DETAILED ACTION
This communication is responsive to the amendment filed on 06/19/2026.
Claims 1, 8, and 15 are independent claims and are amended.
Claims 1-20 are pending in this application.
This Action has been made FINAL.
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Continuity
This instant application is a continuation (CON.) of application no. 15/647,870 filed on 07/12/2017, which is Pat. No. 10,740,294, and has provisional no. 62/445,668 filed on 01/12/2017.
Claim Objections
Claims 1-7 and 15-20 are objected to because of the following informalities:
Regarding claim 1, the claim recites “the processing device configured to:…” in line 5 should be changed to “the processing device is configured to:…”. Appropriate correction is required.
Regarding claim 15, the claim recites “the processing device configured to:…” in line 2 should be changed to “the processing device is configured to:…”
Claims 2-7 and 16-20 are also objected because of dependency to claims 1 and 15, respectively.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 1 recites the limitation "the plurality of solid-state storage devices" in line 3. There is insufficient antecedent basis for this limitation in the claim.
Claim 8 recites the limitation "the plurality of solid-state storage devices" in lines 6-7. There is insufficient antecedent basis for this limitation in the claim.
Claim 15 recites the limitation "the plurality of solid-state storage devices" in lines 7-8. There is insufficient antecedent basis for this limitation in the claim.
Claims 2-7, 9-14, and 16-20 are also rejected because of dependency to claims 1, 8, and 15.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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, 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.
Claims 1-6, 8-13, 15-20 are rejected under 35 U.S.C. 103 as being unpatentable over Kimmel et al., US Patent No. 8,621,145 B1 (hereinafter as “Kimmel”) and in view of Ebsen et al., US Patent No. 10,739,996 B1 (hereinafter as “Ebsen”), and further in view of Singhai et al., US Pub. No. 2017/0123676 A1 (hereinafter as “Singhai”).
Regarding claim 1, Kimmel teaches: a system (see Figs. 2-3), comprising:
a plurality of storage devices (Fig. 3 is shown the plurality of storage devices at elements 34-35, 38; and col. 3, lines 38-42: discloses a solid-state secondary cache, and flash memory; and col. 5, lines 35-42); and
a storage controller external to the plurality of solid-state storage devices and operatively coupled to the plurality of storage devices (see Fig. 3, element 31: wherein the Storage Manager is interpreted as the storage controller; further Figs. 1-3 are shown solid-state storage devices; and col. 6, lines 28-33), the storage controller comprising a processing device (Fig. 2, element 21-Processor(s); and col. 6, lines 28-33: “a network storage server in which the techniques described above can be implemented (e.g., storage server 2 in FIG. 1). In the illustrated embodiment, the storage server 2 includes one or more processors 21 and memory 22 coupled to an interconnect 29.”), the processing device configured to:
receive, from two or more of the plurality of storage devices, a plurality of characteristics associated with valid data stored at a plurality of erase blocks across the plurality of storage devices of the plurality of storage devices (Figs. 1-3 are shown the plurality of storage devices; col. 5, lines 9-19: “classification and localization of cache lines with similar cache aging and invalidation behaviors within erase block boundaries, allowing efficient reuse of flash locations while improving effective cache capacity. After erase block fill using these methods, the slow-turn, fast-turn or no-turn designation for an erase block or stripe can be forgotten, using line-granular tracking of line use and invalidation to inform subsequent reuse of the erase block or stripe. Alternatively, the slow-turn, fast-turn or no-turn designation can be retained and inform subsequent replacement policy”, wherein the “aging” and/or “invalidation behaviors” are/is interpreted as the characteristic(s); and col. 10, lines 37-40: “receives data blocks from the EC layer 36 in the form of write units. As illustrated in FIG. 4, a write unit 49 is a group of several queued data blocks 50 of the same data class (e.g., slow-turn, fast-turn or no-turn)…”; and col. 12, line 37: wherein the “valid entries in the erase block/stripe is interpreted as valid data associated with the characteristic(s)).
