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 .
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Information Disclosure Statement
The information disclosure statements (IDS) submitted on August 7, 2024; February 3, 2025; and January 2, 2026 are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements are being considered by the examiner.
Specification
The abstract of the disclosure is objected to because on line 10, -- to – should be inserted after “corresponding”. A corrected abstract of the disclosure is required and must be presented on a separate sheet, apart from any other text. See MPEP § 608.01(b).
The lengthy specification has not been checked to the extent necessary to determine the presence of all possible minor errors. Applicant’s cooperation is requested in correcting any errors of which applicant may become aware in the specification.
The disclosure is objected to because of the following informality:
Numerals 502 and 522 in Figure 5 should be identified in the specification.
Appropriate correction is required.
Claim Objections
Claims 1-20 are objected to because of the following informalities:
In claim 1, line 14, -- to – should be inserted after “corresponding”.
In claim 11, line 20, -- to – should be inserted after “corresponding”.
Appropriate correction is required.
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 1-3, 7-13, 19 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Kruglick (U.S. Patent Publication 2013/0185722) in view of Ramnami et al (U.S. Patent Publication 2021/0209419).
Regarding claim 11, Kruglick teaches a system for reclaiming system resources in an electronic device (See Figure 7), the system comprising: memory (720) storing one or more computer programs; and one or more processors (710) communicatively coupled to the memory, wherein the one or more computer programs include computer-executable instructions that, when executed by the one or more processors individually or collectively, cause the system to: identify an initialization of an activity corresponding to a first application associated with the electronic device (See paragraph [0031)]), determine whether a combination of the activity and the first application is defined in a resource pool database (Paragraph [0032]), upon determining that the combination of the activity and the first application is not defined in the resource pool database: monitor resource consumption by the activity (Paragraph [0038]), and store the combination of the activity and the first application with the monitored resource consumption in the resource pool database, (Paragraph [0039], “the task fingerprint may be a newly identified task fingerprint and updating the task behavior profile may include providing a new fingerprint and a new behavior profile entry”), and upon determining that the combination of the activity and the first application is defined in the resource pool database, reclaim using the resource pool database the system resources corresponding to the combination of the activity and the first application (See paragraph [0031]-[0034}, the task is identified in the behavior profile and resources are allocated, or reallocated, based on the reference task behavior profile). Kruglick does not mention using a reinforced learning (RL) model. Ramnami teaches the use of reinforcement learning in the resource management environment. It would have been obvious to one of ordinary skill in the art at the time of the claimed invention to provide the system of Kruglick with a reinforcement learning model as taught by Ramnami. The rationale is as follows: One of ordinary skill in the art would have been motivated to use the reinforcement learning model as taught by Ramnami in the system of Kruglick since Ramnami shows in Figure 5 using the model to modify usage of computing device resources.
Regarding claim 12, Kruglick teaches to identify the initialization of the activity corresponding to the first application, the one or more computer programs further include computer-executable instructions that, when executed by the one or more processors individually or collectively, cause the system to: monitor an activity manager service to identify the initialization of the activity (Figure 1, 110).
Regarding claim 13, Kruglick teaches wherein one or more computer programs further include computer-executable instructions that, when executed by the one or more processors individually or collectively, cause the system to: receive, via the activity manager service, one or more user inputs corresponding to the activity, and identify the initialization of the activity based on the received one or more user inputs by the activity manager service (Figure 1, 110).
Regarding claims 19 and 20, these are the computer readable medium claims corresponding to system claims 11 and 13 above, and are therefore rejected for the same reasons.
Regarding claims 1-3, these are the method claims corresponding to system claims 11-13 above, and are therefore rejected for the same reasons.
Regarding claim 7, Kruglick further teaches (Paragraphs [0028] and [0051]) determining whether the combination of the activity and the first application is defined in the resource pool database comprises: generating a hash value for the combination of the activity and the corresponding first application; and searching the hash value in the resource pool database.
Regarding claim 8, Kruglick further teaches (Paragraphs [0028] and [0051]) wherein storing the combination of the activity and the first application with the monitored resource consumption in the resource pool database comprises: generating a hash value for the combination of the activity and the corresponding first application; and storing the hash value and the monitored resource consumption in the resource pool database.
