# Intelligent Monitoring of Data Center Physical Infrastructure
## 3 Results
### Experimental Results of a Reduced Number of Alarms by RCM  
The RCM was run on stored data collected between 2016 and 2019 and filtered by a correlation process. The data query starts at a node or a group of nodes without children. Nodes that share the same group of parents have the same internode. The procedure checks the parental status of all nodes in the possible alarm state. If the parent of the observed node is in an alarm state, the repeat loop procedure is performed in the method, checking the state of the next parent until it reaches a parent without further errors. When you follow a parental path up the tree diagram, you need to check the one redundancy path with the highest parental priority. Later, the paths of parents with lower priority factors are checked. After the use of data queries, different RCM results are possible:  
* having a malfunction;
* No connected nodes with the current event;
* A Level 1 event can have a root cause on Level 0;
* The data connections of multiple line paths are checked with possible events;
* The priority classification of alarms due to the reliability of the node is triggered. When managing and acquiring a great amount of data, data overwrite, data reduplication, missing transfer data, and many other related events can happen. Because of these possible events, data filtering has to be done in the selected time interval. Filtering also enables the same type of event gathered via different types of interfaces to be marked as the same event. This scenario is frequently used when the DC infrastructure is operational, because it is not possible to anticipate all events during the design stage. During the first experiment, first the data center power supply level was simulated. The same test data were manually inserted into the database in Tables 3 and 4 (\"Events\"). Table 3 shows the number of alarms without using RCM, and Table 4 shows that when it was used. The main cause was inserted as a failure of the diesel generator due to a filter failure. All nodes had an alarm event. For a more transparent presentation, the alarm nodes were grouped into parts connected to the same device or cabinets and power devices. For example, a component in the line labeled \"DEG\" (Tables 3 and 4) refers to a diesel electric generator. The power supplies of the system cabinets are marked with \"Psc 1, 2, 3\". The power distribution units are designated as \"Pdu 1, 2\" and they are in all IT cabinets. The \"UPS A, B\" labels represent uninterruptible power supplies and all components related to them. The \"Cch A, B\" are cooling chillers. \"Psc A, B\" represent power supplies of the cooling devices. The successive steps in the process from \"Events\" to \"Alerts\" were systematically derived as shown in Table 4. The RCM inquiry procedure (Figures 2 and 3) started with a childless node. In the event that the internode existed as the main node, all other children of the internode were ignored. Several specific causes were identified due to special rules stored with node entities. To find the root cause of a group of related events, the reverse method was used. After filtering the data, a correlation process was used to combine the associated alarm events with the same parent group. A correlation step must be performed in order to search for all related events among alarms. Correlation does not imply causation [48; 49], which means that one alarm event does not necessarily cause another. It can only be assumed, as to the definitions, that if the events are correlated, that means that a change in one event causes a change in another node. The correlation factor in this approach is related connectivity. If there are any alarm events that have the same parents, they are grouped together, so the node path of these events is checked in the root cause analysis only once. After linking related events to internodes, the correlation method yielded results for each part of the system, as shown in Table 4 in the \"Correlation\" row. Table 4 shows that the number of alarm events decreased.