Kimmel teaches classifying and locating the valid/invalid entries in the erase blocks/stripes in the groups of slow-turn, fast-turn or no-turn according the similar aging (col. 5, lines 9-19, col. 10 and col. 12). However, Kimmel does not explicitly teach “wherein the plurality of erase blocks are indicated as ready to be garbage collected;” and “perform, […], a garbage collection process […], wherein to perform the garbage collection process the processing device is configured to: group valid data from the plurality of erase blocks across the plurality of storage devices based on a similarity of the plurality of characteristics between the valid data stored at the plurality of erase blocks, and store the grouped valid data at erase blocks of the plurality of storage devices, the erase blocks for storage selected based on the characteristics associated with the valid data from the plurality of erase blocks and wear-related characteristic of the erase blocks.”
In the same field of endeavor (i.e., data processing), Ebsen teaches enhanced garbage collection technique including that: “wherein the plurality of erase blocks are indicated as ready to be garbage collected” (see col. 1, lines 27-33: valid data, and “The garbage collection operation may include selecting a plurality of blocks on which to perform the garbage collection operation,…” wherein the technique of “selecting” is interpreted as “are indicated”, and see further in Fig. 3 for indicating the erase blocks as ready to be garbage collected);
perform, by the storage controller (Fig. 2, element 206 – Controller), a garbage collection process for the plurality of storage devices (Fig. 2: shown the plurality of storage devices 203, 208, 209, and Fig. 4, element 408; and col. 2, lines 9-13: “perform garbage collection operation …”), wherein to perform the garbage collection process the processing device (col. 3, lines 14-25, e.g., “DSD 104 may include garbage collection module (GCM) 110... A module may include one or more physical components of a computing device (e.g., circuits, processors, etc.), may include instructions that, when executed, can cause a processor to perform a particular task or job, or any combination thereof. The GCM 110 may perform the methods and processes described herein to select data and blocks for collection”) is configured to:
group valid data from the plurality of erase blocks across the plurality of storage devices based on a similarity of the plurality of characteristics between the valid data stored at the plurality of erase blocks (Fig. 2 is shown the plurality of storage devices, Fig. 3 is shown the at least Flash Memory with the grouping valid data in the blocks or erase blocks; col. 2, lines 20-31, and lines 49-67; col. 4, lines 7-14, and col. 10, lines 15-46: via the grouping of plurality of blocks to specify a garbage collection unit, wherein group the blocks comprise the valid data, and group the blocks having invalid data, e.g., “stale” or “staleness” that need to be erased, and col. 11, lines 4-17: “Efficiency metrics for blocks may also be based on characteristics of the block itself, such as how many program & erase cycles the block has undergone, or whether the block is exhibiting high wear or frequent errors… The different factors and access efficiency metrics may be weighted in any number of ways when selecting blocks for garbage collection”, and col. 11, lines 65-67 to col. 12, lines 1-5: “The GCM may collect and combine data with similar update patterns or frequency and store them together, so that frequently updated data is combined together and infrequently updated data is stored separately. For example, infrequently updated data may be combined and stored to blocks having higher wear or lower reliability, while frequently updated data may be combined and stored to blocks with less wear or greater reliability” wherein the technique of “collect and combine” is interpreted as group/grouping. And also see further in col. 12, lines 7-12: teaches “characteristics of stored data”, and lines 38-49), and
(wherein) the erase blocks for storage selected based on the characteristics associated with the valid data from the plurality of erase blocks (see col. 1, lines 31-33: “The garbage collection operation may include selecting a plurality of blocks on which to perform the garbage collection operation,…” wherein the technique of “selecting” is interpreted as “are indicated”, and see further in Fig. 3 for indicating the erase blocks as ready to be garbage collected; col. 6, lines 45-62; and col. 10, lines 15-46: wherein “stale” or “staleness” inherits to “age” or “time” which is interpreted as characteristic associated with data in the blocks/pages of the storage device(s), col. 11, lines 62-67 to col. 12, lines 1-5: “select those blocks for garbage collection to consolidate the data associated with the particular stream. Access pattern analysis may also indicate how frequently certain data is updated. The