Prosecution Insights
Last updated: April 19, 2026
Application No. 18/913,807

MICROSERVICE PROVISION AND MANAGEMENT

Non-Final OA §102§DP
Filed
Oct 11, 2024
Examiner
WILLIAMS, CLAYTON R
Art Unit
2443
Tech Center
2400 — Computer Networks
Assignee
Intel Corporation
OA Round
1 (Non-Final)
82%
Grant Probability
Favorable
1-2
OA Rounds
2y 9m
To Grant
76%
With Interview

Examiner Intelligence

Grants 82% — above average
82%
Career Allow Rate
551 granted / 676 resolved
+23.5% vs TC avg
Minimal -5% lift
Without
With
+-5.2%
Interview Lift
resolved cases with interview
Typical timeline
2y 9m
Avg Prosecution
12 currently pending
Career history
688
Total Applications
across all art units

Statute-Specific Performance

§101
17.1%
-22.9% vs TC avg
§103
39.1%
-0.9% vs TC avg
§102
13.2%
-26.8% vs TC avg
§112
19.1%
-20.9% vs TC avg
Black line = Tech Center average estimate • Based on career data from 676 resolved cases

Office Action

§102 §DP
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 . Claims 1-15 are pending. Double Patenting The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969). A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b). The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13. The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer. Claims 1-3, 5-8, 10-13 and 15 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-3, 5-8, 10-13 and 15 of U.S. Patent No. 12141620 (hereinafter ‘620). Although the claims at issue are not identical, they are not patentably distinct from each other because each of the instant, enumerated claims in following table is anticipated by a correspondingly mapped ‘620 claim. Instant claims ‘620 claims 1, 6, 11. Distributed computing system configurable for use in association with providing at least one cloud service associated with Internet of Things (IoT) resources, the distributed computing system comprising: processing hardware; and machine-readable memory storing instructions for being executed by the processing hardware, the instructions, when executed by the processing hardware, resulting in the distributed computing system being configured for performance of operations comprising: determining, based upon telemetry data, metrics data, and machine-learning, whether at least one condition is present; and in event that the at least one condition is determined to be present, determining at least one responsive action to be taken; wherein: [1] the telemetry data is associated with IoT-resource-related object data; and the IoT-resource-related object data is configurable to indicate one or more of: behaviors related to the IoT resources; states related to the IoT resources; and interactions related to the IoT resources. 2, 7, 12. The distributed computing system of claim 1, wherein: the at least one responsive action is configurable to result in one or more of: alert data; and taking at least one other action (maps to ‘620, claims 1, 6 and 11 limitation “determining at least one action to be taken in response to the determination that the at least one condition is present”) . 3, 8, 13. The distributed computing system of claim 1, wherein: modeling data is to be used in association with the IoT-resource-related object data; and the modeling data is for use in association with one or more of: behavior modeling; and failure event data. 3, 8, 13. The distributed computing system of claim 1, wherein: modeling data is to be used in association with the IoT-resource-related object data; and the modeling data is for use in association with one or more of: behavior modeling; and failure event data. 5, 10, 15. The distributed computing system of claim 1, wherein: one or more of the IoT resources are associated with one or more of: at least one vehicle; at least one emergency vehicle; at least one temperature sensor; at least one weather sensor; at least one alarm system; at least one camera; at least one traffic monitor; and at least one traffic light. 1, 6, 11. Distributed computing system configurable for use in association with providing at least one cloud service associated with Internet of Things (IoT) resources, the distributed computing system comprising: computing hardware; and machine-readable memory storing instructions for being executed by the computing hardware, the instructions, when executed by the computing hardware, resulting in the distributed computing system being configured for performance of operations comprising: associating the IoT resources with IoT-related objects; [1] receiving telemetry data associated, at least in part, with the IoT-related objects; generating, based upon the telemetry data, at least one of IoT resource health-related data and event management-related data; and based upon determination, based upon the telemetry data and associated metrics data, that at least one condition is present, determining at least one action to be taken in response to the determination that the at least one condition is present; wherein: the IoT-related objects are configurable to comprise object data to indicate at least one of behaviors, states, and interactions that are in association with the IoT resources; the distributed computing system is configurable to utilize machine-learning in association with the determination that the at least one condition is present; and the distributed server system is configurable to monitor central processing unit (CPU) usage and memory usage in association with the telemetry data. 2, 7, 12. The distributed computing system of claim 1, wherein: the operations also comprise generating modeling data for use in association with the IoT-related objects; and the modeling data is for use in association with failure event data. 3, 8, 13. The distributed computing system of claim 2, wherein: the modeling data is for use in association with behavior modeling. 