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 § 101
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 1-20 are rejected under 35 USC 101 because the claimed invention is directed to a judicial exception (i.e. abstract idea) without anything significantly more.
Step 1: Claims 1-12 are directed to a system, claims 13-19 are directed to a device, and claim 20 is directed to a method. Therefore, the claims are directed to patent eligible categories of invention.
Step 2A, Prong 1: Independent claims 1, 13, and 20 are related to making determinations based upon energy, constituting an abstract idea based on “Mental Processes” related to concepts performed in the human mind including observation, evaluation, judgment, and opinion. Claim 1 recites limitations including “wherein the one or more files are selected or assembled based upon a workspace definition created, at least in part, based upon an energy score.” Claim 13 recites limitations including “create a workspace definition based, at least in part, upon an energy target.” Claim 20 recites limitations including “creating a workspace definition based upon at least one of: a security target, a productivity target, or an energy target.” These limitations, as drafted, but for the recitation of processor and memory, is a process that covers performance of the limitations in the mind but for the recitation of generic computer components. That is, but for the processor and memory language, nothing in the claim elements preclude the steps from practically being performed in the human mind. For example, with the exception of the processor and memory language, the claim steps in the context of the claim encompass a user mentally or manually performing the steps of the claim.
Dependent claims 2-6, 8-9, and 15-16 further narrow the abstract idea identified in the independent claims and do not introduce further additional elements for consideration.
Dependent claims 7, 10-12, 14, and 17-19 will be evaluated under Step 2A, Prong 2 below.
Step 2A, Prong 2: Independent claims 1, 13, and 20 do not integrate the judicial exception into a practical application. Claim 1 recites the additional elements of “a processor; and a memory coupled to the processor, the memory having program instructions stored thereon that, upon execution by the processor, cause the IHS to,” “receive, at a local management agent from a workspace orchestration service, one or more files configured to enable the local management agent to instantiate a workspace,” and “instantiate the workspace.” Claim 13 recites the additional elements of “transmit, to a client IHS, one or more files configured to enable the client IHS to instantiate a workspace based upon the workspace definition.” Claim 20 recites the additional elements of “transmitting, to a local management agent of a client Information Handling System (IHS), one or more files or policies configured to enable the local management agent to instantiate a workspace based upon the workspace definition.” These additional elements are mere instructions to implement an abstract idea using a computer in its ordinary capacity, or merely uses the computer as a tool to perform the identified abstract idea. Use of a computer or other machinery in its ordinary capacity for tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., mental processes) does not integrate a judicial exception into a practical application. See MPEP 2106.05(f).
Therefore, the additional elements of the independent claims, when considered both individually and in combination, are not sufficient to prove integration into a practical application.
Dependent claims 2-6, 8-9, and 15-16 further narrow the abstract idea identified in the independent claims and do not introduce further additional elements for consideration, which does not integrate the judicial exception into a practical application.
Dependent claim 7 introduces the additional element of “wherein the one or more files are configured to enforce, based upon the energy score, at least one of: a reduction of energy consumption by the IHS, a load balancing or peak shifting operation, or a battery charging rate.” This limitation does not integrate the judicial exception into a practical application because the claim merely adds the words “apply it” (or an equivalent) with the judicial exception. Use of a computer or other machinery in its ordinary capacity for performing the steps of the abstract idea or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., mental process or certain methods of organizing human activity) does not integrate a judicial exception into a practical application. See MPEP 2106.05(f).
Dependent claim 10 introduces the additional element of “receive, at the local management agent from the workspace orchestration service, a second one or more files configured to enable the local management agent to instantiate a second workspace, at least in part, in response to a change in the energy score; and instantiate the second workspace.” This limitation does not integrate the judicial exception into a practical application because the claim merely adds the words “apply it” (or an equivalent) with the judicial exception. Use of a computer or other machinery in its ordinary capacity for performing the steps of the abstract idea or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., mental process or certain methods of organizing human activity) does not integrate a judicial exception into a practical application. See MPEP 2106.05(f).
Dependent claim 11 introduces the additional element of “wherein in response to a changed energy score being worse than a previous energy score, the second one or more files replace a local component of the workspace with a remote component in the second workspace.” This limitation does not integrate the judicial exception into a practical application because the claim merely adds the words “apply it” (or an equivalent) with the judicial exception. Use of a computer or other machinery in its ordinary capacity for performing the steps of the abstract idea or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., mental process or certain methods of organizing human activity) does not integrate a judicial exception into a practical application. See MPEP 2106.05(f).
Dependent claim 12 introduces the additional element of “wherein in response to the changed energy score being better than a previous energy score, the second one or more files replace a remote component of the workspace with a local component in the second workspace.” This limitation does not integrate the judicial exception into a practical application because the claim merely adds the words “apply it” (or an equivalent) with the judicial exception. Use of a computer or other machinery in its ordinary capacity for performing the steps of the abstract idea or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., mental process or certain methods of organizing human activity) does not integrate a judicial exception into a practical application. See MPEP 2106.05(f).