GCM may collect and combine data with similar update patterns or frequency and store them together, so that frequently updated data is combined together and infrequently updated data is stored separately. For example, infrequently updated data may be combined and stored to blocks having higher wear or lower reliability, while frequently updated data may be combined and stored to blocks with less wear or greater reliability. Other embodiments are also possible.”; and col. 12, lines 7-8: “characteristics of stored data”) and wear-related characteristic of the erase blocks (col. 11, lines 4-17, e.g., “Efficiency metrics for blocks may also be based on characteristics of the block itself, such as how many program & erase cycles the block has undergone, or whether the block is exhibiting high wear or frequent errors... Factors such as the staleness of a block may still be considered and factored into the efficiency metrics…”; and col. 11, lines 65-67 to col. 12, lines 1-5: “... For example, infrequently updated data may be combined and stored to blocks having higher wear or lower reliability, while frequently updated data may be combined and stored to blocks with less wear or greater reliability”: wherein the “higher wear” and “less wear” are interpreted as “wear-related characteristic of the (erase) blocks, col. 12, lines 40-49: “The target blocks to which the garbage collected data may be stored can also be evaluated. For example, data selected because it is frequently updated may be stored to a block with low wear levels, while data that is infrequently updated may be stored to a block with higher wear. Intelligently selecting blocks and data for garbage collection can improve the quality of service provided by the DSD, with faster response times, more reliable data storage, and other improvements”)
Accordingly, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the instant application to combine the teachings of the cited references because the teachings of Ebsen would have provided Kimmel with the above indicated limitations for allowing a skilled artisan in motivation to improve the grouping valid/invalid data (e.g., frequently/infrequently updated data) in erase blocks (e.g., target blocks) based on the similar characteristics of data for performing the garbage collection to efficiently free space, faster response time, more reliable data storage, and other improvements of the storage device(s) including SSD (Ebsen: Abstract, Figs. 2-3; cols. 2-3; col. 10, lines 15-65; and col. 11, lines 54-67 to col. 12, lines 1-49)
Kimmel teaches the optimization for a non-volatile solid-state cache/storage device(s) including the erase blocks and valid data/entries having the characteristic, e.g., similar “aging”, and grouping of valid and invalid data/entries of erase blocks (col. 3, lines 44-67; and cols. 4-5). Ebsen, in the same field of endeavor, teaches enhanced garbage collection processing operations include selecting, combining and grouping the valid (frequently) and invalid (infrequently) data of the blocks of the plurality of storage devices including the solid-state storage devices based on the data is “stale”/”staleness” (Figs. 1-2 and cols. 4, 10-12, for instance; col. 1, lines 31-33: “The garbage collection operation may include selecting a plurality of blocks on which to perform the garbage collection operation,…” and see further in Fig. 3 for indicating the erase blocks as ready to be garbage collected; col. 2, lines 23-67; col. 10, lines 15-46: wherein “stale” or “staleness” inherits to “age” or “time” which is interpreted as characteristic associated with data in the blocks/pages of the storage device(s), and col. 11, lines 4-17, e.g., “Efficiency metrics for blocks may also be based on characteristics of the block itself, such as how many program & erase cycles the block has undergone, or whether the block is exhibiting high wear or frequent errors. Data and statistics may also be maintained according to data streams, rather than or in addition to data maintained for particular blocks, GCUs, or data segments. Factors such as the staleness of a block may still be considered and factored into the efficiency metrics…”, and lines 54-67 to col. 12, lines 1-49).
However, Kimmel and Ebsen do not explicitly teach: “store the grouped valid data at erase blocks of the plurality of storage devices.”
In the same field of endeavor (i.e., data processing), teaches: “store the grouped valid data at erase blocks of the plurality of storage devices” (see [0047] “aggregating data blocks that rely on a reference data set into a segment. The segment refers to a chunk of flash storage that can be filled sequentially and erased as a unit” and [0083] “data blocks and update one or more identifiers associated with the data block in a records table stored in a data store (e.g. data storage repository 110/220)”, wherein the data storage repository 110 comprises data storage devices 112a and 112n as shown in Fig. 1).
