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technology’s introduction in 2003. This data is significant
because SATA is the predominant drive technology used
in desktop and nearline systems.
Most organizations use financial models as only one data
point in deciding whether to buy or lease an asset. Other
factors also influence their decision. 7 However, our proposed
model bridges a critical gap in the literature and, more
importantly, the market. Our model helps users understand
the premium they’re paying for what seems to be an arbitrarily
priced online storage market. Our research agenda
aims to provide a quantitative framework for rationally reasoning
about the cost of leasing infrastructure from cloud
services, and extends our prior work on leasing from compute
clouds. 10 Importantly, the systematic understanding of
the real cost of leasing assets from cloud services lets users
make rational decisions with innovative pricing structures.
This promotes market transparency and ultimately supports
a competitive product market.
PRELIMINARIES
A key principle in economic finance is the time value
of money. Basically, this principle states that an investor
always prefers to receive some fixed amount of money
today rather than in the future. Hence, when making
buy-or-lease decisions, investors often compare future
cash flows in an investment over time, discounted to their
present value by some interest rate. 5-7 The discounting
interest rate used reflects the risk involved in raising the
capital needed to invest.
In equation form, the simplified standard capitalbudgeting
format for calculating a purchased asset’s net
present value (NPV) is as follows:
NPV P =
N
T = 0
P P C T T
(1+ I ) K T
S
+ E , N (1+ I ) K
where P is the annual profit resulting from the purchased
T
P asset in year T; C is the asset’s expected annual operat-
T
ing cost at year T; I is the firm’s cost of capital, defined
K
as the interest rate of its outstanding debt used to finance
the purchase; 11 N is the asset’s productive life in years; S is
the asset’s salvage value after N years; and E is the asset’s
purchase (capital) cost.
Similarly, the equation for calculating a leased asset’s
NPV is as follows:
NPV L =
L P C T T
( ) T
N
T = 0
1+ I K
LT ( ) T
N
T = 0
1+ I R
L where C is the leased asset’s expected annual operat-
T
ing cost at year T; L is the lease payment at year T; and
T
I is the interest rate for financing the lease payments. In
R
this formulation, the lease’s financing rate is generally
regarded as smaller than the cost of capital, I , because of
K
,
Table 1. Parameter terms in the buy-or-lease decision model.
Term Description
Cost of electric utility ($/kilowatt hour)
Size of purchased disk drives (Gbytes)
Proportional difierence between human efiort in main -
taining a purchased versus a leased storage infrastructure
ϒ Used disk depreciation factor on salvage ([0.0, 1.0])
C Disk controller unit cost ($)
H Annual human operator salary ($)
T
I Risk-free interest rate (percent)
F
Κ Current per-Gbyte storage price ($/Gbyte)
LT Pc PD VT Expected annual per-Gbyte lease payment ($/Gbyte/year)
Disk controller power consumption (kW)
Disk drive power consumption (kW)
Expected storage requirement in year T (Gbytes)
the involved payment structure’s predictability. 5
With this NPV formulation for asset purchase and lease,
investors can make the buy-or-lease decision using the
following criteria: If the incremental NPV (NPV) 0
buy; if NPV < 0 lease, where NPV = NPV P – NPV L .
DECISION MODEL
We derive a buy-or-lease decision model that calculates
the comparative NPVs from storage purchase versus
lease. Our model accounts for the expected capital expenditure
from SATA hard disk drive purchase, replacement,
and end-of-use salvage. It also accounts for the expected
operational expenditure for utility consumption and
human operator cost. The “Derivation of the Decision
Model” sidebar describes how we derived our decision
model. We summarize it as follows: If NPV 0 buy; if
NPV < 0 lease, where
C − E + L T T T
ΔNPV =
( 1+ I F ) T
N
S
∑
+ − C
N
T = 0
( 1+ I F )
S =γ ∗ Ω∗⎡⎢ V ⎤ ∗ K ∗e T ⎥Ω −0.438T
C =−ρ∗H − 365 ∗24
T T ( ⎡⎢ ⎤⎥Ω )
( )∗δ ∗ P + P ∗ V C D T
( ⎡⎢ ⎤ − ⎡⎢ V ⎤ ⎥Ω T −1 ⎥Ω )∗Ω∗K ∗e −0.438T
E T = 1.03∗ V T
Table 1 lists the model parameters. We assume ⎡V⎤ fl is
an operator returning the minimum number of fl-sized
disk drives needed to store V Gbytes of data. The derived
terms S, C T , and E T represent the expected end-of-life disk
salvage value, the operating cost in year T, and the capital
cost in year T, respectively.
EXAMPLE APPLICATION
We used our decision model to evaluate the advantages
of purchasing versus leasing storage from a hypothetical
storage cloud vendor.
.
APRIL 2010
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