A Review of Data Centers Energy Consumption and Reliability Modeling

Ahmed, Kazi Main Uddin; Bollen, M.H.J.; Alvarez, Manuel

doi:10.1109/access.2021.3125092

Cited by 63 publications

(11 citation statements)

References 165 publications

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“…(1) Reliability Indices for User Service. In [21], user service reliability refers to the readiness of an IoT monitoring center system to deliver the promised IT service to a user. In [22], the service reliability is also emphasized since the probability of fulfilling the service requests without latency is characterized by this index.…”

Section: The Reliability Modeling Of Iot Monitoring Centersmentioning

confidence: 99%

Energy Consumption Optimization of an IoT Monitoring Center Based on a Max-Min Ant Colony Algorithm

Tong

2023

Wireless Communications and Mobile Computing

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As a result of the green IoT, application layer users are increasingly seeking more services, and it is particularly important to reduce the energy consumption of an IoT monitoring center while ensuring service reliability. In this paper, the max-min ant colony algorithm is proposed to effectively solve the problems of user service reliability and energy consumption optimization of an IoT monitoring center. First, the service reliability of the application layer users is modeled based on a Markov chain, and the quantitative reliability performance indicators are given. Second, an optimization model between the user service reliability and the energy consumption of an IoT monitoring center is established. Finally, the optimization problem is solved based on the improved max-min ant system. Simulation experimental results show that compared with the improved FFD algorithm, the average power consumption of the max-min ant colony algorithm can be reduced by up to 7.14%.

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Section: The Reliability Modeling Of Iot Monitoring Centersmentioning

confidence: 99%

Energy Consumption Optimization of an IoT Monitoring Center Based on a Max-Min Ant Colony Algorithm

Tong

2023

Wireless Communications and Mobile Computing

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“…More HDCs have been constructed to meet this demand, which has caused a contradiction between huge energy consumption and the limited power supply, and it is necessary to balance the performance of HDCs with the capability of the external environment. In addition, operators of HDCs try to find business opportunities by taking advantage of natural advantages [ 3 ]. At present, there are two main development directions for large-scale data centers: (1) reducing PUE and improving the energy efficiency of data centers, and (2) purchasing renewable energy to provide power, rather than using a traditional power supply [ 1 ].…”

Section: Introductionmentioning

confidence: 99%

Prediction of Overall Energy Consumption of Data Centers in Different Locations

Zhang

Liu

2022

Sensors

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The use of big data leads to higher demands for hyperscale data centers (HDCs) in terms of the scale and quantity required for data storage and processing. Before the construction of an HDC, it is necessary to comprehensively analyze the economic budget according to the energy requirements and potential energy cost. We propose a global energy consumption prediction framework based on the power usage effectiveness (PUE) calculation that considers all heat sources and power consumption. The framework integrates physical models and a statistical framework that combines IT equipment energy consumption and data center energy consuming predictions. Furthermore, the framework provides a method to calculate the carbon emissions and electricity cost of the data center. Using hourly meteorological data as climate parameters, combined with a limited range of energy parameters, the annual PUE values of 60 regions were estimated, and a further analysis of the Carbon Usage Effectiveness (CUE) and electricity costs in China was conducted as an example. Based on experimental validation and an evaluation of real-time data, our framework can predict the overall energy consumption of HDCs effectively, filling a gap in HDC research in the Asia-Pacific region and providing a basis for HDC feasibility analysis.

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“…In the event of an AC grid failure, the system immediately switches to backup mode [ 16 , 17 ]. With the AC–DC input stage, there is the possibility of the implementing power factor correction [ 16 , 17 , 18 , 19 , 20 , 21 , 22 ].…”

Section: Introductionmentioning

confidence: 99%

“…UPS systems cover a wide range of power levels, from single-phase systems rated at less than 1 kVA, to three-phase systems rated at more than 1000 kVA. High power systems, designed for large equipment and data centers, operate from battery banks with voltages in the range of hundreds of volts [ 16 , 17 , 21 ]. Smaller scale systems, for use in a small office or home office (SOHO) environments, generally include inverters that operate on 12 V or 24 V batteries and are mainly of offline and line-interactive type [ 16 , 17 ].…”

Section: Introductionmentioning

confidence: 99%

Comparative Analysis of Modulation Techniques on the Losses and Thermal Limits of Uninterruptible Power Supply Systems

et al. 2022

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This paper presents a comparative analysis of electrical losses and subsequent thermal limits of the inverter of UPSs for small office and home office (SOHO) applications. For this, three PWM modulation techniques applied to the full-bridge converter are considered, with power levels of 100–1000 W and switching frequencies of 30–120 kHz. To validate the electrical and thermal models, a dSapce MicroLabBox equipment was used to implement modulation techniques on a commercial 1000 W UPS, and a Keysight DAQ970A data logger was used for temperature measurements. As a result, the MOSFET temperatures and losses are obtained for the three modulation techniques evaluated, indicating the best scenario for use and its influence on the UPS autonomy time.

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A Review of Data Centers Energy Consumption and Reliability Modeling

Cited by 63 publications

References 165 publications

Energy Consumption Optimization of an IoT Monitoring Center Based on a Max-Min Ant Colony Algorithm

Energy Consumption Optimization of an IoT Monitoring Center Based on a Max-Min Ant Colony Algorithm

Prediction of Overall Energy Consumption of Data Centers in Different Locations

Comparative Analysis of Modulation Techniques on the Losses and Thermal Limits of Uninterruptible Power Supply Systems

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