Regarding claim 9, Kruglick teaches (Figure 1, blocks 170 and 180) monitoring a performance of the activity; and updating based on the monitored performance of the activity. Kruglick does not mention using a reinforced learning (RL) model. Ramnami teaches the use of reinforcement learning in the resource management environment as taught above. It would have been obvious to one of ordinary skill in the art at the time of the claimed invention to provide the system of Kruglick with a reinforcement learning model as taught by Ramnami for the reasons set forth above.
Regarding claim 10, Kruglick teaches reclaiming the system resources for the activity comprises: identifying a previous amount of the system resources utilized for the activity during one or more previous execution of the activity and corresponding feedbacks (Figure 1, blocks 150 and 180); determining a target amount of the system resources for the activity based on the identified previous amount of system resources and corresponding feedbacks (i.e., using the updated reference task behavior profile); and reclaiming the system resources for the activity based on the determined target amount of the system resources (See paragraph [0031]-[0034}, the task is identified in the behavior profile and resources are allocated, or reallocated, based on the reference task behavior profile). Kruglick does not mention using a reinforced learning (RL) model. Ramnami teaches the use of reinforcement learning in the resource management environment as taught above. It would have been obvious to one of ordinary skill in the art at the time of the claimed invention to provide the system of Kruglick with a reinforcement learning model as taught by Ramnami for the reasons set forth above.
Claims 4-6 and 14-18 are rejected under 35 U.S.C. 103 as being unpatentable over Kruglick (U.S. Patent Publication 2013/0185722) in view of Ramnami et al (U.S. Patent Publication 2021/0209419) as applied to claims 1 and 11 above, and further in view of Yang et al (U.S. Patent 11,099,900).
Regrading claims 4 and 14, Kruglick in view of Ramnami does not mention the specific details of reclaiming the memory. Yang teaches (Column 1, lines 34+) that it is known in the art to determine whether the system resources available at the electronic device are sufficient to execute the activity corresponding to the first application; and upon determining the system resources available at the electronic device is insufficient to execute the activity corresponding to the first application, reclaiming the system resources for the activity corresponding to the first application. Yang further teaches (See Figure 2A and the description of step 202 in Column 10) a process that identifies one or more second applications running on the electronic device, identifying context information corresponding to the first application and the one or more second applications, and terminating at least one of the one or more second applications based on the corresponding identified context information. It would have been obvious to one of ordinary skill in the art at the time of the claimed invention to provide the system of Kruglick in view of Ramnami with the reclaiming of memory process as taught by Yang. The rationale is as follows: One of ordinary skill in the art would have been motivated to reclaim memory using a priority list of processes as taught by Yang so that less important applications are the first ones to be deleted in order to free up memory, as taught by Yang.
Regarding claims 5 and 15, the method of Yang includes classifying each of the one or more second applications as at least one of a neighboring application (See column 12, line 40, “application relation”) or a non-neighboring application based on the identified context information (See column 12, line 40, “application relation”); and terminating the at least one of the one or more second applications classified as the non-neighboring application (i.e., when a low priority application that includes a high application relation score is killed, then a non-neighboring application is terminated). The rationale for combining Yang with Kruglick in view of Ramnami is the same as the rationale used above with respect to claim 4.
Regarding claims 6 and 16, Yang further teaches identifying one or more operational characteristics of each of the one or more second applications, the one or more operational characteristics comprises a category (Column 13, line 20+, “classified into 18 categories”), an application associativity frequency, a size, and resource utilization of the corresponding second application; determining a neighborhood value corresponding to each of the one or more second applications based on the identified one or more operational characteristics (“a killable list may be determined”); and terminating the at least one of the one or more second applications based on the determined neighborhood value (i.e. applications in the killable list are terminated first). The rationale for combining Yang with Kruglick in view of Ramnami is the same as the rationale used above with respect to claim 4.
Regarding claims 17 and 18, Kruglick shows (Figure 7) the memory further stores the resource pool database and the resource pool database stores hash values corresponding to the combination of the activity and the associated application (Paragraphs [0028] and [0051]).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Lee et al (U.S. Patent Publication 2023/0168807) is cited to show memory reallocation.
Watson et al (U.S. Patent 8,516,198) is cited to show memory management.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to WILLIAM R KORZUCH whose telephone number is (571)272-7589. The examiner can normally be reached Mon.-Fri. 8:00-4:00.
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/WILLIAM R KORZUCH/Supervisory Patent Examiner, Art Unit 2491
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