5, 10, 15. The distributed computing system of claim 1, wherein: one or more of the IoT resources are associated with one or more of: at least one vehicle; at least one emergency vehicle; at least one temperature sensor; at least one weather sensor; at least one alarm system; at least one camera; at least one traffic monitor; and/or at least one traffic light. Claim Rejections - 35 USC § 102 The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action: A person shall be entitled to a patent unless – (a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention. Claims 1-15 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Yang US 20180375720. For claims 1, 6 and 11, Yang discloses: Distributed computing system configurable for use in association with providing at least one cloud service associated with Internet of Things (IoT) resources (par. 0020: distributed IoT management system disclosed; par. 0022: Cloud-based geolocation and computational services disclosed; par. 0014: IoT system comprising plurality of devices/assets 105), the distributed computing system comprising: processing hardware (par. 0036: computer processor apparatus disclosed); and machine-readable memory storing instructions for being executed by the processing hardware, the instructions, when executed by the processing hardware, resulting in the distributed computing system being configured for performance of operations comprising: determining, based upon telemetry data, metrics data, and machine-learning, whether at least one condition is present (par. 0056: “During operation of an asset 105 in an IoT system governed by application 418, telemetry logic 426 of the asset 105 can collect data generated by various sensors provisioned within the asset 105 describing performance attributes and state of the asset 105 during operation. Operating status 428 and status changes can be determined from the sensor data (e.g., by machine learning logic of the asset 105”). Par. 0056: Furthermore, assets 105 periodically send local model 432 data to management system 1540 of IoT system.)); and in event that the at least one condition is determined to be present, determining at least one responsive action to be taken (par. 0059: “An out-of-service condition (e.g., at 446) or other operating status 428 detected at a particular asset (e.g., 105) can prompt remediation at the system level by the management system 150….Assets can also escalate issues (e.g., out-of-service conditions) detected in real-time at the asset to prompt the management system to initiate a wider reconfiguration or redeployment (e.g., in response to self-healing or other tasks performed at the asset failing to resolve the issue(s)).”); wherein: the telemetry data is associated with IoT-resource-related object data (par. 0056: “…telemetry logic 426 of the asset 105 can collect data generated by various sensors provisioned within the asset 105”); and the IoT-resource-related object data is configurable to indicate one or more of: behaviors related to the IoT resources; states related to the IoT resources; and interactions related to the IoT resources (par. 0058 and 0059: Local asset 105 reconfiguration taught in light of observed/reporting operating status conditions. Management system 150 performs remediation of detected asset 105 problems). For claims 2, 7 and 12, Yang discloses: The distributed computing system of claim 1, wherein: the at least one responsive action is configurable to result in one or more of: alert data; and taking at least one other action (par. 0059: Response to a change in operating status include “[r]edeployment 458…can involve redeploying the same collection of assets (including asset 105), but with an adjustment to the configuration of the overall system (or one or more devices) as determined by the management system 150 from the global model.)”. For claims 3, 8 and 13, Yang discloses: The distributed computing system of claim 1, wherein: modeling data is to be used in association with the IoT-resource-related object data (par. 0043: “The global model 225 can include component models modeling each of a collection of taxonomies, or device abstractions, as well as model specific one or more of the devices known to the management system 150 and falling within one or more of the taxonomies. The global model 255 can be derived from or updated based on copies of local models 230 maintained locally at IoT assets (e.g., 105a-b, 125)…”; and the modeling data is for use in association with one or more of: behavior modeling; and failure event data (par. 0049: “…the global resiliency manager 210 can utilize the global model to identify and forecast events affecting a portion of a broader IoT system (e.g., two or more assets) and can utilize functionality of the IoT management system 150 to restart or reconfigure two or more devices in a system (e.g., using device manager 214)…”). For claims 4, 9 and 14, Yang discloses: The distributed computing system of claim 1, wherein: the distributed computing system is to execute one or more workloads for use in association with the IoT resources and the providing of the at least one cloud service (par. 0031: “…a scalable system management framework for resilient Internet of Things (IOT) systems is provided that facilitates the ability of IOT applications or services to dynamically adapt to changes in the system (e.g., battery level change, microprocessor idle time, network topology, device workload change, etc.)”; par. 0022: IoT systems interface with cloud-based services). For claims 5, 10 and 15, Yang discloses: The distributed computing system of claim 1, wherein: one or more of the IoT resources are associated with one or more of: at least one vehicle; at least one emergency vehicle; at least one temperature sensor; at least one weather sensor; at least one alarm system; at least one camera; at least one traffic monitor; and at least one traffic light (par. 0018: IoT devices include HVAC controllers and vehicle interior/exterior sensors). Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to CLAYTON R WILLIAMS whose telephone number is (571)270-3801. The examiner can normally be reached M-F 10:00am - 6:00pm. 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, Nicholas Taylor can be reached at 571-272-3889. 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. /CLAYTON R WILLIAMS/Primary Examiner, Art Unit 2443
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Prosecution Timeline

Oct 11, 2024
Application Filed
Apr 04, 2026
Non-Final Rejection — §102, §DP (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

1-2
Expected OA Rounds
82%
Grant Probability
76%
With Interview (-5.2%)
2y 9m
Median Time to Grant
Low
PTA Risk
Based on 676 resolved cases by this examiner. Grant probability derived from career allow rate.

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