Accordingly, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the instant application to combine the teachings of the cited references because the teachings of Singhai would have provided Kimmel and Ebsen with the storing the grouped of valid data at erase blocks of the plurality of storage devices for allowing a skilled artisan in motivation to improve the storing of the grouped valid data in erase blocks in the plurality of storage devices enhancing the garbage collection efficiently (Singhai: Fig. 1 and par. [0038]: “The endurance reduction in flash storage devices is associated with the tolerance for write-erase cycles by the flash storage device, while performance of the flash storage device is impacted by the availability of free writeable data blocks in the flash storage device”).
Regarding claim 2, Kimmel, Ebsen, and Singhai, in combination, teach: wherein the plurality of storage devices comprise a plurality of direct-mapped solid-state storage devices (Kimmel: Fig. 3, and col. 3, lines 28-39; Ebsen: Fig. 1 and Fig. 2 at element 203, 206, and 209, and col. 2, lines 20-31, e.g., “a solid state drive (SSD)”, and lines 54-64; and Singhai: Fig. 17 as shown the directed mapped solid-state storage devices, pars. [0004] “perform data block aggregation by comparing each corresponding data block of an incoming data set to a stored data block in storage…”, [0034] “managing sets of reference data blocks in storage devices”).
Regarding claim 3, Ebsen and Singhai teach: wherein the garbage collection process is performed (Ebsen: col. 1, lines 27-38, e.g., “to perform the garbage collection operation”) based on a capacity of the plurality of storage devices being used for storage (Ebsen: see col. 3, lines 1-13, e.g., “a storage drive’s capacity is filled with invalid data, the drive may perform garbage collection operations to recapture blocks for storage. Garbage collection may include copying the valid data from one or more blocks, and then erasing or resetting those blocks so that they can be made available for storing additional data”; and Singhai: pars. [0038] “…storage capacity limitations and endurance reduction over the life span. The endurance reduction in flash storage devices is associated with the tolerance for write-erase cycles by the flash storage device, while performance of the flash storage device is impacted by the availability of free writeable data blocks in the flash storage device.” and [0049-50] “Garbage Collection for Reference Sets in Flash Storage Systems” and “…garbage collection can be performed as described below…”, [0055] “ [0189] “… amount of memory used for associated with a data set… a reference data set meets retirement based on the amount of memory used in a storage device…”, wherein the amount of memory is illustrated as the capacity of the storage device(s) as known by a skilled artisan).
Regarding claim 4, Singhai teaches wherein the processing device (Fig. 2 at element 204 – Processor) is further to:
-66-Docket No.: P70479 11840US.C1determine an expected longevity associated with each of the valid data based on the plurality of characteristics, wherein the valid data is grouped based on a similarity of the expected longevity between the valid data (pars.[0010] and [0042] “the reference data sets may have the following characteristics: 1)… a period of time and 2)… Next, 3)… Lastly, 4)…it can be retired after the use count drops to zero…” and [0049-52], “Garbage Collection” algorithm, “valid data blocks” which storing valid data to be moved=erased, “if a reference data set (e.g., reference data set R) is expected to be retired soon, then reconstruct original data blocks using the reference data set (e.g., R) and newly deduplicate it using a newer reference data set(s).”, wherein the “expected to be retired soon” is interpreted as an expected longevity in the claim, and the reconstruct=generate group of original data blocks and group of newer reference data sets, see further in pars. [0143] “the new reference data set may satisfy for retirement …” and [0162], “In some embodiments, reference blocks are grouped into a subset based on a degree of similarity associated with content of each reference data block” wherein herein the data blocks contain the valid data).
