Prosecution Insights
Last updated: October 02, 2026
Application No. 18/641,801

SYSTEMS AND METHODS OF GENERATING A RELATIONAL ATTRIBUTE NETWORK IN A STORAGE SYSTEM

Final Rejection §103
Filed
Apr 22, 2024
Examiner
CURRAN, J MITCHELL
Art Unit
2169
Tech Center
2100 — Computer Architecture & Software
Assignee
Dell Products L.P.
OA Round
4 (Final)
64%
Grant Probability
Moderate
5-6
OA Rounds
8m
Est. Remaining
94%
With Interview

Examiner Intelligence

Grants 64% of resolved cases
64%
Career Allowance Rate
75 granted / 117 resolved
+9.1% vs TC avg
Strong +30% interview lift
Without
With
+30.2%
Interview Lift
resolved cases with interview
Typical timeline
3y 2m
Avg Prosecution
5 currently pending
Career history
129
Total Applications
across all art units

Statute-Specific Performance

§101
8.3%
-31.7% vs TC avg
§103
66.4%
+26.4% vs TC avg
§102
15.8%
-24.2% vs TC avg
§112
4.6%
-35.4% vs TC avg
Black line = Tech Center average estimate • Based on career data from 117 resolved cases

Office Action

§103
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 . Detailed Action This is an Office Action for application 18/641,801, in response to arguments and amendments filed on 06/17/2026. Claims 1, 11 and 20 are currently amended. Claims 1-20 are pending and examined below. Response to Arguments Applicant’s arguments, see pgs. 8-11, filed 06/17/2026, with respect to the rejection(s) of claim(s) 1-20 under 35 USC § 103 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Vasquez-Cantell et al. (US Pub. 2023/0359705) and Kundu et al. (US Pub. 2024/0311395). 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. Claim(s) 1-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Mueller et al. (WO 2020/010350) in view of Vasquez-Cantell et al. (US Pub. 2023/0359705) and Kundu et al. (US Pub. 2024/0311395). Regarding claim 1, Mueller teaches A computer-implemented method comprising: receiving telemetry data from one or more system components, the telemetry data including a plurality of values associated with a plurality of attributes; (Fig. 1a; Abs. Par. [000115] a number of stored time series data variables (i.e. telemetry data including values and attributes) are received by the user in the process of generating the correlation graph) storing the telemetry data in a data structure according to the plurality of attributes; (Fig. 1a; Abs., Par. [000115] a number of stored time series variables (i.e. telemetry data) are selected by the user in the process of generating the correlation graph) Mueller does not explicitly teach generating a correlation matrix from the data structure, the correlation matrix including entries that indicate correlation values for corresponding pairs of the plurality of attributes; and generating, from the entries of the correlation matrix, a correlation network graph including a plurality of nodes corresponding to the plurality of attributes and a plurality of undirected edges, each undirected edge connecting a corresponding pair of the plurality of nodes and being weighted according to the correlation value indicated by a corresponding entry of the correlation matrix for the corresponding pair of the plurality of attributes. However, from the same field, Vasquez-Cantell teaches generating a correlation matrix from the data structure, the correlation matrix including entries that indicate correlation values for corresponding pairs of the plurality of attributes; and (Fig 5; Par [0087] a correlation matrix is generated based on relationships between devices (i.e. corresponding pairs)) It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to combine the graph correlation matrix of Vasquez-Cantell into the telemetry data of Mueller. The motivation for this combination would have been to improve event detection as explained in Vasquez-Cantell (Par. [0039]). The combination of Mueller and Vasquez-Cantell do not explicitly teach generating, from the entries of the correlation matrix, a correlation network graph including a plurality of nodes corresponding to the plurality of attributes and a plurality of undirected edges, each undirected edge connecting a corresponding pair of the plurality of nodes and being weighted according to the correlation value indicated by a corresponding entry of the correlation matrix for the corresponding pair of the plurality of attributes. However, from the same field, Kundu teaches generating, from the entries of the correlation matrix, a correlation network graph including a plurality of nodes corresponding to the plurality of attributes and a plurality of undirected edges, each undirected edge connecting a corresponding pair of the plurality of nodes and being weighted according to the correlation value indicated by a corresponding entry of the correlation matrix for the corresponding pair of the plurality of attributes. (Fig. 5A; Par. [0076-8] an observability graph (#504) is generated based on various data sources (#502-1 – 501-N) and the graph policy (#506)) It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to combine the relational attribute network of Kundu into the telemetry data of Mueller. The motivation for this combination would have been to improve distributed tracing and analysis as explained in Kundu (Par. [0017]). Regarding claim 2, Muller, Vasquez-Cantell and Kundu teach claim 1 as shown above, and Mueller further teaches The method of claim 1 wherein the one or more system components includes a first component and a second component, wherein generating the graph includes identifying a relationship between a first attribute of the first component and a second attribute of the