and realized. The platform adopted the modular architecture. SET-MRTS consisted of the task module, the processor module, the shared resource module, the algorithm library, the configuration module and the output module. The experimental results show that, SET-MRTS supports uni- and multi-processor real-time scheduling algorithms and synchronization protocol analyses, which can correctly perform the schedulability test and output intuitive experimental results, and support the expansion of the algorithm library. Compared with algorithms in the algorithms library implemented in the experiment, SET-MRTS has good compatibility and expansibility. SET-MRTS is the first open source platform to support a complete experimental process, including algorithmic implementation, parameter configuration, result statistics, charting, and so on.