Regarding claim 5, Kimmel, Ebsen, and Singhai, in combination, teach: wherein the plurality of characteristics comprise an age associated with each of the valid data (Kimmel: col. 5, lines 9-19: “classification and localization of cache lines with similar cache aging and invalidation behaviors within erase block boundaries, allowing efficient reuse of flash locations while improving effective cache capacity. After erase block fill using these methods, the slow-turn, fast-turn or no-turn designation for an erase block or stripe can be forgotten, using line-granular tracking of line use and invalidation to inform subsequent reuse of the erase block or stripe.”; Ebsen: col. 10, lines 15-46 via the grouping of plurality of blocks to specify a garbage collection unit, wherein group the blocks comprise the valid data, and group the blocks having invalid data, e.g., “stale” or “staleness” that need to be erased, and col. 11, lines 4-17: “… Factors such as the staleness of a block may still be considered and factored into the efficiency metrics.”; and Singhai: pars. [0050-52] “retirement”/”retire older…” inherit to age, and [0189] e.g., “retirement criteria…amount of times, … a predetermined duration (e.g., minutes, hours, days, weeks, etc. “ which equivalent to “age” of the reference data sets storing in blocks of storage device(s), Fig. 2).
Regarding claim 6, Singhai teaches: wherein the plurality of characteristics comprise a type of data associated with each of the valid data (Singhai: par. [0154] “…receives a set of data blocks from one or more client devices (e.g. client devices 102). The set of data blocks can be associated with, but not limited to, document files of a type such as, but not limited to, word doc, pdfs, jpegs, etc., rendered by applications of the client devices (e.g. client devices 102). Next, the method 800 may continue by performing 804 a similarity analysis of the set of data blocks.”, wherein the “a type such as, but not limited to, word doc, pdfs, jpegs, etc.,” is interpreted as type of data which associated with the valid data in data blocks of storage device(s)).
Claims 8-13, 15-20 are rejected in the analysis of above claims 1-6; and therefore, the claims are rejected on that basis.
Claims 7 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Kimmel, Ebsen, and Singhai, and further in view of Huang et al., US Pub. No. 20150019797 (hereinafter as “Huang”).
Regarding claim 7, the claim is rejected by the same reasons set forth above to claim 1. However, Kimmel, Ebsen, and Singhai do not explicitly teach “wherein the plurality of characteristics specifies a deduplication importance associated with each valid data,” and “the deduplication importance corresponding to a number of times that a respective valid data was associated with a deduplication operation.”
In the same field of endeavor (i.e., data processing), Huang teaches:
wherein the plurality of characteristics specifies a deduplication importance associated with each valid data (pars. [0034-37] teaches the duplicate pages/data found in block(s) during the garbage collection processing or performing), the deduplication importance corresponding to a number of times that a respective valid data was associated with a deduplication operation (Fig. 5 element 512 checking for “De-dupe” data, and pars. [0035-37] and [0050-51] teaches exceeding threshold implies to detecting a number of times the valid/invalid pages/data were associated with the duplicate operation).
Therefore, it would have been obvious to one of ordinary skill in the data processing art before the effective filing date of the claimed invention to combine the teachings of the cited references because the teachings of Huang would have provided Kimmel, Ebsen, and Singhai with the above indicated limitations for facilitating data deduplication to perform garbage collection to save/reduce storage.
Claim 14 is rejected in the analysis of above claim 7; and therefore, the claim is rejected on that basis.
Response to Arguments
Referring to claim rejections under 35 U.S.C. §101, Applicant’s arguments (see Remarks, pages 7-8) have been fully considered, and are persuasive; thus, the rejections have been withdrawn.
Referring to claim rejections under 35 USC. §103, Applicant’s arguments (see Remarks, pages 8-11) to the claim limitations including amended limitation in claim 1 (similar to claims 8 and 15) have been fully considered but are not persuasive.
