Ex Parte Aschoff et al

Patent Trial and Appeal Board

Sep 24, 2012

10929081 (P.T.A.B. Sep. 24, 2012)

UNITED STATES PATENT AND TRADEMARK OFFICE
____________

BEFORE THE PATENT TRIAL AND APPEAL BOARD
____________

Ex parte JOHN G. ASCHOFF, DAVID D. CHAMBLISS,
and BRUCE MCNUTT
____________

Appeal 2010-004886
Application 10/929,081
Technology Center 2400
____________

Before BRUCE R. WINSOR, JOHN A. EVANS, and
JEREMY J. CURCURI, Administrative Patent Judges.

WINSOR, Administrative Patent Judge.

DECISION ON APPEAL
Appellants appeal under 35 U.S.C. § 134(a) from a Final Rejection of
claims 1-14 and 16-30, which constitute all the claims pending in this
application. Claim 15 is cancelled. We have jurisdiction under 35 U.S.C.
§ 6(b).
We reverse.

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STATEMENT OF THE CASE
Appellants’ invention relates to optimizing the revenue realized by the
operator of a data storage service under multiple service level agreements.
(Spec. 1:4-5). Claim 1, which is illustrative of the invention, reads as
follows:
1. A method to optimize revenue realized under
multiple service level agreements, comprising the steps of:
providing an information storage and retrieval system,
comprising one or more data storage devices;
entering into (N) service level agreements with one
storage services customer by a storage services provider to
provide data storage services for (N) applications using said
information storage and retrieval system, wherein each of said
(N) service level agreements specifies a maximum response
time RTSLA comprising an elapsed time from receipt by the
storage services provider from a storage services customer of a
request to write data to a data storage device or read data from a
data storage device and completion of that request, and wherein
a (j)th SLA recites a RT(j)SLA, wherein (j) is greater than or
equal to 1 and less than or equal to (N), and wherein (N) is
greater than 1;
calculating for each value of (j), a monetary value per
unit throughput νj for the (j)th application;
calculating (N) optimum data flow rates to maximize the
revenues to the storage services provider;
determining for each value of (j) an optimum data flow
rate X(j)OPT;
initializing, for each value of (j), a maximum data flow
rate X(j)MAX that the (j)th application can utilize;
determining, for each value of (j), if X(j)OPT equals
X(j)MAX;
for each value of (j) wherein X(j)OPT does not equal
X(j)MAX, delaying execution of I/O requests from the (j)th
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application, such that the average response time for the (j)th
application equals RT(j)SLA.
Claims 1-14 and 16-30 stand rejected under 35 U.S.C. § 103(a) as
unpatentable over Karnik (US 2004/0064557 A1; Apr. 1, 2004) and Chiang
(US 2002/0103895 A1; Aug. 1, 2002). (Ans. 4-11).
Rather than repeat the arguments here, we refer to the Briefs and the
Answer for the respective positions of Appellants and the Examiner.

ISSUE
The dispositive issue raised by Appellants’ contentions1 is as follows:
Does Karnik teach or suggest “calculating for each value of (j), a monetary
value per unit throughput νj for the (j)th application[,] calculating (N)
optimum data flow rates to maximize the revenues to the storage services
provider[, and] determining for each value of (j) an optimum data flow rate
X(j)OPT” (hereinafter the disputed limitations), as recited in claim 1?

ANALYSIS
The Examiner finds that Karnik teaches the disputed limitations at
paragraphs [0006], [0040], and [0045]-[0069]. (Ans. 5). Appellants contend
“that neither Karnik et al., nor Chiang, singly or in combination, teach[es]
calculating (N) optimum data flow rates to maximize the revenues to the
storage services provider, as recited by Appellants' claim 1.” (App. Br. 21).
We agree with Appellants.

1 Appellants’ contentions raise additional issues. However, we are
persuaded of error with regard to the identified issue, which is dispositive of
the appeal. Accordingly, we do not reach the additional issues raised by
Appellants’ contentions.
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As an initial matter, we do not agree with Appellants’ contention
(App. Br. 16-17) that Karnik does not contemplate optimizing revenue under
multiple service agreements. Karnik states, for example, that “[d]ifferent
policies can be used [to distribute resources] depending on the aim of the
allocation, e.g. fair sharing of capacity, maximizing revenue generated,
ensuring high resource utilization, minimizing perturbation of the current
allocation etc.” (Karnik, ¶ [0037] (emphasis added); see also ¶¶ [0008],
[0045]; claims 10, 20, 41). However, the resource allocation policy to
maximize revenue generated that is taught by the cited passages of Karnik is
as follows: “When the system is lightly loaded, the service provider may
choose to allow a customer to exceed its guaranteed throughput, since this
results in additional revenue.” (Karnik, ¶ [0045]).
Karnik teaches that “[t]he objective of the algorithm [described in
paragraphs [0045]-[0069] relied on by the Examiner] is to enforce fair
sharing of the available capacity amongst the active customers.” (Id.). The
Examiner explains:
Karnik in at least [0052] discloses that a various types of
throughput are computed in determining the capacity of the
system and the various data capacities of the customers. Both
terms “desired” and “optimum” are in relation to the flow of
data. Of the throughputs in this case disclosed in [0046-0065]
of Karnik, at least “desired throughput” is equivalent to the
Applicant’s “optimum flow rate”.
(Ans. 14 (brackets in original)). While the Examiner’s position that “desired
throughput” and “optimum data flow” rates are equivalent terms is not
unreasonable, the Examiner’s explanation does not establish that Karnik
teaches or suggests that the “desired throughput” is a throughput that
“maximize[s] the revenues to the storage services provider” (emphasis
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added), as recited in claim 1 (see Reply Br. 4), as opposed to achieving some
other policy objective, such as enforcing fair sharing of available capacity
(see Karnik, ¶ [0045]-[0046]). The Examiner does not persuasively identify
any passage in Chiang that cures the deficiency in Karnik’s disclosure.
On the record before us, we find that the Examiner has not established
that Karnik, alone or in combination with Chiang, teaches the disputed
limitations. Accordingly, we will not sustain the rejection of (1) claim 1; (2)
independent claims 14, 16, 23, 24, and 30, which recite limitations that are
substantially similar to the disputed limitations; and (3) claims 2-13, 17-22,
and 25-29, which depend from claims 1, 16, and 24 respectively.

ORDER
The decision of the Examiner to reject claims 1-14 and 16-30 as
unpatentable over Karnik and Chiang is reversed.2

REVERSED

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2 In the event of further prosecution of claims 24-30, or claims in similar
form, we leave to the Examiner to ascertain whether such claims are directed
to statutory subject matter under 35 U.S.C. § 101. See In re Nuijten, 500
F.3d 1346, 1357 (Fed. Cir. 2007); David J. Kappos, Subject Matter
Eligibility of Computer Readable Media, 1351 OFF. GAZ. PAT. OFFICE 212
(Feb. 23, 2010).