09-10-2012, 10:38 AM
Green Cloud Computing: Balancing Energy in Processing, Storage, and Transport
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ABSTRACT
Network-based cloud computing is rapidly
expanding as an alternative to conventional office-based
computing. As cloud computing becomes more widespread,
the energy consumption of the network and computing
resources that underpin the cloud will grow. This is happening
at a time when there is increasing attention being paid to the
need to manage energy consumption across the entire
information and communications technology (ICT) sector.
While data center energy use has received much attention
recently, there has been less attention paid to the energy
consumption of the transmission and switching networks that
are key to connecting users to the cloud. In this paper, we
present an analysis of energy consumption in cloud computing.
The analysis considers both public and private clouds, and
includes energy consumption in switching and transmission as
well as data processing and data storage. We show that energy
consumption in transport and switching can be a significant
percentage of total energy consumption in cloud computing.
Cloud computing can enable more energy-efficient use of
computing power, especially when the computing tasks are of
low intensity or infrequent. However, under some circumstances
cloud computing can consume more energy than
conventional computing where each user performs all computing
on their own personal computer (PC).
INTRODUCTION
The increasing availability of high-speed Internet and
corporate IP connections is enabling the delivery of new
network-based services [1]. While Internet-based mail
services have been operating for many years, service
offerings have recently expanded to include network-based
storage and network-based computing. These new services
are being offered both to corporate and individual end
users [2], [3]. Services of this type have been generically
called Bcloud computing[ services [2]–[7].
The cloud computing service model involves the
provision, by a service provider, of large pools of highperformance
computing resources and high-capacity storage
devices that are shared among end users as required
[8]–[10]. There are many cloud service models, but
generally, end users subscribing to the service have their
data hosted by the service, and have computing resources
allocated on demand from the pool. The service provider’s
offering may also extend to the software applications required
by the end user. To be successful, the cloud service
model also requires a high-speed network to provide connection
between the end user and the service provider’s
infrastructure.
Storage as a Service
Through storage as a service, users can outsource their
data storage requirements to the cloud [3]–[6]. All processing
is performed on the user’s PC, which may have
only a solid state drive (e.g., flash-based solid-state storage),
and the user’s primary data storage is in the cloud.
Data files may include documents, photographs, or videos.
Files stored in the cloud can be accessed from any computer
with an Internet connection at any time [5]. However,
to make a modification to a file, it must first be
downloaded, edited using the user’s PC and then the
modified file uploaded back to the cloud. The cloud service
provider ensures there is sufficient free space in the cloud
and also manages the backup of data [5]. In addition, after
a user uploads a file to the cloud, the user can grant read
and/or modification privileges to other users. One example
of storage as a service is the Amazon Simple Storage
service [13].
Summary of Models
Table 1 provides a summary of the location of processing,
location of storage, and function of transport for
each of these cloud services. In a storage service, the
majority of processing occurs at the user’s PC (the client)
and the majority of storage is in the cloud. The transmission
and switching network transports the user’s files
between the data center and the user. With a processing
service, the user’s computer processes only short tasks and
the cloud processes large computationally intensive tasks.
Long-term storage of data is on the user’s computer and
transport is required to transfer the files relevant to each
large task. In a software service, processing and storage are
performed in the cloud. Transport is required for all tasks
to enable transmission of commands to the cloud and to
return the results.
MODELS OF ENERGY
CONSUMPTION
In this section, we describe the functionality and energy
consumption of the transport and computing equipment
on which current cloud computing services typically
operate. We consider energy consumption models of the
transport network, the data center, plus a range of
customer-owned terminals and computers. The models
described are based on power consumption measurements
and published specifications of representative equipment
[7], [21], [22], [30]. Those models include descriptions of
the common energy-saving techniques employed by cloud
computing service providers.
User Equipment
A user may use a range of devices to access a cloud
computing service, including a mobile phone (cell phone),
desktop computer, or a laptop computer. In this paper, we
focus on desktop computers and laptops. These computers
typically comprise a central processing unit (CPU), random
access memory (RAM), hard disk drive (HDD),
graphical processing unit (GPU), motherboard, and a
power supply unit. Peripheral devices including speakers,
printers, and visual display devices are often connected to
PCs. These peripheral devices do not influence the
comparison between conventional computing and cloud
computing and so are not included in the model. In our
analysis, we assume that when user equipment is not being
used it is either switched off or in a deep sleep state
(negligible power consumption).
ANALYSIS OF CLOUD SERVICES
In this section, we compare the per-user energy consumption
of each cloud service outlined in Section II using the
energy model described in Section III. The energy consumption
of each cloud service is also compared against
the energy consumption of conventional computing.
As described earlier, the key difference between public
cloud computing and private cloud computing is the transport
network connecting users to the data center. In the
following, ET is the per-bit energy consumption of transport
in cloud computing. If we are considering a private
cloud model, ET ¼ EC (transport through a corporate network),
and if we are considering a public cloud model,
ET ¼ EI (transport through the Internet).
THE FUTURE OF
CLOUD COMPUTING
The analysis in previous sections was based on state-ofthe-
art technology in 2010. In recent years, there have
been continuous improvements in the energy efficiency of
equipment as new generations of technology come on
line. This has led to exponential improvements over time
in the energy efficiency of servers [54], storage equipment
[55] as well as routers and switches [22], [56], [57]. It is
reasonable to expect that future generations of transport
and computing equipment will continue to achieve improvements
in terms of energy efficiency, largely due to
improvements in complementary metal–oxide–semiconductor
(CMOS) integrated circuit technology. In this
section, we utilize estimates of efficiency gains in technology
over time to forecast energy consumption of
cloud computing in the future. We also discuss future
directions for cloud computing and provide guidelines for
how cloud computing can be made as energy efficient as
possible.
CONCLUSION
In this paper, we presented a comprehensive energy consumption
analysis of cloud computing. The analysis considered
both public and private clouds and included energy
consumption in switching and transmission as well as data
processing and data storage. We have evaluated the energy
consumption associated with three cloud computing services,
namely storage as a service, software as a service,
and processing as a service. Any future service is likely to
include some combination of each of these service models.
Power consumption in transport represents a significant
proportion of total power consumption for cloud
storage services at medium and high usage rates. For typical
networks used to deliver cloud services today, public
cloud storage can consume of the order of three to four
times more power than private cloud storage due to the
increased energy consumption in transport.