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than that of leasing from the storage cloud vendor. We
therefore assume the proportional difference in the operator’s
level of effort required to manage the system/data
(H T = $70,000 per year) is = 0.5. We assume that
the firm must purchase an enterprise-class RAID disk
controller (C = $2,000), specified to consume 0.7 kW
of power. Also, as storage is needed, the enterprise will
purchase 1-Tbyte disk drives ( = 1,000), with a present
cost of $300 per drive (K = $0.30), each specified
to consume 0.01 kW of power. Finally, we assume the
electric utility cost is $0.04 per kWh, and the end-of-life
disk salvage depreciation factor is 0.1.
Figure 1 shows the calculated NPV values for a storage
life expectancy of 0 to 10 years. In all the operational lifetimes
examined, the model shows that leasing is always
preferable to purchasing storage. In this case, the clear
recommendation to the medium-size enterprise is to lease
storage from the storage cloud vendor.
Large-size enterprises
Next, we look at the benefits of purchasing versus leasing
storage for a large-size enterprise—for example, a
data center with thousands of servers. In this scenario, we
assume the large enterprise’s storage requirement grows
at 10 Tbytes per year.
In this case, the human operator burden in owning and
operating a storage cluster is even larger than that of leasing
from the storage cloud vendor. We therefore assume
the proportional difference in the operator’s level of effort
required to manage the system/data (H T = $70,000/year)
is = 1.0. We also assume that the firm must purchase an
enterprise-class RAID disk controller (C = $2,000), specified
to consume 0.7 kW of power. Furthermore, we assume
the controller has a peak capacity of 100 Tbytes, and the
firm will purchase additional controllers as the storage
need arises.
For the actual storage, the enterprise will purchase
1-Tbyte disk drives ( = 1,000), with a present cost of
$300 per drive (K = $0.30), each specified to consume 0.01
kW of power. Finally, as before, we assume the electric utility
cost is $0.04 per kWh, and the end-of-life disk salvage
depreciation factor is 0.1.
Figure 2 shows the calculatedNPVs for a storage life
expectancy of 0 to 10 years. As the graph shows, leasing
storage is advantageous up to a nine-year storage life
expectancy. After that, it becomes more advantageous for
the enterprise to purchase and maintain a storage cluster.
Thus, the final decision to buy or lease storage will depend
on the expected use of the storage and data. For example,
if the storage is destined for use by a server cluster with
a five-year life expectancy, the enterprise should lease
storage. However, if the storage is destined for a long-term
archival system with an indefinite life expectancy, the
enterprise should purchase storage instead.
LATENCY IS NOT ZERO
A common flawed assumption in designing distributed
systems is the notion that latency is zero. In fact, latency isn’t
zero for cloud services. Accessing storage from across the
commodity Internet can incur a substantial cost in terms
of I/O latency. Our model doesn’t account for this latency.
However, future extensions can incorporate this factor by
estimating the profit parameter, P T , which we assumed to
be equal when deriving our current model. We can use this
profit parameter to reward services with faster response
times. For example, an enterprise might naïvely consider a
service that’s two times faster to be more productive, and
hence two times more profitable. For the moment, we leave
this substantive extension to a future time.
Our primary purpose in this article is to stimulate
discussion, debate, and future work in the quantitative
modeling of the cloud computing industry.
To this end, we propose a model to assist consumers,
researchers, and policy makers in estimating the
benefit of leasing from storage clouds.
Ultimately, an organization’s buy-or-lease decision will
depend on their anticipated parameters in the analysis.
Our model simply provides a first stepping-stone for rational
decision making to prevail in the cloud computing
market.
Acknowledgments
This article is based on work supported in part by US National
Science Foundation grant 0721931.
References
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________________________________
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3. N. Leavitt, “Is Cloud Computing Really Ready for
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4. A. Henry, “Keynote Address: Cloud Storage FUD
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____________
videos/henry.mov.
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6. G.B. Harwood and R.H. Hermanson, “Lease-or-Buy
Decisions,” J. Accountancy, vol. 142, no. 3, 1976, pp.
83-87.
APRIL 2010
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