DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 01/21/2026 has been entered.
This Action is in response to communications filed 01/21/2026.
Claims 1-2 and 8-16 have been amended.
Claims 1-20 are pending.
Claims 1-20 are rejected.
Response to Arguments
In Remarks filed on 01/21/2026, Applicant substantially argues:
On Pages 8-9, the applied references including O’Brien, Jeon, and Gopal, fail to disclose the amended limitation of claim 1, and similarly amended claims 8 and 15, regarding the use of changing the ratio of compressed data to uncompressed data which to change wear rate by changing write amplification. Specifically, Applicant points to Jeon and Gopal as failing to disclose relationship of controlling wear rate through controlling write amplification via adjusting activity-based threshold for changing a data compression ratio. Applicant’s arguments filed have been fully considered but they are moot in view of the current rejections made in response to Applicant’s amendments.
The applied references fail to disclose the respective dependent claims 2-7, 9-14, and 16-20 by virtue of dependency on claims 1, 8, and 15 for the reasons identified above. Applicant’s arguments filed have been fully considered but they are moot in view of the current rejections made in response to Applicant’s amendments.
All arguments by the applicant are believed to be covered in the body of the office action; thus, this action constitutes a complete response to the issues raised in the remarks dated January 21, 2026.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102 of this title, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103(a) are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-3, 8-10, and 15-17 are rejected under 35 U.S.C. 103 as being unpatentable over O’Brien et al. (US 2010/0250831) in view of Jeon et al. (US 2021/0263682) and further in view of Yoshida et al. (US 2019/0018788).
Regarding claim 1, O’Brien discloses, in the italicized portions, a method comprising: iteratively monitoring wear rate of solid-state drives (SSDs) of a drive array ([0062] and [0067] Each of the respective data collectors 28n collect, in a known fashion, resource utilization information associated with the activities of the server 12n on which they are deployed. The data collector 28a may collect, for example, data storage wear rate, skew of the work load distribution, write activity, remaining lifetime, etc. This resource utilization information may be forwarded to (or requested by) one of the policy engines 30n.) for which an activity based compression (ABC) threshold is used to determine whether extents are accessed frequently enough to be stored as uncompressed data to reduce data compression and decompression overhead or not accessed frequently enough to be stored as uncompressed data and therefore are stored as compressed data to reduce storage capacity requirements, the ABC threshold defining a ratio of compressed data to uncompressed data stored on the SSDs; and converging wear rate of the SSDs with a target wear rate by dynamically adjusting the ABC threshold to change the ratio of compressed data to uncompressed data stored on the SSDs to change write amplification to change wear rate of the SSDs ([0063] In certain embodiments disclosed herein, the global management system may gather usage information such as data storage wear rate, skew of the work load distribution (the degree to which the load distribution is balanced-the lower the skew, the more uniform the load balancing, the higher the skew, the less uniform the load balancing, etc.), write activity, and remaining lifetime from the independent file systems within the data storage system. It may then use this information to determine when to move data from one file system to another and what data to move. It may also use this information to dynamically adjust a configuration of the data storage system to control the data storage wear rate and skew of the work load distribution. [0069] The policy engine 30a may specify several wear rate and workload distribution policies as discussed above… These example policies (or policies, for example, directed to the storage units, etc.) may allow the global management system 21a to sacrifice wear rate to improve the uniformity of the work load distribution, or sacrifice uniformity of the work load distribution to improve wear rate…), where increasing the ratio of compressed data to uncompressed data reduces wear rate by reducing write amplification. The Examiner notes not all portions cited are reproduced herein for sake of brevity. Herein O’Brien discloses managing a