Prosecution Insights
Last updated: October 02, 2026
Application No. 18/617,684

Method and system for optimizing live migration of a virtual machine from a source server to a destination server

Non-Final OA §102§103
Filed
Mar 27, 2024
Priority
Jul 13, 2023 — CN PCT/CN2023/107133
Examiner
KIM, SISLEY NAHYUN
Art Unit
Tech Center
Assignee
Intel Corporation
OA Round
1 (Non-Final)
89%
Grant Probability
Favorable
1-2
OA Rounds
1m
Est. Remaining
99%
With Interview

Examiner Intelligence

Grants 89% — above average
89%
Career Allowance Rate
614 granted / 693 resolved
+28.6% vs TC avg
Strong +17% interview lift
Without
With
+16.6%
Interview Lift
resolved cases with interview
Typical timeline
2y 7m
Avg Prosecution
24 currently pending
Career history
715
Total Applications
across all art units

Statute-Specific Performance

§101
9.7%
-30.3% vs TC avg
§103
51.1%
+11.1% vs TC avg
§102
24.3%
-15.7% vs TC avg
§112
7.3%
-32.7% vs TC avg
Black line = Tech Center average estimate • Based on career data from 693 resolved cases

Office Action

§102 §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 . Claim Rejections - 35 USC § 102 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 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 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)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale or otherwise available to the public before the effective filing date of the claimed invention. Claims 1, 8, 9, 16, and 17 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Li et al. (US 2022/0188965, hereinafter Li). Regarding claim 1, Li discloses A method for optimizing live migration of a virtual machine (VM) from a source server to a destination server where hardware accelerator virtualization is used (paragraph [0276]: if it is observed that a VF in one GPU always generates an external workload, it may migrate this GPU-intensive VM to a higher performance node or a VF with more GPU resources available), comprising: obtaining hardware accelerator performance data while executing a workload on a virtual function at the source server (paragraph [0228]: severe performance downgrade may be observed in some media-heavy workloads of a media application when it uses GPU media hardware acceleration extensively; paragraph [0276]: the controller 2120 executing the firmware may collect and/or generate statistics associated with workload scheduling); determining whether to transfer the workload from the source server to the destination server based on the hardware accelerator performance data; and transferring the workload from the source server to the destination server based on the determination (paragraph [0276]: if it is observed that a VF in one GPU always generates an external workload, it may migrate this GPU-intensive VM to a higher performance node or a VF with more GPU resources available). Regarding claim 9 referring to claim 1, Li discloses A compute system for optimizing live migration of a virtual machine (VM) to a destination server, comprising: a processor configured to run a VM and perform live migration of the VM from the compute system to the destination server; and a hardware accelerator for exposing a plurality of virtual functions, wherein the processor is configured to … (Fig. 1, paragraph [0276]: if it is observed that a VF in one GPU always generates an external workload, it may migrate this GPU-intensive VM to a higher performance node or a VF with more GPU resources available). Regarding claims 8 and 16, Li discloses wherein the workload is one of a graphics processing unit (GPU) rendering workload, a GPU media workload, a GPU 3D workload, or an artificial intelligence (AI) workload ((paragraph [0231]: 3D workload or media workload)). Regarding claim 17, Li discloses A non-transitory machine-readable medium including code, when executed, to cause a machine to perform the method of claim 1 (paragraph [0333]: non-transitory machine readable media; See the rejection for claim 1). 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 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 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 Claims 2-7, 10, and 11 are rejected under 35 U.S.C. 103 as being unpatentable over Li in view of Chan et al. (US 2014/0136729, hereinafter Chen). Regarding claims 2 and 10, Li does not disclose wherein the hardware accelerator performance data includes an amount of output data the workload generates and an amount of input data to the workload. Chen discloses wherein the hardware accelerator performance data includes an amount of output data the workload generates and an amount of input data to the workload (paragraph [0047]: FIG. 7 illustrates an example of a process 700 for migrating computer applications from a computing device to a server. The process 700 starts at step 705, where a computing device identifies a service component of a computer application executing at the computing device … The service component can be designed to handle computing tasks, e.g., a CPU intensive task, a GPU intensive task, a memory intensive task, a power intensive task, or a data input/output intensive task; [0048] At step 710, the computing device determines whether a workload of the computing device can be reduced if the service component is migrated to a server; [0049] At step 710, the computing device stops executing the service component at the computing device. Then at step 720, the computing device transfers to the server an instance of the service component; paragraph [0054]: The optimization factor may depend on, e.g., a CPU resource, a GPU resource, a memory resource, a power level, a data input/output amount, or a completion time needed for the instance of the background component to continue executing at the server; paragraph [0055]: If the optimization factor is less than the predetermined value, at step 775, the computing device may retrieve, from the server, data generated by the instance of the service component executed at the server before the instance of the server component is stopped. At step 780, the computing device sends to the server an instruction to stop executing the instance of the service component at the server. At step 785, the computing device may choose to execute the service component of the computer application at the computing device). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Li’s migration-based workload optimization to also consider Chen’s data input/output amount or I/O-intensive workload condition, because both references address workload migration in response to resource or performance constraints. The motivation would have been to improve overall performance of the device (Chan paragraph [0005]). Regarding claims 3 and 11, Li discloses wherein the hardware accelerator is a graphics processing unit (GPU), the workload is a GPU workload, and the hardware accelerator performance data is GPU performance data (paragraph [0228]: severe performance downgrade may be observed in some media-heavy workloads of a media application when it uses GPU media hardware acceleration extensively; paragraph [0276]: the controller 2120 executing the firmware may collect and/or generate statistics associated with workload scheduling). Regarding claim 4, Li discloses wherein the GPU performance data is obtained by inserting, by an input/output (IO) mediator in the source server, a GPU performance command when submitting the GPU workload to a GPU virtual function (Note: the broadest reasonable interpretation of a method (or process) claim having contingent limitations requires only those steps that must be performed and does not include steps that are not required to be performed because the condition(s) precedent are not met (MPEP 2111.04 II Contingent Limitations). Accordingly, patentable weight is not given because the step is not performed if the disclosed condition is not met). Regarding claim 5, Li discloses wherein if it is determined that a ratio of the amount of output data the GPU workload generates to the amount of input data to the GPU workload does not exceed a threshold, output data generated by the GPU workload and marked as dirty page is transferred to the destination server (Note: the broadest reasonable interpretation of a method (or process) claim having contingent limitations requires only those steps that must be performed and does not include steps that are not required to be performed because the condition(s) precedent are not met (MPEP 2111.04 II Contingent Limitations). Accordingly, patentable weight is not given because the step is not performed if the disclosed condition is not met). Regarding claim 6, Li discloses wherein if it is determined that a ratio of the amount of output data the GPU workload generates to the amount of input data to the GPU workload exceeds a threshold, an input/output (IO) mediator in the source server transfers the GPU workload to the destination server (Note: the broadest reasonable interpretation of a method (or process) claim having contingent limitations requires only those steps that must be performed and does not include steps that are not required to be performed because the condition(s) precedent are not met (MPEP 2111.04 II Contingent Limitations). Accordingly, patentable weight is not given because the step is not performed if the disclosed condition is not met). Regarding claim 7, Li discloses wherein the IO mediator in the source server packs the GPU workload and streams the GPU workload within a live migration bitstream to the destination server (Note: the broadest reasonable interpretation of a method (or process) claim having contingent limitations requires only those steps that must be performed and does not include steps that are not required to be performed because the condition(s) precedent are not met (MPEP 2111.04 II Contingent Limitations). Accordingly, patentable weight is not given because the step disclosed in parent claim 6 is not performed if the disclosed condition is not met). Allowable Subject Matter Claims 12-15 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims. Conclusion The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure. Jiang et al. (US 2020/0192691) discloses “The API generates a list of pages modified by the first GPU running in the source guest VM (referred to as “dirty” pages) based on the page table maintained by the first GPU and provides the list of pages to the hypervisor. The hypervisor copies the dirty pages and transfers the dirty pages to the destination guest VM. After transferring the dirty pages to the destination guest VM, the hypervisor stops the source guest VM and identifies any additional frame buffer pages and system memory that were modified by the first GPU at the source guest VM during the time between first time copying the dirty pages and stopping the source guest VM” (paragraph [0011]). Salsburg et al. (US 2012/0317249) discloses” the medium server POD is optimized for a web-tier environment with moderate-to-heavy network activity, where the I/O ratio is estimated to be around 65 percent network and 35 percent storage traffic. The large server and storage PODs are optimized for database usage with moderate-to-heavy storage activity, where the I/O ratio is estimated to be around 65 percent storage and 35 percent network traffic. The large number of network ports in each configuration (56 total) allows for virtualization hypervisors such as VMware with vMotion to use two ports for operating system and VM migration--leaving two ports per blade available for the customer network” (paragraph [0089]). Any inquiry concerning this communication or earlier communications from the examiner should be directed to SISLEY N. KIM whose telephone number is (571)270-7832. The examiner can normally be reached M-F 11:30AM -7:30PM. 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, April Y. Blair can be reached on (571)270-1014. 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. /SISLEY N KIM/Primary Examiner, Art Unit 2196 8/23/2026
Read full office action

Prosecution Timeline

Mar 27, 2024
Application Filed
Apr 25, 2024
Response after Non-Final Action
Aug 26, 2026
Non-Final Rejection mailed — §102, §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

1-2
Expected OA Rounds
89%
Grant Probability
99%
With Interview (+16.6%)
2y 7m (~1m remaining)
Median Time to Grant
Low
PTA Risk
Based on 693 resolved cases by this examiner. Grant probability derived from career allowance rate.

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