DETAILED ACTION
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.
Claims 1-20 are presented for the examination.
The cross reference related to the application cited in the specification must be updated (i.e. update the relevant status, with PTO serial numbers or patent numbers where appropriate, on para[0001], ln 1-7). The entire specification should be so revised.
Double Patenting
3. 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. See 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);and, 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) may be used to overcome an actual or provisional rejection based on a nonstatutory double patenting ground provided the conflicting application or patent is shown to be commonly owned with this application. See 37 CFR 1.130(b).
Effective January 1, 1994, a registered attorney or agent of record may sign a terminal disclaimer. A terminal disclaimer signed by the assignee must fully comply with 37 CFR 3.73(b).
Claims 1-20 are rejected under the judicially created doctrine of obviousness-type double patenting as being unpatentable over claims 1-21 of US Patent No. 12/057,430.
US Patent 12/057,430 teaches obtaining, with a management server of a software-defined data center (SDDC)(obtaining resource usage samples provided by the host), triggering an event( triggering an event), the determination that the SDDC is idle is based at least in part on a determination that all of the hosts of the plurality of hosts are idle( determining that the host is idle; determining that the SDDC is idle, in response to determination that all of the hosts of the plurality of hosts are idle ), the determination that a respective host of the plurality of hosts is idle is based at least in part on an idleness score assigned to the respective host( and determining the idleness score of the host from a smallest of either the first idleness score or the second idleness score); and the idleness score assigned to the respective host is based at least in part on at least some of the resource usage samples and a coefficient of variation (CV) associated with the resource usage samples( determining a coefficient of variation (CV) associated with fluctuations of the resource usage samples; determining an idleness score of the host based at least in part on the usage samples and the CV) and performing, based at least in part on the triggered event, a remediation action for the idle SDDC( triggering an event to perform a remediation action for the idle SDDC);
Although the conflicting claims are not identical, they are not patentably distinct from each other because both computer systems comprise substantially the same elements. The difference between claims 1, 8, 15 of the copending application and this case are resource usage samples provided by each host of a plurality of hosts in the SDDC, wherein each host of the plurality of hosts is a respective physical machine that executes virtualization software supporting one or more virtualized computing instances running on the respective physical machine a multiple filters defining a filter graph. It would have been obvious to one of the ordinary skill level in the art to include above feature because this monitors or controllers designates a processor for deactivation and routes new requests away from the designated processor, but allows the processor to continue handling current requests.
§ 101 2. 35 U.S.C. 101 reads as follows
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1, 8, 15 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
As to Claims 1, 8, 15 have been rejected under 35 USC 101 for abstract idea without significantly more. Under Step 2A, Prong 1, the “ determination that the SDDC is idle, an event, wherein: the determination that the SDDC is idle is based at least in part on a determination that all of the hosts of the plurality of hosts are idle; the determination that a respective host of the plurality of hosts ” recite a mental process since “determining” is functions that can be reasonably performed in the human mind with the aid of pen and paper through observation, evaluation, judgment, opinion.
Under Prong 2, the additional element “ obtaining, with a management server of a software-defined data center (SDDC), resource usage samples provided by each host of a plurality of hosts in the SDDC, wherein each host of the plurality of hosts is a respective physical machine that executes virtualization software supporting one or more virtualized computing instances running on the respective physical machine; triggering, by the management server and based on a determination that the SDDC is idle, an event, the idleness score assigned to the respective host is based at least in part on at least some of the resource usage samples and a coefficient of variation (CV) associated with the resource usage samples; and performing, based at least in part on the triggered event, a remediation action for the idle SDDC” are recited at a high-level of generality such that it amounts no more than mere instructions to apply the exception using a generic computer component, or merely a generic computer or generic computer components to perform the judicial exception, Accordingly, the additional elements do not integrate the recited judicial exception into a practical application, and the claim is therefore directed to the judicial exception. See MPEP 2106.05(f).
Under Step 2B, the additional elements “ obtaining, with a management server of a software-defined data center (SDDC), resource usage samples provided by each host of a plurality of hosts in the SDDC, wherein each host of the plurality of hosts is a respective physical machine that executes virtualization software supporting one or more virtualized computing instances running on the respective physical machine; triggering, by the management server and based on a determination that the SDDC is idle, an event ” - this generally have been a mental process although the software-defined data center could be a generic computer component if the spec describes it as actual computer software in computer hardware. “ the idleness score assigned to the respective host is based at least in part on at least some of the resource usage samples and a coefficient of variation (CV) associated with the resource usage samples; and performing, based at least in part on the triggered event, a remediation action for the idle SDDC ” - this is mere instructions to apply the mental process under mpep 2106.05(f), amounts to merely generally linking the use of the judicial exception to a particular technological environment or field or use, and is merely applying the judicial exception, therefore, does not amount to significantly more, hence, cannot provide an inventive concept.
7. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application. See MPEP 2106.05(d). Thus, the claim is not patent eligible.
Claim Objections
8. Claims 1, 8, 15 are objected to because of the following informalities: There is a type error on the word “ leat”. Appropriate correction is required.
Claim Rejections - 35 USC § 103
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.
9. Claim(s) 1, 5, 6, 8, 12, 13, 15 are rejected under 35 U.S.C. 103 as being unpatentable over Wolski( US 20140189410 A1) in view of Pramod( EP 3118781 A1) in view of LEI(CN 113886086 A) and further in view of Hwang(US 20180288143 A1).
As to claim 1, Wolski teaches obtaining, with a management server of a software-defined data center (SDDC), resource usage samples provided by each host of a plurality of hosts in the SDDC( Examples of computing centers include data centers or data warehouses, computer clusters, and server farms. As illustrated in FIG. 1, the computing center 120 is a server farm operating physical servers 130 hosting virtual servers 150, para[0019], ln 2-7/ The controller may be a physical server 130 in the computing center 120, para[0021], ln 7-11/ the controller 140 finds the difference (x) of the largest number of busy machines at any time in each epoch minus the number (b) of physical servers 130 that were busy at the beginning of the respective epoch. That is, the controller 140 identifies the peak usage level in each epoch and determines a delta between the initial usage at the start of each epoch and the peak usage for the epoch, para[0044], ln 1-10/ At step 610, a monitoring system (e.g., controller 140 may act in a monitoring capacity), monitors usage of one or more processors in a multi-processor computing environment over a plurality of periodic intervals, wherein each periodic interval has a number of active-busy processors and a number of active-idle processors. At step 620, the monitoring system determines, for each periodic interval, a delta value representing a change in the number of active-busy processors during the respective interval. At step 630, the monitoring system maintains a sorted list of processor usage changes, para[0050], ln 2-12/ one or more of the servers (e.g., the physical servers 130, the controller 140, and/or the remote servers 160) illustrated in FIG. 1 are constructed to be similar to the computer system 200 of FIG. 2. , par[0027], ln 1-5/ FIG. 2 illustrates an example computer system 200 suitable for use in implementing the computerized components described herein. The example computer system 200 includes one or more processors 250, para[0025], ln 1-5);
wherein each host of the plurality of hosts is a respective physical machine that executes virtualization software supporting one or more virtualized computing instances running on the respective physical machine( The computing center 120 provides access to physical servers 130 (e.g., physical servers 130a-n). A controller 140 determines which physical servers 130 are active. The physical servers 130 host virtual servers 150 (e.g., virtual servers 150a-n), para[0016], ln 2-10/ web site on a virtual server 150 hosted by a physical server 130 in the computing center 120 and an access device 170 may fetch a web page from the web site, para[0018], ln 7-10);
the determination that a respective host of the plurality of hosts is idle is based at least in part on an idleness score ( At step 650, the monitoring system causes a number of processors to transition between a non-active state and an idle active state, wherein the number of processors transitioned is based on the predicted delta value. If the predicted delta indicates that additional processors will be needed during the next periodic interval, then additional processors are activated; if the predicted delta indicates that fewer processors will be needed, then some active-idle processors are de-activated, para[0055], ln 1-10/ one or more of the servers (e.g., the physical servers 130, the controller 140, and/or the remote servers 160) illustrated in FIG. 1 are constructed to be similar to the computer system 200 of FIG. 2. , par[0027], ln 1-5/ FIG. 2 illustrates an example computer system 200 suitable for use in implementing the computerized components described herein. The example computer system 200 includes one or more processors 250, para[0025], ln 1-5) .