policy-driven data storage configuration to modify the storage system wear rate from a monitored rate to a policy identified wear rate based on system usage information. Herein the policy to reconfigure the storage to alter the wear rate is determined analogous to “converging” the wear rate to a target wear rate as claimed. O’Brien does not explicitly identify that to adjust the wear rate, including reducing the wear rate by write amplification via increasing the ratio of compressed to uncompressed data, the ratio of compressed data to uncompressed data stored on the SSDs is dynamically adjusted as controlled by an activity based compression (ABC) threshold. Regarding these aspects of the limitation, Jeon discloses in Paragraphs [0036], [0039], and [0041] explicitly that the storage device controller dynamically resizes the compressed and uncompressed portions of the storage device in order to address data I/O latency and efficiency as well as reducing write amplification. Specifically, Jeon identifies divided zones of the storage device may be configured and dynamically managed to control the compression ratio of the zones, which is the ratio of compressed data versus uncompressed data, to adjust the I/O latency and compression efficiency. Jeon explicitly notes that the write amplification of the storage device can be reduced by decreasing the frequency of garbage collection which improves the efficiency of the device. In this manner, it would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention that the write amplification as addressed by Jeon includes wear rate leveling as discussed in O’Brien, O’Brien may be modified to include the uncompressed and compressed data region resizing as part of the present resource configuration changing to address the activity of the storage device and respond to current storage performance and/or conditions (Jeon [0036]). This is further clarified and supported by Yoshida wherein Paragraph [0044] discusses the relationship between memory consumption, write amplification, and lifespan, or wear rate, of the SSD. In particular, it is explicitly noted that increased memory consumption causes an increase in write amplification which thereby further reduces the lifespan of the device. In this manner, it would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention that the demonstrated relationship between data compression, write amplification, and wear rate is known in the field of endeavor and therefore the cited references herein in combination render obvious the dynamic resource configuration to address memory usage and performance. O’Brien, Jeon and Yoshida are analogous art because they are from the same field of endeavor of managing storage allocation configuration.
Regarding claim 2, O’Brien, Jeon, and Yoshida in combination further disclose, in the italicized portions, the method of claim 1 further comprising dynamically updating the ABC threshold to converge the wear rate of the SSDs with the target wear rate based on whether current aggregate wear rate of the SSDs is greater than, less than, or equal to an aggregate target wear rate (O’Brien [0069] and [0070] In some embodiments, policy engine 30a may track historical trends in the data collected by the data collectors 28n and initiate a configuration change when justified by the magnitude of improvement in the data storage system 10 operation that the policy engine 30a anticipates will result from the configuration change. The policy engine 30a may balance the conflicting goals of, on the one hand, achieving a desired wear rate or workload distribution and, on the other hand, minimizing the impact to the data storage system 10 operations due to carrying out a configuration change. And Jeon [0036]). As identified previously, Jeon discloses resizing uncompressed and compressed data storage regions dynamically based on storage device performance and/or conditions. In view of O’Brien and Jeon wherein O’Brien specifically identifies performing configuration changes to address the workload distribution to affect the wear rate and Jeon explicitly identifies that respective zones may be allocated to particular tiers of data including hot or cold, it would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include, as part of the configuration modifications performed by O’Brien, the uncompressed and compressed region allocations to reach predetermined settings.
Regarding claim 3, O’Brien further discloses the method of claim 2 further comprising balancing wear across the SSDs ([0062-65]). Herein O’Brien discloses wear leveling or load balancing across the storage system.