first component or second component. (Fig. 1A-B, 1D, Par. [000100] the path diagram view (1B) shows a visual analysis of both causation and correlation, including relationships between time series variables (i.e. telemetry attributes)) Regarding claim 3, Muller, Vasquez-Cantell and Kundu teach claim 1 as shown above, and Mueller further teaches The method of claim 1 wherein generating the graph includes identifying an indirect relationship between a first attribute and a second attribute, wherein a first node of the plurality of nodes corresponding to the first attribute and a second node of the plurality of nodes corresponding to the second attribute are connected by at least two edges. (Fig. 11B; Par. [00042] in the given example, event c causes event e indirectly via chaining (i.e. two edges)) Regarding claim 4, Muller, Vasquez-Cantell and Kundu teach claim 1 as shown above, and Mueller further teaches The method of claim 1 further comprising storing the graph in a database and providing a query interface configured to receive a user query relating to at least one of the plurality of attributes. (Par. [000221] users are able to save the discoveries of the analysis for later re-examination (i.e. user query for list of related components)) Regarding claim 5, Muller, Vasquez-Cantell and Kundu teach claim 4 as shown above, and Mueller further teaches The method of claim 4 comprising generating a list of related components in response to the user query. (Par. [000221] users are able to save the discoveries of the analysis for later re-examination (i.e. user query for list of related components)) Regarding claim 6, Muller, Vasquez-Cantell and Kundu teach claim 4 as shown above, and Mueller further teaches The method of claim 4 further comprising providing a response to the user query indicating the correlation between the at least two nodes. (Fig. 11B; Par. [00042] in the given example, event c causes event e indirectly through x via chaining (i.e. two nodes)) Regarding claim 7, Muller, Vasquez-Cantell and Kundu teach claim 6 as shown above, and Mueller further teaches The method of claim 6 wherein the user query includes a prospective system change and the response includes a list of affected attributes related to the prospective system change. (Fig. 12B; Par. [000267-8] user inspects rows (i.e. a list) and chooses a column (i.e. prospective system change) to check its significance) Regarding claim 8, Muller, Vasquez-Cantell and Kundu teach claim 1 as shown above, and Mueller further teaches The method of claim 1 wherein the one or more system components comprises a complex system. (Par. [00095] visual analytics is used in this system to better understand complex systems) Regarding claim(s) 9, Muller, Vasquez-Cantell and Kundu teach claim 8 as shown above, and Vasquez-Cantell further teaches The method of claim 8 wherein the complex system comprises a distributed storage system. (Par. [0099] the system can be a distributed system) Regarding claim 10, Muller, Vasquez-Cantell and Kundu teach claim 1 as shown above, and Mueller further teaches The method of claim 1 wherein the telemetry data is further stored in the data structure according to an event time. (Fig. 1a; Abs. a number of stored time series (i.e. according to event time) data variables are received by the user in the process of generating the correlation graph) Regarding claim 11, while worded slightly differently, is rejected under the same rationale as claim 1. Mueller further teaches a memory; and at least one processor (Par. [000312] system includes memory and processors) Regarding claim 12, while worded slightly differently, is rejected under the same rationale as claim 2. Regarding claim 13, while worded slightly differently, is rejected under the same rationale as claim 3. Regarding claim 14, while worded slightly differently, is rejected under the same rationale as claim 4. Regarding claim 15, while worded slightly differently, is rejected under the same rationale as claim 5. Regarding claim 16, while worded slightly differently, is rejected under the same rationale as claim 6. Regarding claim 17, while worded slightly differently, is rejected under the same rationale as claim 7. Regarding claim 18, while worded slightly differently, is rejected under the same rationale as claim 8. Regarding claim 19, while worded slightly differently, is rejected under the same rationale as claim 9. Regarding claim 20, while worded slightly differently, is rejected under the same rationale as claim 11. 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 J MITCHELL CURRAN whose telephone number is (469)295-9081. The examiner can normally be reached M-F 8:00am - 5:00pm. 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. /J MITCHELL CURRAN/Examiner, Art Unit 2161 /SHERIEF BADAWI/Supervisory Patent Examiner, Art Unit 2169
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Prosecution Timeline

Show 5 earlier events
Jun 23, 2025
Response Filed
Oct 07, 2025
Final Rejection mailed — §103
Dec 08, 2025
Response after Non-Final Action
Jan 05, 2026
Request for Continued Examination
Jan 22, 2026
Response after Non-Final Action
Mar 17, 2026
Non-Final Rejection mailed — §103
Jun 17, 2026
Response Filed
Sep 21, 2026
Final Rejection mailed — §103 (current)

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

5-6
Expected OA Rounds
64%
Grant Probability
94%
With Interview (+30.2%)
3y 2m (~8m remaining)
Median Time to Grant
High
PTA Risk
Based on 117 resolved cases by this examiner. Grant probability derived from career allowance rate.

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