The Effects of Temperature Variation on Data Center IT Systems

MoDCS - Modelling of Distributed and Concurrent Systems <www.modcs.org>MoDCS - Modelling of Distributed and Concurrent Systems <www.modcs.org>
The Effects of Temperature Variation on
Data Center IT Systems
IEEE SMC International Conference on Systems,
Man, and Cybernetics (IEEE SMC’13)
Rafael Roque, Gustavo Callou, Kádna Camboin, João Ferreira and Paulo Maciel
Presenter: Rafael Roque rrs4@cin.ufpe.br

MoDCS - Modelling of Distributed and Concurrent Systems <www.modcs.org>
Plan
• Introduction
• Preliminaries
– Data Center.
– Dependability.
• Models
• Case Study
– Architecture Description
– Model
– Result
• Conclusions

Introduction
• This paper proposes an approach for
evaluating the effect of such temperature
changes on data center IT systems.
• In this approach, the evaluation is
accomplished with stochastic Petri net (SPN)
models which simulate the impact of
temperature on the availability of variously
specified IT and cooling architectures.
• A case study is included to demonstrate the
applicability of the proposed models.

Data Center
• Infrastructures of Data Center
– Energy
• UPS, Step Down Transformer, Subpanel, Power Strip
– IT
• Router, Switch, Server
– Cooling
• CRAC, Chiller, Cooling Tower

Dependability
• Dependability of a computer system can be understood as the
ability to avoid service failures that are more frequent and
more severe than is acceptable. The concepts of dependability
consists of three shares:
• Threats: comprising the faults, errors and failures. A system
failure is the event that occurs when delivering service does
not happen correctly.
• Attributes: enables obtaining quantitative measures, which
are often crucial to the analysis of the services offered.
Dependability attributes include the concepts of availability,
reliability, safety, integrity and maintainability.
• Means: the dependability analysis comprises calculating
indices such as Mean Time To Failure (MTTF) and Mean Time
To Repair (MTTR).

Energy model
•Example 1
•Example 2
wall conductivity indexArea converts to BPU IT heat produced efficiency time extracting heat
desired temperature

Arrhenius model
Example 1
Example 2

Reliability block diagrams
• The RBD model allows analysis of reliability and
availability of complex systems using block diagrams to
represent each component.
• The blocks can be connected in series and/or parallel
based on the operating mode of each component.
a b

Stochastic Petri Nets
• As an example, the series composition is presented as
follows, considering SPN. The same model can
represent a system in parallel without loss of
generality, only changing the expression to be
measure.

Case Study
• The case study focuses on the dependability analysis of
various data center configurations for a hotel company.
The main objective is to quantify the impact of the
cooling system on the availability of the IT system,
considering financial losses.
• This paper assumed that the hotel company consists of
5 employees who support the data center, to which
each receives a monthly amount of $5,000.00, which
results in an expenditure of $ 240,000.00 per year for
the company.

Case Study
• The company receives its billing by means of a system
of online booking of rooms, which are considered the
sale of two reservations per hour, where each
reservation costs $ 120.00.
• The cost of electricity to functioning of the data center
was $ 0.11 per kWh.
• Therefor this study evaluates eight different data center
configurations, where each configuration is composed
of IT and cooling architectures.

Architecture Description

Energy model
HP ower advisor
HP power advisor

Reliability block diagrams

Operational Mode (Availability)

Cost and Profit metrics
• Acquisition Cost (AC)
• Operational Cost (OC)
• Income (I)
• Employees Cost (EC)
• Profit (Pf)
• Maintenance Cost (MC)
• Financial Losses (FL)

Results
$794,99
$556,03

Conclusions
• The paper presented a set of formal models for
estimating financial losses in relation to the impact of
temperature variation on data center IT systems. RBD
and SPN models were adopted to compute the
dependability evaluation.
• Additionally, the SPN dependence model was proposed
to quantify both the impact of the IT system on the
cooling system and the impact of the cooling system on
the availability of the IT system.

Thank You!
The Effects of Temperature Variation on Data Center IT
Systems
João Ferreira jfsj3@cin.ufpe.br
IEEE SMC International Conference on Systems, Man, and Cybernetics
(IEEE SMC’13)

The Effects of Temperature Variation on Data Center IT Systems

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