7,545 research outputs found
Minimizing data center cooling and server power costs
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On Reliability-Aware Server Consolidation in Cloud Datacenters
In the past few years, datacenter (DC) energy consumption has become an
important issue in technology world. Server consolidation using virtualization
and virtual machine (VM) live migration allows cloud DCs to improve resource
utilization and hence energy efficiency. In order to save energy, consolidation
techniques try to turn off the idle servers, while because of workload
fluctuations, these offline servers should be turned on to support the
increased resource demands. These repeated on-off cycles could affect the
hardware reliability and wear-and-tear of servers and as a result, increase the
maintenance and replacement costs. In this paper we propose a holistic
mathematical model for reliability-aware server consolidation with the
objective of minimizing total DC costs including energy and reliability costs.
In fact, we try to minimize the number of active PMs and racks, in a
reliability-aware manner. We formulate the problem as a Mixed Integer Linear
Programming (MILP) model which is in form of NP-complete. Finally, we evaluate
the performance of our approach in different scenarios using extensive
numerical MATLAB simulations.Comment: International Symposium on Parallel and Distributed Computing
(ISPDC), Innsbruck, Austria, 201
Power Management Techniques for Data Centers: A Survey
With growing use of internet and exponential growth in amount of data to be
stored and processed (known as 'big data'), the size of data centers has
greatly increased. This, however, has resulted in significant increase in the
power consumption of the data centers. For this reason, managing power
consumption of data centers has become essential. In this paper, we highlight
the need of achieving energy efficiency in data centers and survey several
recent architectural techniques designed for power management of data centers.
We also present a classification of these techniques based on their
characteristics. This paper aims to provide insights into the techniques for
improving energy efficiency of data centers and encourage the designers to
invent novel solutions for managing the large power dissipation of data
centers.Comment: Keywords: Data Centers, Power Management, Low-power Design, Energy
Efficiency, Green Computing, DVFS, Server Consolidatio
Energy-Efficient Management of Data Center Resources for Cloud Computing: A Vision, Architectural Elements, and Open Challenges
Cloud computing is offering utility-oriented IT services to users worldwide.
Based on a pay-as-you-go model, it enables hosting of pervasive applications
from consumer, scientific, and business domains. However, data centers hosting
Cloud applications consume huge amounts of energy, contributing to high
operational costs and carbon footprints to the environment. Therefore, we need
Green Cloud computing solutions that can not only save energy for the
environment but also reduce operational costs. This paper presents vision,
challenges, and architectural elements for energy-efficient management of Cloud
computing environments. We focus on the development of dynamic resource
provisioning and allocation algorithms that consider the synergy between
various data center infrastructures (i.e., the hardware, power units, cooling
and software), and holistically work to boost data center energy efficiency and
performance. In particular, this paper proposes (a) architectural principles
for energy-efficient management of Clouds; (b) energy-efficient resource
allocation policies and scheduling algorithms considering quality-of-service
expectations, and devices power usage characteristics; and (c) a novel software
technology for energy-efficient management of Clouds. We have validated our
approach by conducting a set of rigorous performance evaluation study using the
CloudSim toolkit. The results demonstrate that Cloud computing model has
immense potential as it offers significant performance gains as regards to
response time and cost saving under dynamic workload scenarios.Comment: 12 pages, 5 figures,Proceedings of the 2010 International Conference
on Parallel and Distributed Processing Techniques and Applications (PDPTA
2010), Las Vegas, USA, July 12-15, 201
Energy challenges for ICT
The energy consumption from the expanding use of information and communications technology (ICT) is unsustainable with present drivers, and it will impact heavily on the future climate change. However, ICT devices have the potential to contribute signi - cantly to the reduction of CO2 emission and enhance resource e ciency in other sectors, e.g., transportation (through intelligent transportation and advanced driver assistance systems and self-driving vehicles), heating (through smart building control), and manu- facturing (through digital automation based on smart autonomous sensors). To address the energy sustainability of ICT and capture the full potential of ICT in resource e - ciency, a multidisciplinary ICT-energy community needs to be brought together cover- ing devices, microarchitectures, ultra large-scale integration (ULSI), high-performance computing (HPC), energy harvesting, energy storage, system design, embedded sys- tems, e cient electronics, static analysis, and computation. In this chapter, we introduce challenges and opportunities in this emerging eld and a common framework to strive towards energy-sustainable ICT
Greening Multi-Tenant Data Center Demand Response
Data centers have emerged as promising resources for demand response,
particularly for emergency demand response (EDR), which saves the power grid
from incurring blackouts during emergency situations. However, currently, data
centers typically participate in EDR by turning on backup (diesel) generators,
which is both expensive and environmentally unfriendly. In this paper, we focus
on "greening" demand response in multi-tenant data centers, i.e., colocation
data centers, by designing a pricing mechanism through which the data center
operator can efficiently extract load reductions from tenants during emergency
periods to fulfill energy reduction requirement for EDR. In particular, we
propose a pricing mechanism for both mandatory and voluntary EDR programs,
ColoEDR, that is based on parameterized supply function bidding and provides
provably near-optimal efficiency guarantees, both when tenants are price-taking
and when they are price-anticipating. In addition to analytic results, we
extend the literature on supply function mechanism design, and evaluate ColoEDR
using trace-based simulation studies. These validate the efficiency analysis
and conclude that the pricing mechanism is both beneficial to the environment
and to the data center operator (by decreasing the need for backup diesel
generation), while also aiding tenants (by providing payments for load
reductions).Comment: 34 pages, 6 figure
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