Pramod teaches the determination that the SDDC is idle is based at least in part on a determination that all of the hosts of the plurality of hosts are idle, the determination that a respective host of the plurality of hosts is idle is based at least in part on an idleness score assigned to the respective host (Fig. 1 illustrates an exemplary environment for decommissioning a production computer system; Fig. 2 illustrates various exemplary operations that may be performed by the decommissioning system in determining whether an application operating on a server should be decommissioned, Sec: Fig: 1/the term "decommissioning" generally means deactivating an application on a computing infrastructure in a data center and possibly moving the application to a cloud system as one of the possible enhancement models. When[determine] all the applications at a given data, center are deactivated[idle] at a given data center, the datacenter itself may be deactivated[idle] (i.e., computers sold, etc.). Thus "decommissioning" may also refer to the deactivating of the entire data center, Sec: As used herein, ln 1-15/defines a business value associated with the target application, wherein if the business value is below a threshold and if the target application is determined to not be suitable for migration to the cloud computing system, indicating on the report that the application should be decommissioned, Sec: The method according to claim 1 low business values cause application is idled; therefore, low business value is idleness score / decommissioning system may be configured to send notifications (i.e., emails, text messages, etc.) to stakeholders pertaining to various stages of the decommissioning[idleness score] and cloud migration process, such as "Being Assessed", "Ready to Deploy", "Deployed,[ [idleness score] " etc. The notifications could also provide other status updates, escalations, alerts, approval notices, reverse sign off mailers etc.], Sec: Other modification, ln 1-10/ A status of "Deployed"[ idleness score ] may indicate that the application has been decommissioned[idle] on the named server and moved to the cloud computing system 115. While not illustrated, the status indicator may also indicate "Ready to Deploy" or something similar to indicate that the cloud computing system 115 is ready to receive the application to be deployed. The status indicator[ idleness score ]may also indicate "Decommissioned" or something similar to indicate that the application has been decommissioned, Sec: Fig. 6 illustrates a screen shot 600, ln 5-16/ determining that the SDDC is idle, in response to determination that all of the hosts of the plurality of hosts are idle because when all the applications in the data center are deactivate, the data center is deactivated as described above ).
It would have been obvious to one of the ordinary skill in the art before the effective claimed invention was made to modify the above teaching to incorporate the feature of based at least in part on the idleness score, determining that the host is idle; determining that the SDDC is idle, in response to determination that all of the hosts of the plurality of hosts are idle because this technical solutions are needed for mitigating the risks and overcome the challenges that are encountered during the decommissioning process.
LEI teaches a coefficient of variation (CV) associated with the resource usage samples( respectively the product of each recommended reference value of each host, and accumulating the product of all the main machine as the recommendation coefficient, Sec: Contents of the Invention, ln 11-16) ;
determining an idleness score of the host based at least in part on the usage samples and the CV( according to the product of the recommendation coefficient and each recommendation reference value of the host, calculating the host idle degree value, sec: Contents of the Invention, ln 14-20).
It would have been obvious to one of the ordinary skill in the art before the effective claimed invention was made to modify the above teaching to incorporate the above feature because this enables the cloud platform to rationally allocate resources when planning multiple users to create virtual machine, so as to improve the efficiency of the system.
Hwang teaches triggering, by the management server and based on a determination that the SDDC is idle, an event, and performing, based at least in part on the triggered event, a remediation action for the idle SDDC triggering an event to perform a remediation action for the idle SDDC which is idled in part on the idleness score(managing idle and active servers in cloud data centers, para[004], ln 1-6/ The action plan generator 310 develops 414 treatment options for idle servers, and the cloud data center manager 312 implements 416 the treatment options. In certain implementations, the treatment options comprise terminating, terminating with snapshot, and stopping a virtual machine, para[0067], ln 8-20/analyzer 308 will detect 406 target servers as idle if they satisfy conditionally the following rules: No recent user login activities: if the target server has no user login activity over last three months, then the server will be detected as an idle server.No recent established network connections: if the target server has not established any network connections over the last month, then the server will be detected as an idle server, para[0051] to para[0053] ).
It would have been obvious to one of the ordinary skill in the art before the effective claimed invention was made to modify the above teaching to incorporate the feature of triggering an event to perform a remediation action for the idle SDDC because this Reduces management/operational costs in cloud data centers.
As to claim 5, Wolski teaches the management server is a physical computer( para[0027], ln 1-3/ para[0021], ln 5-11).
As to claim 6, Wolski teaches the management server is a network device( para[0021], ln 7-20).
As to claims 8, 12, 13, 15, 19, 20, they are rejected for the same reasons as to claims 1, 5, 6 above.
Claims 2, 9, 16 are rejected under 35 U.S.C. 103 as being unpatentable over LEI(CN 113886086 A) in view of Pramod( EP 3118781 A1) in view of Hwang(US 20180288143 A1) in view of Ignatowsk(US 20050122987 A1) and further in view of Faye(US 11246071 B2).
