Introduction to Data Center Energy Flow and Thermal Management

Joshi, Yogendra; Kumar, Pramod

doi:10.1007/978-1-4419-7124-1_1

Cited by 8 publications

(10 citation statements)

References 19 publications

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“…In this work the computer software COMSOL Multiphysics 1 has been used to solve the data center flow problem using the FEM. The nodal equation is obtained by integrating over the control volumes, for the case s this is described by the following equation, dx s dx (6) and for which the same boundary conditions as the FEM can be imposed to obtain a numerical solution. The approach imposed by the FVM leads to a conservative scheme where the flux on a boundary is equal to the opposing flux in the adjacent cell, making it a useful method in solving partial differential equations based on conservation laws.…”

Section: Finite Element Methodsmentioning

confidence: 99%

Three computational methods for analysing thermal airflow distributions in the cooling of data centres

Boer

Johns

Delbosc³

et al. 2018

HFF

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This paper uses three different numerical simulation technologies to analyse the thermal airflow distribution in a simple example data center layout. The numerical approaches used are based on finite element, finite volume and lattice Boltzmann methods and are respectively implemented via commercial Multiphysics software, opensource CFD code and GPU based code developed by the authors. Each method includes an appropriate turbulence model and the simulation results focus on comparison of the three methods when applied to 2 rows of datacom racks with cool air supplied by a computer room air conditioner and distributed via an underfloor plenum. Good quantitative agreement between the three methods is seen in terms of the inlet temperatures to the Datacom equipment.Key Words: Data center cooling, Lattice Boltzmann, Finite Element, Finite Volume. IntroductionData centers are facilities hosting information and communications technology (ICT) infrastructure, usually laid out in rows of 2m tall racks. Their operation provides digital services across a range of sectors. The quantity and density of these ICT systems results in a distributed and complex dynamic generation of heat throughout the facility that needs to be transported away from the ICT, referred to as datacom, equipment. This is usually achieved by air cooling, where the heat is transferred and ultimately rejected to the outside environment. The growth of these facilities has been considerable, with data centers consuming only 0.12% of US energy consumption for the year 2000 [1] and that figure having risen to over 2% only ten years later, in 2010 [2]. Globally this figure is currently closer to 1.5%, at a growth of roughly 11% per year over the last decade [3], and approximately 45% of this energy is used in the removal of heat [4]. Improvements to the energy efficiency of these facilities are rapidly becoming paramount, due to the need to reduce both running costs and environmental impact [5].

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Section: Finite Element Methodsmentioning

confidence: 99%

Three computational methods for analysing thermal airflow distributions in the cooling of data centres

Boer

Johns

Delbosc³

et al. 2018

HFF

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“…Cloud providers offer many different types of cloud services, from software to the artificial intelligence platform, from virtual machines to storage systems. These services are generally provided by using data centers with a large number of pieces of computing equipment [4]. Data centers are energy-intensive facilities with an average rack density of 8.2 kW as indicated in the 2020 State of the Data Center report [5] which can even reach 43 kW per rack using efficient water-cooling techniques [6].…”

Section: Introductionmentioning

confidence: 99%

“…The proposed ECO-VMAP model 4 differentiates from the previous work as follows. The model is based on the multi-unit nondiscriminatory combinatorial auction model in which the bidders may express their valuations for any combination of VM types declaring complementarities and substitutabilities among the requested VMs.…”

Section: Related Work and A Brief Introduction To Combinatorial Amentioning

confidence: 99%

An Energy-Aware Combinatorial Virtual Machine Allocation and Placement Model for Green Cloud Computing

Gamsiz

Özer

2021

IEEE Access

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Resource allocation is an important problem for cloud environments. This paper introduces an energyaware combinatorial auction-based model for the resource allocation problem in clouds. The proposed model allows users of a cloud to submit their virtual resource requests as bids using the provided bidding language which allows complementarities and substitutabilities among those resources to be declared. The model finds the most profitable mutually satisfiable set of winning bids, and the corresponding allocation of virtual resources to the users while considering the placement of virtual resources to the available physical resources in the cloud by executing an optimization problem. During the optimization, the model also takes account of the non-linear energy requirements of the physical resources based on their utilization levels to find a placement with the lowest energy cost, thus, providing an energy-aware solution to the resource allocation problem. The associated optimization problem is formally defined and formulated using integer programming. Since the optimization problem is intractable, four heuristic methods are also proposed. To evaluate the performance of the model and the proposed heuristic methods, several experiments are conducted on a comprehensive test suite. The results demonstrate the benefits of the proposed model, and the high-quality solutions provided by the proposed methods.

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“…Cooling processes serve a critical role in the effective operation of data centers [1]- [3]. There are strict temperature and humidity requirements that co-location (Colo) service providers must adhere to, often stipulated within the terms of a service level agreement (SLA) between the provider and the client leasing the data hall premises for the placement and operation of server infrastructures [4], [5].…”

Section: Introductionmentioning

confidence: 99%

A Novel Methodology to Improve Cooling Efficiency at Data Centers

et al. 2019

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Data centers are mission-critical infrastructures. There are strict service level requirements and standards imposed on operators and maintainers to ensure reliable run-the-clock operation. In the context of thermal management and data hall environmental control, the formation of hot and cold spots around server cabinets are especially undesirable, and can result in overheating, lifespan reductions, and performance throttling in the former and condensation damage in the latter. In this paper, we present a comprehensive multi-pronged methodology in data center environmental control, comprising computational fluid dynamics (CFD) simulation-aided predictive design first-stage approach, and a complementing Internet of Things (IoT) reactive management system that autonomously monitors and regulates fluctuations in thermal parameters. The novel hybrid methodology is demonstrated on various test scenarios derived from real-world context, and prototypes of the IoT system have been experimentally validated. The approach is shown to be efficient in eliminating unfavourable environmental variations and provides an enhanced understanding of common design problems and respective mitigation measures.

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Introduction to Data Center Energy Flow and Thermal Management

Cited by 8 publications

References 19 publications

Three computational methods for analysing thermal airflow distributions in the cooling of data centres

Three computational methods for analysing thermal airflow distributions in the cooling of data centres

An Energy-Aware Combinatorial Virtual Machine Allocation and Placement Model for Green Cloud Computing

A Novel Methodology to Improve Cooling Efficiency at Data Centers

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