# Intelligent Monitoring of Data Center Physical Infrastructure
## 1 Introduction  
Intelligent monitoring in today's data centers has increased significantly in recent years. In order to maintain high availability of data, all components of the data center infrastructure must carry out their assigned tasks, including adequate energy support without excessive energy consumption. All physical infrastructure failures, regardless of the level at which they occur, have a significant impact on the effectiveness of information technology (IT) services [1; 2]. Therefore, monitoring and control is important for all existing component parameters in the data center infrastructure system, including energy consumption management, which have become crucial in recent years due to their high economic and environmental impact. The cooling infrastructure consumes a large amount of data center energy. In terms of consumption, it is followed by servers, storage, and other infrastructure elements [3]. A typical data center can consume as much energy as 25,000 households. For instance, data center spaces can consume 100 to 200 times more electricity than standard office spaces. The use of energy in data centers also causes over-heating of the environment [4]. A study by [PERSON] et al. [5] showed that in 2014, data centers consumed 270 TWh of energy worldwide, and that this consumption will have a combined annual growth rate (CAGR) of 5% in the future. For these reasons, data center energy reduction is now regarded as the main concern for data center operators, equally important to (if not more so than) the traditional aspects of availability and security [2; 6; 7]. The basic goals of past research were to clearly define and monitor all processes of data center operation. When such processes are not effectively implemented, inconsistencies in the operation and maintenance of the systems are inevitable, leading to unexpected downtime. The cost of downtime depends on the industry, reaching thousands of dollars per minute. The average cost associated with data center downtime for an unplanned outage is 88851 per minute [8]. Recently, a number of studies on event monitoring and management have been published. Surveys [4; 9] showed the control of alarms in electricity distribution. The basis of these research works was the concept of ontology. On the second ontological level there is an expert system with professional, if-then rules. The determination of rules is based on professional knowledge, which is a complex task aiming to turn knowledge into both intelligible and logical rules. In [5; 10], soft conclusions were used with [PERSON]'s network, but it had limitations in more complex systems. This method was used to detect the location of an event in a distribution network of electricity. For each part of the network, there was a model based on expertise with possible causes of events or failures. In these models, it is a matter of establishing retroactively the cause of events with probability values. In [11], tools with integrated processes, called data center infrastructure management (DCIM), were discussed, highlighting the system connectivity and interconnectivity between the operations of the system support and system for data center operators. Different communication technologies were presented as models for use in the design of data center communication paths. These models can reduce the network operating costs, improve energy efficiency, and increase operational efficiency. DCIM in [12] used tools that monitor, measure, manage, and control the resources and energy consumption of both a data center's IT equipment (servers, storage devices) and its infrastructure components (power distribution units (PDUs), air conditioners, etc.). Event management is a part of DCIM's philosophy, where users have to manually set alarms and prioritize them. In [13; 14], the emphasis is on the general philosophy of event processing, availability, and shortened mean time to repair (MTTR) the system.