Dependent claim 14 introduces the additional element of “transmit, to the client IHS, one or more other files configured to enable the client IHS to instantiate a modified workspace based upon the modified workspace definition.” This limitation does not integrate the judicial exception into a practical application because the claim merely adds the words “apply it” (or an equivalent) with the judicial exception. Use of a computer or other machinery in its ordinary capacity for performing the steps of the abstract idea or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., mental process or certain methods of organizing human activity) does not integrate a judicial exception into a practical application. See MPEP 2106.05(f).
Dependent claim 17 introduces the additional element of “wherein the modified workspace definition re-instantiates or migrates a local component of the workspace for execution by a remote IHS in the modified workspace.” This limitation does not integrate the judicial exception into a practical application because the claim merely adds the words “apply it” (or an equivalent) with the judicial exception. Use of a computer or other machinery in its ordinary capacity for performing the steps of the abstract idea or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., mental process or certain methods of organizing human activity) does not integrate a judicial exception into a practical application. See MPEP 2106.05(f).
Dependent claim 18 introduces the additional element of “wherein the modified workspace definition re-instantiates or migrates a remote component of the workspace for execution by the client IHS in the modified workspace.” This limitation does not integrate the judicial exception into a practical application because the claim merely adds the words “apply it” (or an equivalent) with the judicial exception. Use of a computer or other machinery in its ordinary capacity for performing the steps of the abstract idea or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., mental process or certain methods of organizing human activity) does not integrate a judicial exception into a practical application. See MPEP 2106.05(f).
Dependent claim 19 introduces the additional element of “wherein the modified workspace definition migrates a remote component of the workspace from a first remote IHS to a second remote IHS in the modified workspace.” This limitation does not integrate the judicial exception into a practical application because the claim merely adds the words “apply it” (or an equivalent) with the judicial exception. Use of a computer or other machinery in its ordinary capacity for performing the steps of the abstract idea or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., mental process or certain methods of organizing human activity) does not integrate a judicial exception into a practical application. See MPEP 2106.05(f).
Therefore, the additional elements of the dependent claims, when considered both individually and in combination with the independent claims above, are not sufficient to prove integration into a practical application.
Step 2B: Independent claims 1, 13, and 20 do not comprise anything significantly more than the judicial exception. Claim 1 recites the additional elements of “a processor; and a memory coupled to the processor, the memory having program instructions stored thereon that, upon execution by the processor, cause the IHS to,” “receive, at a local management agent from a workspace orchestration service, one or more files configured to enable the local management agent to instantiate a workspace,” and “instantiate the workspace.” Claim 13 recites the additional elements of “transmit, to a client IHS, one or more files configured to enable the client IHS to instantiate a workspace based upon the workspace definition.” Claim 20 recites the additional elements of “transmitting, to a local management agent of a client Information Handling System (IHS), one or more files or policies configured to enable the local management agent to instantiate a workspace based upon the workspace definition.” These additional elements are mere instructions to implement an abstract idea using a computer in its ordinary capacity, or merely uses the computer as a tool to perform the identified abstract idea. Use of a computer or other machinery in its ordinary capacity for tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., mental processes) is not anything significantly more than the judicial exception. See MPEP 2106.05(f).
Therefore, the additional elements of the independent claims, when considered both individually and in combination, are not anything significantly more than the judicial exception.
Dependent claims 2-6, 8-9, and 15-16 further narrow the abstract idea identified in the independent claims and do not introduce further additional elements for consideration, which is not anything significantly more than the judicial exception.
Dependent claim 7 introduces the additional element of “wherein the one or more files are configured to enforce, based upon the energy score, at least one of: a reduction of energy consumption by the IHS, a load balancing or peak shifting operation, or a battery charging rate.” This limitation is not anything significantly more than the judicial exception because the claim merely adds the words “apply it” (or an equivalent) with the judicial exception. Use of a computer or other machinery in its ordinary capacity for performing the steps of the abstract idea or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., mental process or certain methods of organizing human activity) is not anything significantly more than the judicial exception. See MPEP 2106.05(f).
Dependent claim 10 introduces the additional element of “receive, at the local management agent from the workspace orchestration service, a second one or more files configured to enable the local management agent to instantiate a second workspace, at least in part, in response to a change in the energy score; and instantiate the second workspace.” This limitation is not anything significantly more than the judicial exception because the claim merely adds the words “apply it” (or an equivalent) with the judicial exception. Use of a computer or other machinery in its ordinary capacity for performing the steps of the abstract idea or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., mental process or certain methods of organizing human activity) is not anything significantly more than the judicial exception. See MPEP 2106.05(f).
