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- Ahmed, Kazi Pushpa, et al.
(author)
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Application of Predictive Maintenance in Industry 4.0: A Use-Case Study for Datacenters
- 2021
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In: 2021 3rd International Conference on Sustainable Technologies for Industry 4.0 (STI). - : IEEE.
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Conference paper (peer-reviewed)abstract
- In the context of the upcoming 4th generation industrial revolution (industry 4.0), mechanical failures in the cyber-physical systems have huge financial impacts. The IT industry like Google, Facebook, Microsoft, etc. mostly depends on the Datacenters (DCs) to assure the quality of services. The equipment of the DC including the power supply system and the computational resources are sensitive to supplied power quality, thus predictive maintenance is needed to prevent failures and limit financial losses. The predictive maintenance assures operational security based on the monitored data that can characterize the failures of the physical machines, and also ensures the maximum return of the capital investment by prolonging the useful life of the equipment. The size of the monitored data typically occupies large memory space that can compare with “big-data” nowadays. Thus, the big-data-sized monitored data analysis is an additional computational challenge to characterize the failures of physical machines, hence, schedule the predictive maintenance. However, characterizing the failure and repair time of the major components based on the measured data is still a challenge that is the goal of this paper. Meanwhile, the revenue of the business also largely depends on the accuracy of predictive maintenance in general. In this paper, a predictive maintenance approach is presented based on the stochastic failure time of the major components of the DC. Additionally, the business challenges for predictive maintenance considering industry 4.0 are also analyzed in this paper.
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| 2. |
- Ahmed, Kazi Main Uddin, 1989-, et al.
(author)
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A Novel Reliability Index to Assess the Computational Resource Adequacy in Data Centers
- 2021
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In: IEEE Access. - NY : IEEE. - 2169-3536. ; 9, s. 54530-54541
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Journal article (peer-reviewed)abstract
- The energy demand of data centers is increasing globally with the increasing demand for computational resources to ensure the quality of services. It is important to quantify the required resources to comply with the computational workloads at the rack-level. In this paper, a novel reliability index called loss of workload probability is presented to quantify the rack-level computational resource adequacy. The index defines the right-sizing of the rack-level computational resources that comply with the computational workloads, and the desired reliability level of the data center investor. The outage probability of the power supply units and the workload duration curve of servers are analyzed to define the loss of workload probability. The workload duration curve of the rack, hence, the power consumption of the servers is modeled as a function of server workloads. The server workloads are taken from a publicly available data set published by Google. The power consumption models of the major components of the internal power supply system are also presented which shows the power loss of the power distribution unit is the highest compared to the other components in the internal power supply system. The proposed reliability index and the power loss analysis could be used for rack-level computational resources expansion planning and ensures energy-efficient operation of the data center.
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| 3. |
- Ahmed, Kazi Main Uddin, 1989-, et al.
(author)
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A Review of Data Centers Energy Consumption And Reliability Modeling
- 2021
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In: IEEE Access. - : IEEE. - 2169-3536. ; 9
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Research review (peer-reviewed)abstract
- Enhancing the efficiency and the reliability of the data center are the technical challenges for maintaining the quality of services for the end-users in the data center operation. The energy consumption models of the data center components are pivotal for ensuring the optimal design of the internal facilities and limiting the energy consumption of the data center. The reliability modeling of the data center is also important since the end-user’s satisfaction depends on the availability of the data center services. In this review, the state-of-the-art and the research gaps of data center energy consumption and reliability modeling are identified, which could be beneficial for future research on data center design, planning, and operation. The energy consumption models of the data center components in major load sections i.e., information technology (IT), internal power conditioning system (IPCS), and cooling load section are systematically reviewed and classified, which reveals the advantages and disadvantages of the models for different applications. Based on this analysis and related findings it is concluded that the availability of the model parameters and variables are more important than the accuracy, and the energy consumption models are often necessary for data center reliability studies. Additionally, the lack of research on the IPCS consumption modeling is identified, while the IPCS power losses could cause reliability issues and should be considered with importance for designing the data center. The absence of a review on data center reliability analysis is identified that leads this paper to review the data center reliability assessment aspects, which is needed for ensuring the adaptation of new technologies and equipment in the data center. The state-of-the-art of the reliability indices, reliability models, and methodologies are systematically reviewed in this paper for the first time, where the methodologies are divided into two groups i.e., analytical and simulation-based approaches. There is a lack of research on the data center cooling section reliability analysis and the data center components’ failure data, which are identified as research gaps. In addition, the dependency of different load sections for reliability analysis of the data center is also included that shows the service reliability of the data center is impacted by the IPCS and the cooling section.
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| 4. |
- Ahmed, Kazi Main Uddin, 1989-, et al.
(author)
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Reliability Analysis of Internal Power Supply Architecture of Data Centers in Terms of Power Losses
- 2021
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In: Electric power systems research. - : Elsevier. - 0378-7796 .- 1873-2046. ; 193
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Journal article (peer-reviewed)abstract
- The number of data centers and the energy demand are increasing globally with the development of information and communication technology (ICT). The data center operators are facing challenges to limit the internal power losses and the unexpected outages of the computational resources or servers. The power losses of the internal power supply system (IPSS) increase with the increasing number of servers that causes power supply capacity shortage for the devices in IPSS. The aim of this paper is to address the outage probability of the computational resources or servers due to the power supply capacity shortage of the power distribution units (PDUs) in the IPSS. The servers outage probability at rack-level defines the service availability of the data center since the servers are the main computational resource of it. The overall availability of the IPSS and the power consumption models of the IPSS devices are also presented in this paper. Quantitative studies are performed to show the impacts of the power losses on the service availability and the overall availability of the IPSS for two different IPSS architectures, which are equivalent to the Tier I and Tier IV models of the data center.
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| 5. |
- Ahmed, Kazi Main Uddin, 1989-, et al.
(author)
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Risk Assessment of Server Outages Due To Voltage Dips In the Internal Power Supply System of a Data Center
- 2021
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In: CIRED 2021 - The 26th International Conference and Exhibition on Electricity Distribution. - : Institution of Engineering and Technology. ; , s. 708-712
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Conference paper (peer-reviewed)abstract
- The data centers host sensitive electronic devices like servers, memory, hard disks, network devices, etc., which are supplied by the power supply units. The regulated direct current (DC) output of the power supply units fluctuates with input voltage variation since they typically contain single phase switch-mode power supplies. The voltage dips caused by faults in the internal power supply system of the data center can be large enough to violate the Information Technology Industry Council (ITIC) proposed voltage-tolerance guideline. The output of the power supplies, hence the operation of the servers will be interrupted due to such voltage dips. In this paper, the outage probability of the servers caused by the voltage dips are analyzed for different fault location in the internal supply system of a data center.
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