As to claim 2, Faye teaches the idleness score for each respective host is based on a filtered set of the resource usage samples; and the filtered set of resource usage samples does not include outlier resource usage samples associated with a management overhead. ( According to one embodiment of the invention, the weighting coefficients “coef1” and “coef2” may be predetermined. According to another embodiment of the invention, the weighting coefficients “coef1” and “coef2” are determined by the formulae: (1) if the connection is active, that is to say the client node is exchanging data with the gathering node, then the quality data “airTimeUsage” is positive, and:Coef1=Coef2=PhyRate Threshold/RSSIThreshold, with: “PhyRate Threshold”: predetermined value of the low-level transmission rate of the connection, typically chosen in the range [26; 52], “RSSIThreshold”: predetermined value of the reception power of a radio signal sent by the client node and received by the first gathering node, typically chosen in the range [−80; −65]. (2) if the connection is inactive, that is to say if the client node is not exchanging data with the gathering node (in other words, the client node is “asleep”), then the quality data “airTimeUsage” is zero and: Coef1=1/RSSIThreshold, and Coef2=0, col 6, ln 15-40).
It would have been obvious to one of the ordinary skill in the art before the effective claimed invention was made to modify the above teaching to incorporate the feature of filtering outlier samples associated with a management overhead, prior to determining the idleness score of the hosts because this seeks to establish a wireless connection with a gathering node among the plurality of gathering nodes available, the gathering node corresponds to the gathering node the radio signal of which is received with the greatest power by the client node.
As to claims 9, 16, they are rejected for the same reason as to claim 9 above.
Claim(s) 3, 10, 17 are rejected under 35 U.S.C. 103 as being unpatentable over Wolski( US 20140189410 A1) in view of Pramod( EP 3118781 A1) in view of LEI(CN 113886086 A) and further in view of Hwang(US 20180288143 A1) and further in view of Chopra( US 9977704 B1).
As to claim 3, Chopra teaches the virtualization software executed by at least one of the plurality of hosts is a hypervisor; and at least one of the virtualized computing instances running on the at least one of the plurality of hosts is a virtual machine (VM)( . SDDCs are virtual datacenters (vCenters) that may include hundreds to thousands of virtual machines, col 1, ln 31-35/ virtual machine environments utilize hypervisors to create and run the virtual machines. A computer running the hypervisor is a host machine and all virtual machines are guest machines running guest operating systems (OS), col 8, ln 9-15).
It would have been obvious to one of the ordinary skill in the art before the effective claimed invention was made to modify the above teaching to incorporate the feature of filtering outlier samples associated with a management overhead, prior to determining the idleness score of the hosts because this backs up virtual datacenters in a dynamic process that optimizes storage and resource usage, and that backs up data based on user customized criteria as opposed to a hardcoded schedule.
As to claims 10, 17, they are rejected for the same reason as to claim 3 above.
Claim(s) 4, 11, 18 are rejected under 35 U.S.C. 103 as being unpatentable over Wolski( US 20140189410 A1) in view of Pramod( EP 3118781 A1) in view of LEI(CN 113886086 A) in view of Hwang(US 20180288143 A1) in view of Chopra( US 9977704 B1) and further in view of Zhang(US 20180262431 A1)
As to claim 4, Wolski teaches VM comprising the management server Para[0021], ln 5-9/ para[0021], ln 1-2).
Zhang teaches VM is a single-purpose VM( Emerging network applications, such as cloud and big data applications, may involve joint consideration of IT resources residing within multiple domains within one or more data centers (DCs). Network function virtualization (NFV) can be used to virtualize network functions and migrate them from devices that are built for a single, specific purpose to multi-purpose virtual machines, para[0003], ln 1-10).
It would have been obvious to one of the ordinary skill in the art before the effective claimed invention was made to modify the above teaching to incorporate the feature of triggering an event to perform a remediation action for the idle SDDC because this reduces service deployment costs and improve service flexibility.
As to claims 11, 18, they are rejected for the same reason as to claim 4 above.
Allowable Subject Matter
Claims are 7, 14 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
US 20140189410 A1 teaches computing center provides access to a plurality of physical computing machines. Examples of computing centers include data centers or data warehouses, computer clusters, and server farms. Generally, a computing center is designed for a varying level of use such that the typical use is within the computing capacity of the center. When usage is below capacity, idle machines can be operated at a,.
US 20200225856 A1 teaches In some implementations, the machine-learned model may be configured to update the final counter values of each of the groups by a coefficient value. In some implementations, the machine learned model may be configured to track idle times across multiple days, days of a week (e.g., weekdays, weekends).
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/LECHI TRUONG/Primary Examiner, Art Unit 2194
Prosecution Insights