Regarding claim 8, O’Brien discloses, in the italicized portions, an apparatus comprising: a storage system comprising at least one compute node configured to manage access to solid-state drives (SSDs), the compute node comprising hardware resources including multi-core processors, memory, and data compression controller adapted to ([0099] Computing device 700 including processors, storage, and controller): iteratively monitor wear rate of solid-state drives (SSDs) of a drive array ([0062] and [0067]) for which an activity based compression (ABC) threshold is used to determine whether extents are accessed frequently enough to be stored as uncompressed data to reduce data compression and decompression overhead or not accessed frequently enough to be stored as uncompressed data and therefore are stored as compressed data to reduce storage capacity requirements, the ABC threshold defining a ratio of compressed data to uncompressed data stored on the SSDs; and converging wear rate of the SSDs with a target wear rate by dynamically adjusting the ABC threshold to change the ratio of compressed data to uncompressed data stored on the SSDs to change write amplification to change wear rate of the SSDs ([0069]), where increasing the ratio of compressed data to uncompressed data reduces wear rate by reducing write amplification. Herein O’Brien discloses managing a policy driven data storage configuration to modify the storage system wear rate from a monitored rate to a policy identified wear rate. Herein the policy to reconfigure the storage to alter the wear rate is determined analogous to “converging” the wear rate to a target wear rate as claimed. O’Brien does not explicitly identify that to adjust the wear rate, including reducing the wear rate by write amplification via increasing the ratio of compressed to uncompressed data, the ratio of compressed data to uncompressed data stored on the SSDs is dynamically adjusted as controlled by an activity based compression (ABC) threshold. Regarding these aspects of the limitation, Jeon discloses in Paragraphs [0036], [0039], and [0041] explicitly that the storage device controller dynamically resizes the compressed and uncompressed portions of the storage device in order to address data I/O latency and efficiency as well as reducing write amplification. This is further clarified and supported by Yoshida wherein Paragraph [0044] discusses the relationship between memory consumption, write amplification, and lifespan, or wear rate, of the SSD. In particular, it is explicitly noted that increased memory consumption causes an increase in write amplification which thereby further reduces the lifespan of the device. Claim 8 is rejected on a similar basis as claim 1.
Regarding claim 9, O’Brien, Jeon, and Yoshida in combination further disclose, in the italicized portions, the apparatus of claim 8 further comprising the data compression controller adapted to dynamically update the ABC threshold to converge the wear rate of the SSDs with the target wear rate based on whether current aggregate wear rate of the SSDs is greater than, less than, or equal to an aggregate target wear rate (O’Brien [0069-70] and Jeon [0036]). As identified previously, Jeon discloses resizing by a controller the uncompressed and compressed data storage regions dynamically and O’Brien discloses changing configurations to achieve policy goals. Claim 9 is rejected on a similar basis as claim 2.
Regarding claim 10, O’Brien further discloses the apparatus of claim 9 further comprising the data compression controller adapted to balance wear across the SSDs ([0062-65]). Herein O’Brien discloses wear leveling or load balancing across the storage system.
Regarding claim 15, O’Brien discloses, in the italicized portions, a non-transitory computer-readable storage medium storing instructions that when executed by a computer perform a method comprising ([0099] and [0102-103] readable media storing executable instructions): iteratively monitoring wear rate of solid-state drives (SSDs) of a drive array ([0062] and [0067]); for which an activity based compression (ABC) threshold is used to determine whether extents are accessed frequently enough to be stored as uncompressed data to reduce data compression and decompression overhead or not accessed frequently enough to be stored as uncompressed data and therefore are stored as compressed data to reduce storage capacity requirements, the ABC threshold defining a ratio of compressed data to uncompressed data stored on the SSDs; and converging wear rate of the SSDs with a target wear rate by dynamically adjusting the ABC threshold to change the ratio of compressed data to uncompressed data stored on the SSDs to change write amplification to change wear rate of the SSDs ([0069]), where increasing the ratio of compressed data to uncompressed data reduces wear rate by reducing write amplification. Herein O’Brien discloses managing a policy driven data storage configuration to modify the storage system wear rate from a monitored rate to a policy identified wear rate. Herein the policy to reconfigure the storage to alter the wear rate is determined analogous to “converging” the wear rate to a target wear rate as claimed. O’Brien does not explicitly identify that to adjust the wear rate, including reducing the wear rate by write amplification via increasing the ratio of compressed to uncompressed data, the ratio of compressed data to uncompressed data stored on the SSDs is dynamically adjusted as controlled by an activity based compression (ABC) threshold. Regarding these aspects of the limitation, Jeon discloses in Paragraphs [0036], [0039], and [0041] explicitly that the storage device controller dynamically resizes the compressed and uncompressed portions of the storage device in order to address data I/O latency and efficiency as well as reducing write amplification. This is further clarified and supported by Yoshida wherein Paragraph [0044] discusses the relationship between memory consumption, write amplification, and lifespan, or wear rate, of the SSD. In particular, it is explicitly noted that increased memory consumption causes an increase in write amplification which thereby further reduces the lifespan of the device. Claim 15 is rejected on a similar basis as claim 1.
