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Abstract
Cloud computing is offering utility-oriented IT services to users worldwide. Based on a pay-as-you-
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,
ower units, cooling and software), and holistically work to boost data center energy efficiency and
performance. In articular, this pape r 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 © 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 Cloud Sim 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.

Introduction
Computing Utilities, Data Centers and Cloud
Computing: Vision and Potential
In 1969, Leonard Kleinrock [1], one of the chief
scientists of the original Advanced Research Projects
Agency Network
(ARPANET) which seeded the Internet, said: “As of
now, computer networks are still in their infancy, but as
they grow up
and become sophisticated, we will probably see the
spread of „computer utilities which, like present electric
and telephone
utilities, will service individual homes and offices across
the country.” This vision of computing utilities based on
a service
provisioning model anticipated the massive
transformation of the entire computing industry in the
21st century
whereby computing services will be readily available on
demand, like other utility services available in today’s
society.
Similarly, users (consumers) need to pay providers only
when they access the computing services. In addition,
consumers
no longer need to invest heavily or encounter difficulties
in building and maintaining complex IT infrastructure.
In such a model, users access services based on their
requirements without regard to where the services are
hosted. This
model has been referred to as utility computing, or
recently as Cloud computing [5]. The latter term denotes
the
infrastructure as a “Cloud” from which businesses and
users can access applications as services from anywhere
in the world
on demand. Hence, Cloud computing can be classified
as a new paradigm for the dynamic provisioning of
computing
services supported by state-of-the-art data centers that
usually employ Virtual Machine (VM) technologies for
consolidation
and environment isolation purposes [11]. Many
computing service providers including Google,
Microsoft, Yahoo, and IBM
are rapidly deploying data centers in various locations
around the world to deliver Cloud computing services.
The potential
of this trend can be noted from the statement:
The Data Center Is The Computer,” by Professor David
Patterson of the University of California, Berkeley, an
ACM Fellow, and former President of the ACM –
CACM [2].
Cloud computing delivers infrastructure, platform, and
software (applications) as services, which are made
available to
consumers as subscription-based services under the pay-
as-you-go model. In industry these services are referred
to as
Infrastructure as a Service (IaaS), Platform as a Service
(PaaS), and Software as a Service (SaaS) respectively. A
recent
Berkeley report [23] stated “Cloud Computing, the long-
held dream of computing as a utility, has the potential to
transform
a large part of the IT industry, making software even
more attractive as a service”.
Clouds aim to drive the design of the next generation
data centers by architecting them as networks of virtual
services
(hardware, database, user-interface, application logic) so
that users can access and deploy applications from
anywhere in the
world on demand at competitive costs depending on
their QoS (Quality of Service) requirements [3].
Developers with
innovative ideas for new Internet services no longer
require large capital outlays in hardware to deploy their
service or
human expense to operate it [23]. Cloud computing
offers significant benefits to IT companies by freeing
them from the
low-level task of setting up basic hardware and software
infrastructures and thus enabling focus on innovation
and creating
business value for their services.
The business potential of Cloud computing is
recognised by several market research firms. According
to Gartner, Cloud
market opportunities in 2013 will be worth $150 billion.
Furthermore, many applications making use of utility-
oriented
computing systems such as Clouds emerge simply as
catalysts or market makers that bring buyers and sellers
together. This
creates several trillion dollars worth of business
opportunities to the utility/pervasive computing industry
as noted by Sun cofounder
Bill Joy [24]. He said “It would take time until these
markets mature to generate this kind of value. Predicting
nowwhich companies will capture the value is impossible.
Many of them have not even been created yet.”
Cloud Infrastructure: Challenges and
Requirements
Modern data centers, operating under the Cloud
computing model are hosting a variety of applications
ranging from those
that run for a few seconds (e.g. serving requests of web
applications such as e-commerce and social networks
portals with
transient workloads) to those that run for longer periods
of time (e.g. simulations or large data set processing) on
shared
hardware platforms. The need to manage multiple
applications in a data center creates the challenge of on-
demand resource
provisioning and allocation in response to time-varying
workloads. Normally, data center resources are statically
allocated to
applications, based on peak load characteristics, in order
to maintain isolation and provide performance
guarantees. Until
recently, high performance has been the sole concern in
data center deployments and this demand has been
fulfilled without
paying much attention to energy consumption. The
average data center consumes as much energy as 25,000
households [20].
As energy costs are increasing while availability
dwindles, there is a need to shift focus from optimising
data center resource
management for pure performance to optimising for
energy efficiency while maintaining high service level
performance.
“The total estimated energy bill for data centers in 2010
is $11.5 billion and energy costs in a typical data center
double every five years”, according to McKinsey report
[19].
Data centers are not only expensive to maintain, but also
unfriendly to the environment. Data centers now drive
more in
carbon emissions than both Argentina and the
Netherlands [20]. High energy costs and huge carbon
footprints are incurred
due to massive amounts of electricity needed to power
and cool numerous servers hosted in these data centers.
Cloud service
providers need to adopt measures to ensure that their
profit margin is not dramatically reduced due to high
energy costs. For
instance, Google, Microsoft, and Yahoo are building
large data centers in barren desert land surrounding the
Columbia

River, USA to exploit cheap and reliable hydroelectric
power [4]. There is also increasing pressure from
Governments
worldwide to reduce carbon footprints, which have a
significant impact on climate change. For example, the
Japanese
government has established the Japan Data Center
Council to address the soaring energy consumption of
data centers [6].
Leading computing service providers have also recently
formed a global consortium known as The Green Grid
[7] to
promote energy efficiency for data centers and minimise
their environmental impact.
Lowering the energy usage of data centers is a
challenging and complex issue because computing
applications and data
are growing so quickly that increasingly larger servers
and disks are needed to process them fast enough within
the required
time period. Green Cloud computing is envisioned to
achieve not only efficient processing and utilisation of
computing
infrastructure, but also minimise energy consumption.
This is essential for ensuring that the future growth of
Cloud
computing is sustainable. Otherwise, Cloud computing
with increasingly pervasive front-end client devices
interacting with
back-end data centers will cause an enormous escalation
of energy usage. To address this problem, data center
resources
need to be managed in an energy-efficient manner to
drive Green Cloud computing.

Green Cloud Architectural Elements
The aim of this paper is to addresses the problem of
enabling energy-efficient resource allocation, hence
leading to Green
Cloud computing data centers, to satisfy competing
applications’ demand for computing services and save
energy. Figure 1
shows the high-level architecture for supporting energy-
efficient service allocation in Green Cloud computing
infrastructure.
There are basically four main entities involved:
a) Consumers/Brokers: Cloud consumers or their
brokers submit service requests from anywhere in the
world to the Cloud.
It is important to notice that there can be a difference
between Cloud consumers and users of deployed
services.