Regarding claim 1, Applicant argued that “Kimmel does not disclose identifying valid data at erase blocks across multiple storage devices, nor does it disclose grouping such data during a garbage collection process” (Remarks, page 8, last paragraph). Examiner is not persuaded because Kimmel teaches, discloses, or expressly suggests the “various different data classes”, “erase block”, “group together data with similar cache aging and invalidation behaviors” (col. 3, lines 45-53), and “the data classes include “slow-turn data”, “fast-turn data”, and “no-turn data” (col. 3, lines 58-59), which place into erase blocks or erase tripes (col. 4, lines 18-19). Kimmel is also shown in the Figure 3 as the plurality of storage devices including the solid-state storage device(s) as well. Furthermore, Kimmel’s col. 8, lines 37-41 include: “The EC layer 36 can use a different type of write request for each possible data classification (e.g., slow turn, fast turn, no turn) to indicate to the FAL 37 the classification of data it passes to the FAL 37 for caching”, and lines 59-62: “A "write unit" in this context is a group of several (e.g., eight) queued data blocks of the same data class (e.g., slow-turn, fast-turn or no-turn) received by the FAL 37 from the EC layer 36”. Accordingly, Examiner has the right to interpret the data classification in the same data class with the particular/specific “slow-turn, fast-turn or no-turn” as the characteristics which is associated the data.
Per Applicant’s argument to Ebsen (see Remarks, pages 9-10), Examiner respectfully submits that Ebsen, in the same field of endeavor (i.e., data processing), teach the erase blocks are indicated as ready to be garbage collection (col. 1, lines 27-33: valid data, and “The garbage collection operation may include selecting a plurality of blocks on which to perform the garbage collection operation,…” wherein the technique of “selecting” is interpreted as “are indicated”, and see further in Fig. 3 for indicating the erase blocks as ready to be garbage collected). Furthermore, Ebsen teaches, discloses, or expressly suggests “the characteristics associated with the valid data” (see col. 6, lines 45-62; and col. 10, lines 15-46: wherein “stale” or “staleness” inherits to “age” or “time” which is interpreted as characteristic associated with data in the blocks/pages of the storage device(s), col. 11, lines 62-67 to col. 12, lines 1-5: “select those blocks for garbage collection to consolidate the data associated with the particular stream. Access pattern analysis may also indicate how frequently certain data is updated. The GCM may collect and combine data with similar update patterns or frequency and store them together, so that frequently updated data is combined together and infrequently updated data is stored separately. For example, infrequently updated data may be combined and stored to blocks having higher wear or lower reliability, while frequently updated data may be combined and stored to blocks with less wear or greater reliability. Other embodiments are also possible.”; and col. 12, lines 7-8: “characteristics of stored data”) and “wear-related characteristic of the erase blocks” (col. 11, lines 4-17, e.g., “Efficiency metrics for blocks may also be based on characteristics of the block itself, such as how many program & erase cycles the block has undergone, or whether the block is exhibiting high wear or frequent errors... Factors such as the staleness of a block may still be considered and factored into the efficiency metrics…”; and col. 11, lines 65-67 to col. 12, lines 1-5: “... For example, infrequently updated data may be combined and stored to blocks having higher wear or lower reliability, while frequently updated data may be combined and stored to blocks with less wear or greater reliability”: wherein the “higher wear” and “less wear” are interpreted as “wear-related characteristic of the (erase) blocks, col. 12, lines 40-49: “The target blocks to which the garbage collected data may be stored can also be evaluated. For example, data selected because it is frequently updated may be stored to a block with low wear levels, while data that is infrequently updated may be stored to a block with higher wear. Intelligently selecting blocks and data for garbage collection can improve the quality of service provided by the DSD, with faster response times, more reliable data storage, and other improvements”). Ebsen teaches “a data storage device”, “a solid state drive (SSD)”, and “solid state memories” (col. 2, lines 23-24, line 31, and line 59).
Also, Singhai, in the same field of endeavor (i.e., data processing), teaches, discloses, or expressly suggests that the data is grouped into blocks of storage devices (Fig. 1) based on data reference including “characteristics: 1)… a period of time and 2)… Next, 3)… Lastly, 4)…it can be retired after the use count drops to zero…” (pars.[0010], [0042]). Singhai teaches the “Garbage Collection” algorithm, “valid data blocks” which storing valid data to be moved=erased, “if a reference data set (e.g., reference data set R) is expected to be retired soon according “a period of time”, then reconstruct original data blocks using the reference data set (e.g., R) and newly deduplicate it using a newer reference data set(s) (pars. [0049-52] where the reconstruct=generate group of original data blocks and group of newer reference data sets; and see also in pars. [0143]: “the new reference data set may satisfy for retirement …” related to age/time, and [0162], “In some embodiments, reference blocks are grouped into a subset based on a degree of similarity associated with content of each reference data block” wherein herein the data blocks contain the valid data).
