Quantifying the sustainability impact of data center availability

Marwah, Manish; Maciel, Paulo; Shah, Amip; Sharma, Ratnesh; Christian, Tom; Almeida, Virgílio A. F.; Araujo, Carlos; Souza, Erica; Callou, Gustavo; Silva, Bruno Rafael Vieira Souza; Galdino, Sérgio Mário Lins; Pires, Jose

doi:10.1145/1773394.1773405

Cited by 43 publications

(22 citation statements)

References 11 publications

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“…This study focuses on conducting the previous optimization technique in a real-world data center power architecture (from HP Labs, Palo Alto, CA, USA [63]), which assesses the dependability, as well as the environmental impact and operational energy cost. In this case, the number of scenarios to be analyzed through all possible combinations is huge.…”

Section: Case Study IImentioning

confidence: 99%

An Integrated Modeling Approach to Evaluate and Optimize Data Center Sustainability, Dependability and Cost

et al. 2014

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Data centers have evolved dramatically in recent years, due to the advent of social networking services, e-commerce and cloud computing. The conflicting requirements are the high availability levels demanded against the low sustainability impact and cost values. The approaches that evaluate and optimize these requirements are essential to support designers of data center architectures. Our work aims to propose an integrated approach to estimate and optimize these issues with the support of the developed environment, Mercury. Mercury is a tool for dependability, performance and energy flow evaluation. The tool supports reliability block diagrams (RBD), stochastic Petri nets (SPNs), continuous-time Markov chains (CTMC) and energy flow (EFM) models. The EFM verifies the energy flow on data center architectures, taking into account the energy efficiency and power capacity that each device can provide (assuming power systems) or extract (considering cooling components). The EFM also estimates the sustainability impact and cost issues of data center architectures. Additionally, a methodology is also considered to support the modeling, evaluation and optimization processes. Two case studies are presented to illustrate the adopted methodology on data center power systems.

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Section: Case Study IImentioning

confidence: 99%

An Integrated Modeling Approach to Evaluate and Optimize Data Center Sustainability, Dependability and Cost

et al. 2014

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“…The architectures analyzed are similar to those present in HP Labls, Palo Alto, CA, USA [35]. Beginning from the real power infrastructure depicted in Figure 8 (A1), the other architectures were defined according to the reliability importance index [23].…”

Section: Architecturesmentioning

confidence: 99%

A Power Load Distribution Algorithm to Optimize Data Center Electrical Flow

2013

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Energy consumption is a matter of common concern in the world today. Research demonstrates that as a consequence of the constantly evolving and expanding field of information technology, data centers are now major consumers of electrical energy. Such high electrical energy consumption emphasizes the issues of sustainability and cost. Against this background, the present paper proposes a power load distribution algorithm (PLDA) to optimize energy distribution of data center power infrastructures. The PLDA, which is based on the Ford-Fulkerson algorithm, is supported by an environment called ASTRO, capable of performing the integrated evaluation of dependability, cost and sustainability. More specifically, the PLDA optimizes the flow distribution of the energy flow model (EFM). EFMs are responsible for estimating sustainability and cost issues of data center infrastructures without crossing the restrictions of the power capacity that each device can provide (power system) or extract (cooling system). Additionally, a case study is presented that analyzed seven data center power architectures. Significant results were observed, achieving a reduction in power consumption of up to 15.5%.

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“…5 will depend on the magnitude of the difference Ymax − Ymin. In most practical scenarios of interest, this value is expected to be at least moderately large: recent work suggests that storing energy Ymin to last about a minute is sufficient to offer reliable data center operation [14], while Ymax can vary between 5-20 minutes (or even higher) due to reasons such as UPS units being available only in certain sizes and the need to keep room for future IT growth. Furthermore, the UPS units are sized based on the maximum provisioned capacity of the data center, which is itself often substantially (up to twice [10]) higher than the maximum actual power demand.…”

Section: Battery Modelmentioning

confidence: 99%

Optimal power cost management using stored energy in data centers

Urgaonkar

Neely

et al. 2011

Proceedings of the ACM SIGMETRICS Joint International Conference on Measurement and Modeling of Computer Systems

376

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Since the electricity bill of a data center constitutes a significant portion of its overall operational costs, reducing this has become important. We investigate cost reduction opportunities that arise by the use of uninterrupted power supply (UPS) units as energy storage devices. This represents a deviation from the usual use of these devices as mere transitional fail-over mechanisms between utility and captive sources such as diesel generators. We consider the problem of opportunistically using these devices to reduce the time average electric utility bill in a data center. Using the technique of Lyapunov optimization, we develop an online control algorithm that can optimally exploit these devices to minimize the time average cost. This algorithm operates without any knowledge of the statistics of the workload or electricity cost processes, making it attractive in the presence of workload and pricing uncertainties. An interesting feature of our algorithm is that its deviation from optimality reduces as the storage capacity is increased. Our work opens up a new area in data center power management.

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Quantifying the sustainability impact of data center availability

Cited by 43 publications

References 11 publications

An Integrated Modeling Approach to Evaluate and Optimize Data Center Sustainability, Dependability and Cost

An Integrated Modeling Approach to Evaluate and Optimize Data Center Sustainability, Dependability and Cost

A Power Load Distribution Algorithm to Optimize Data Center Electrical Flow

Optimal power cost management using stored energy in data centers

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