Regarding claim 16, O’Brien and Jeon in combination further disclose, in the italicized portions, the non-transitory computer-readable storage medium of claim 15 in which the method further comprises dynamically updating the ABC threshold to converge the wear rate of the SSDs with the target wear rate based on whether current aggregate wear rate of the SSDs is greater than, less than, or equal to an aggregate target wear rate (O’Brien [0069-70] and Jeon [0036]). As identified previously, Jeon discloses resizing by a controller the uncompressed and compressed data storage regions dynamically and O’Brien discloses changing configurations to achieve policy goals. Claim 16 is rejected on a similar basis as claim 2.
Regarding claim 17, O’Brien further discloses the non-transitory computer-readable storage medium of claim 16 in which the method further comprises balancing wear across the SSDs ([0062-65]). Herein O’Brien discloses wear leveling or load balancing across the storage system.
Claims 4-7, 11-14, and 18-20 are rejected under 35 U.S.C. 103 as being unpatentable over O’Brien in view of Jeon and further in view of Yoshida and still in further view of Alshawabkeh et al. (US 9,703,664).
Regarding claim 4, O’Brien, Jeon, and Yoshida do not explicitly disclose the method of claim 3 further comprising using a time series model of extent activity to determine an updated ABC threshold to converge the wear rate of the SSDs with the target wear rate. Regarding this limitation, Alshawabkeh discloses in Column 82, line 60 – Column 83, line 15 using a time series model to predict a future workload and determine data movements. As O’Brien, Jeon and Yoshida involve reconfiguring data storage systems based on monitored metrics, it would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to use a time series model to forecast a future workload condition in order to inform how the reconfiguration of the storage should be modified to change the wear rate to a target wear rate. O’Brien, Jeon, Yoshida and Alshawabkeh are analogous art because they are from the same field of endeavor of managing storage allocation configuration.
Regarding claim 5, O’Brien, Jeon, Yoshida, and Alshawabkeh in combination further disclose the method of claim 4 further comprising decreasing the ABC threshold by a first amount indicated by the time series model in response to determining that monitored wear rate is greater than the target wear rate (Alshawabkeh [Col. 82, ln. 60- Col. 83 ln. 15] and O’Brien [0063] and Jeon [0036]). Herein O’Brien identifies making configuration changes to achieve policy goals, under broadest reasonable interpretation as analogous to decreasing the ABC threshold, the wear rate may be reduced based on access activity.
Regarding claim 6, O’Brien, Jeon, Yoshida, and Alshawabkeh in combination further disclose the method of claim 5 further comprising increasing the ABC threshold by a second amount indicated by the time series model in response to determining that monitored wear rate is less than the target wear rate (Alshawabkeh [Col. 82, ln. 60- Col. 83 ln. 15] and O’Brien [0063] and Jeon [0036]). On a similar basis as the rejection of claim 5, the area allocated for uncompressed data may be increased when the wear rate is below the target wear rate in order to increase access activity.
Regarding claim 7, O’Brien, Jeon, Yoshida, and Alshawabkeh in combination further disclose the method of claim 6 further comprising not updating the ABC threshold in response to determining that monitored wear rate is equal to the target wear rate (Alshawabkeh [Col. 82, ln. 60- Col. 83 ln. 15] and O’Brien [0063] and Jeon [0036]). As the references of record involve wear-leveling and workload distribution, it would be obvious to one of ordinary skill in the art that no modifications to the storage configuration may be made when the configuration is determined to meet policy goals including the wear rate is equal to the target wear rate.