Therefore, as above explanation and accordance, Kimmel, Ebsen, and Singhai are analogous because they are directed to the same field of invention as data processing and storing in the data blocks/chunks/segments of the storage device(s) (Kimmel: Fig. 1, and Fig. 3; Ebsen: Figs. 1-3; Singhai: Fig. 1).
At the time of the invention, it would have been obvious to one of ordinary skill in the art having the teachings of Kimmel, Ebsen, and Singhai before him or her to modify and combine the data classes to group data together and place into erase blocks or erase stripes as disclosed in Kimmel to include enhanced garbage collection based on characteristics of data and of blocks to evaluate whether data is/are valid and invalid to perform grouping as disclosed in Ebsen and to including storing blocks/group of blocks into data storage device(s) as disclosed in Singhai.
One of ordinary skill in the art would have been motivated to make this change in order to improve the quality of service with free space, faster response time, more reliable data storage.
Therefore, it would have been obvious to combine the teachings of Kimmel, Ebsen, and Singhai to obtain the instant claim.
For at least above reasons, the rejections are maintained.
Any other claims argued merely because of a dependency on a previouslyargued claim(s) in the arguments presented to the examiner on 06/19/2026 (Remarks, pages 11-12) are moot in view of the examiner's interpretation of the claims and art and are still considered rejected based on their respective rejections from at least a prior Office action (part(s) of recited above).
Examiner has full latitude to interpret limitation(s) of each claim (e.g., “characteristics”) in the broadest reasonable sense. See MPEP §2111 – Claim Interpretation, e.g., "During examination, the claims must be interpreted as broadly as their terms reasonably allow." In re American Academy of Science Tech Center, 367 F.3d 1359, 1369, 70 USPQ2d 1827, 1834 (Fed. Cir. 2004) (The USPTO uses a different standard for construing claims than that used by district courts; during examination the USPTO must give claims their broadest reasonable interpretation). In Phillips v. AWH Corp., 415 F.3d 1303, 75 USPQ2d 1321 (Fed. Cir. 2005), the court further elaborated on the “broadest reasonable interpretation" standard and recognized that “The Patent and Trademark Office (“PTO") determines the scope of claims in patent applications not solely on the basis of the claim language, but upon giving claims their broadest reasonable construction." Thus, when interpreting claims, the courts have held that Examiners should (1) interpret claim terms as broadly as their terms reasonably allows and (2) interpret claim phrases as broadly as their construction reasonably allows.
The Examiner will reference prior art using terminology familiar to one of ordinary skill in the art. Such an approach is broad in concept and can be either explicit or implicit in meaning.
Prior Arts
The prior art made of record on form PTO-892 and not relied upon is considered pertinent to applicant's disclosure. Applicant is required under 37 C.F.R. § 1.111(c) to consider these references fully when responding to this action.
It is noted that any citation to specific, pages, columns, lines, or figures in the prior art references and any interpretation of the references should not be considered to be limiting in any way. A reference is relevant for all it contains and may be relied upon for all that it would have reasonably suggested to one having ordinary skill in the art. See In re Heck, 699 F.2d 1331, 1332-33, 216 USPQ 1038, 1039 (Fed. Cir. 1983) (quoting In re Lemelson, 397 F.2d 1006, 1009, 158 USPQ 275,277 (CCPA 1968)); Merck & Co. v. Biocraft Laboratories, 874 F.2d 804, 10 USPQ2d 1843 (Fed. Cir.), cert. denied, 493 U.S. 975 (1989).
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Jessica N. Le whose telephone number is (571)270-1009. The examiner can normally be reached M-F 9:30 am - 5:30 pm (EST).
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, SHERIEF BADAWI can be reached on (571) 272-9782. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/Jessica N Le/Examiner, Art Unit 2169
/SHERIEF BADAWI/Supervisory Patent Examiner, Art Unit 2169
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