Regarding claim 11, O’Brien, Jeon, and Yoshida do not explicitly disclose the apparatus of claim 10 further comprising the data compression controller adapted to use a time series model of extent activity to determine an updated ABC threshold to converge the wear rate of the SSDs with the target wear rate. Regarding this limitation, Alshawabkeh discloses in Column 82, line 60 – Column 83, line 15 using a time series model to predict a future workload and determine data movements. Claim 11 is rejected on a similar basis as claim 4.
Regarding claim 12, O’Brien, Jeon, Yoshida, and Alshawabkeh in combination further disclose the apparatus of claim 11 further comprising the data compression controller adapted to decrease the ABC threshold by a first amount indicated by the time series model in response to determining that monitored wear rate is greater than the target wear rate (Alshawabkeh [Col. 82, ln. 60- Col. 83 ln. 15] and O’Brien [0063] and Jeon [0036]). Claim 12 is rejected on a similar basis as claim 5.
Regarding claim 13, O’Brien, Jeon, Yoshida, and Alshawabkeh in combination further disclose the apparatus of claim 12 further comprising the data compression controller adapted to increase the ABC threshold by a second amount indicated by the time series model in response to determining that monitored wear rate is less than the target wear rate (Alshawabkeh [Col. 82, ln. 60- Col. 83 ln. 15] and O’Brien [0063] and Jeon [0036]). Claim 13 is rejected on a similar basis as claim 6.
Regarding claim 14, O’Brien, Jeon, Yoshida, and Alshawabkeh in combination further disclose the apparatus of claim 13 further comprising the data compression controller adapted to not update the ABC threshold in response to determining that monitored wear rate is equal to the target wear rate (Alshawabkeh [Col. 82, ln. 60- Col. 83 ln. 15] and O’Brien [0063] and Jeon [0036]). Claim 14 is rejected on a similar basis as claim 7.
Regarding claim 18, O’Brien, Jeon, and Yoshida do not explicitly disclose the non-transitory computer-readable storage medium of claim 17 in which the method further comprises using a time series model of extent activity to determine an updated ABC threshold to converge the wear rate of the SSDs with the target wear rate. Regarding this limitation, Alshawabkeh discloses in Column 82, line 60 – Column 83, line 15 using a time series model to predict a future workload and determine data movements. Claim 18 is rejected on a similar basis as claim 4.
Regarding claim 19, O’Brien, Jeon, Yoshida, and Alshawabkeh in combination further disclose the non-transitory computer-readable storage medium of claim 18 in which the method further comprises decreasing the ABC threshold by a first amount indicated by the time series model in response to determining that monitored wear rate is greater than the target wear rate (Alshawabkeh [Col. 82, ln. 60- Col. 83 ln. 15] and O’Brien [0063] and Jeon [0036]). Claim 19 is rejected on a similar basis as claim 5.
Regarding claim 20, O’Brien, Jeon, Yoshida, and Alshawabkeh in combination further disclose the non-transitory computer-readable storage medium of claim 19 in which the method further comprises increasing the ABC threshold by a second amount indicated by the time series model in response to determining that monitored wear rate is less than the target wear rate (Alshawabkeh [Col. 82, ln. 60- Col. 83 ln. 15] and O’Brien [0063] and Jeon [0036]). Claim 120 is rejected on a similar basis as claim 6.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Owa et al. (US 10,310,747) – Column 2 Detailed Description wherein determining storage compression form based on access frequency and importance level is discussed.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ALEXANDER J YOON whose telephone number is (408)918-7629. The examiner can normally be reached on Monday-Friday 8am-3pm ET. The examiner’s email is alexander.yoon2@uspto.gov.
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/ALEXANDER YOON/
Examiner, Art Unit 2135
/JARED I RUTZ/Supervisory Patent Examiner, Art Unit 2135