Dependent claim 11 introduces the additional element of “wherein in response to a changed energy score being worse than a previous energy score, the second one or more files replace a local component of the workspace with a remote component in the second workspace.” This limitation is not anything significantly more than the judicial exception because the claim merely adds the words “apply it” (or an equivalent) with the judicial exception. Use of a computer or other machinery in its ordinary capacity for performing the steps of the abstract idea or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., mental process or certain methods of organizing human activity) is not anything significantly more than the judicial exception. See MPEP 2106.05(f).
Dependent claim 12 introduces the additional element of “wherein in response to the changed energy score being better than a previous energy score, the second one or more files replace a remote component of the workspace with a local component in the second workspace.” This limitation is not anything significantly more than the judicial exception because the claim merely adds the words “apply it” (or an equivalent) with the judicial exception. Use of a computer or other machinery in its ordinary capacity for performing the steps of the abstract idea or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., mental process or certain methods of organizing human activity) is not anything significantly more than the judicial exception. See MPEP 2106.05(f).
Dependent claim 14 introduces the additional element of “transmit, to the client IHS, one or more other files configured to enable the client IHS to instantiate a modified workspace based upon the modified workspace definition.” This limitation is not anything significantly more than the judicial exception because the claim merely adds the words “apply it” (or an equivalent) with the judicial exception. Use of a computer or other machinery in its ordinary capacity for performing the steps of the abstract idea or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., mental process or certain methods of organizing human activity) is not anything significantly more than the judicial exception. See MPEP 2106.05(f).
Dependent claim 17 introduces the additional element of “wherein the modified workspace definition re-instantiates or migrates a local component of the workspace for execution by a remote IHS in the modified workspace.” This limitation is not anything significantly more than the judicial exception because the claim merely adds the words “apply it” (or an equivalent) with the judicial exception. Use of a computer or other machinery in its ordinary capacity for performing the steps of the abstract idea or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., mental process or certain methods of organizing human activity) is not anything significantly more than the judicial exception. See MPEP 2106.05(f).
Dependent claim 18 introduces the additional element of “wherein the modified workspace definition re-instantiates or migrates a remote component of the workspace for execution by the client IHS in the modified workspace.” This limitation is not anything significantly more than the judicial exception because the claim merely adds the words “apply it” (or an equivalent) with the judicial exception. Use of a computer or other machinery in its ordinary capacity for performing the steps of the abstract idea or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., mental process or certain methods of organizing human activity) is not anything significantly more than the judicial exception. See MPEP 2106.05(f).
Dependent claim 19 introduces the additional element of “wherein the modified workspace definition migrates a remote component of the workspace from a first remote IHS to a second remote IHS in the modified workspace.” This limitation is not anything significantly more than the judicial exception because the claim merely adds the words “apply it” (or an equivalent) with the judicial exception. Use of a computer or other machinery in its ordinary capacity for performing the steps of the abstract idea or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., mental process or certain methods of organizing human activity) is not anything significantly more than the judicial exception. See MPEP 2106.05(f).
Therefore, the additional elements of the dependent claims, when considered both individually and in combination with the independent claims above, are not anything significantly more than the judicial exception.
Accordingly, claims 1-20 are rejected under 35 USC 101.
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 (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 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.
Claim(s) 1-4, 7, 10, 13, and 20 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Athavale (US 20250216921 A1).
Regarding claim 1, Athavale anticipates an Information Handling System (IHS) (Figs. 1-2 teach a user device), comprising:
a processor (Fig. 2 and [0029] teach a user device and a system that reduces or mitigates the energy footprint of a particular application executing on the user device, wherein Fig. 1 and [0013-0014] teach the user device comprises a CPU and GPU); and
a memory coupled to the processor, the memory having program instructions stored thereon that (Fig. 2 and [0029] teach a user device and a system that reduces or mitigates the energy footprint of a particular application executing on the user device, wherein Fig. 1 and [0013-0014] teach the user device comprises a CPU and memory, wherein [0119] teaches a computer-readable storage media encoding instructions for executing a computer process on a user device), upon execution by the processor, cause the IHS to:
receive, at a local management agent from a workspace orchestration service (Figs. 2, 4 and [0100] teach the applications may receive input from one or more remote devices, such as remotely located servers or smart devices, by communicating with the devices over a wireless network using communication transceivers, wherein the energy savings discovery engine of Fig. 2 is an application executing on the processing device or as a distributed application with different components executing on many different devices, as well as in [0024] teaches the energy consumption metrics can be transmitted to the energy savings discovery engine; see also: [0013-0014, 0029, 0099]), one or more files configured to enable the local management agent to instantiate a workspace (Fig. 1 and [0028] teaches energy savings discovery engine generates an energy saving reconfiguration recommendation that recommends the user device to be re-configured to match the configuration, wherein if the user device, for example, utilizes a specific type of windows, the energy savings reconfiguration recommendation suggests that the user upgrade the operating system to reduce energy consumption, wherein the recommendation is transmitted to the user device and presented on the display, wherein [0017] teaches the locally installed software and user-configurable settings on the user device are configurable contributors that are device features that are configurable e.g. changeable by altering device settings or by installing/removing software, and that contribute to the energy footprint of the application, wherein [0084-0089] teach given the example energy footprints, the energy savings computation and recommendation engine determines that the device configuration presents an estimated energy savings including CPU carbon savings, GPU carbon savings, memory carbon savings, net carbon savings, and more, wherein based on this, the energy savings computation and recommendation engine generates a reconfiguration recommendation that says reduce the carbon footprint of App A, wherein [0095] teaches the energy savings reconfiguration recommendation may be transmitted to the user device and the user device automatically reconfigures the user device in accord with the recommendation, wherein the user device is configured to automatically install updates and/or software products determined to reduce energy consumption of the devices; see also: [0011, 0034], Figs. 2-4),
wherein the one or more files are selected or assembled based upon a workspace definition created, at least in part, based upon an energy score (Fig. 1 and [0028] teaches energy savings discovery engine generates an energy saving reconfiguration recommendation that recommends the user device to be re-configured to match the configuration, wherein if the user device, for example, utilizes a specific type of windows, the energy savings reconfiguration recommendation suggests that the user upgrade the operating system to reduce energy consumption, wherein the recommendation is transmitted to the user device and presented on the display, wherein [0017] teaches the locally installed software and user-configurable settings on the user device are configurable contributors that are device features that are configurable e.g. changeable by altering device settings or by installing/removing software, and that contribute to the energy footprint of the application, wherein [0084-0089] teach given the example energy footprints, the energy savings computation and recommendation engine determines that the device configuration presents an estimated energy savings including CPU carbon savings, GPU carbon savings, memory carbon savings, net carbon savings, and more, wherein based on this, the energy savings computation and recommendation engine generates a reconfiguration recommendation that says reduce the carbon footprint of App A, wherein [0095] teaches the energy savings reconfiguration recommendation may be transmitted to the user device and the user device automatically reconfigures the user device in accord with the recommendation, wherein the user device is configured to automatically install updates and/or software products determined to reduce energy consumption of the devices; see also: [0011, 0034], Figs. 2-4); and
instantiate the workspace (Fig. 1 and [0028] teaches energy savings discovery engine generates an energy saving reconfiguration recommendation that recommends the user device to be re-configured to match the configuration, wherein if the user device, for example, utilizes a specific type of windows, the energy savings reconfiguration recommendation suggests that the user upgrade the operating system to reduce energy consumption, wherein the recommendation is transmitted to the user device and presented on the display, wherein [0017] teaches the locally installed software and user-configurable settings on the user device are configurable contributors that are device features that are configurable e.g. changeable by altering device settings or by installing/removing software, and that contribute to the energy footprint of the application, wherein [0084-0089] teach given the example energy footprints, the energy savings computation and recommendation engine determines that the device configuration presents an estimated energy savings including CPU carbon savings, GPU carbon savings, memory carbon savings, net carbon savings, and more, wherein based on this, the energy savings computation and recommendation engine generates a reconfiguration recommendation that says reduce the carbon footprint of App A, wherein [0095] teaches the energy savings reconfiguration recommendation may be transmitted to the user device and the user device automatically reconfigures the user device in accord with the recommendation, wherein the user device is configured to automatically install updates and/or software products determined to reduce energy consumption of the devices; see also: [0011, 0034], Figs. 2-4).
Regarding claim 2, Athavale anticipates all the limitations of claim 1 above.
Athavale further anticipates wherein the energy score is calculated, at least in part, based upon an energy context of the HIS ([0084-0089] teach given the example energy footprints, the energy savings computation and recommendation engine determines that the device configuration presents an estimated energy savings including CPU carbon savings, GPU carbon savings, memory carbon savings, net carbon savings, and more, wherein based on this, the energy savings computation and recommendation engine generates a reconfiguration recommendation that says reduce the carbon footprint of App A, as well as in [0010] teaches measuring the energy consumption profile of an application of a user device based on the power consumed by processors, power rendering the graphics of the application, and more, as well as in [0022] teaches the user device is configured to collect and self-report energy consumption metrics for the application to the engine, wherein the metrics are sampled or computed as specified times, such as set intervals during execution, as well as in [0034] teaches the metrics are used to derive an energy footprint for the application that corresponds to multiple time intervals of interest, wherein the user device energy footprint may be determined with respect to a multi-day interval, wherein the energy footprint can be for a day, three days, a week, or even for a shorter time period, such as an hour, that the application was executing, as well as in [0021] teaches considering the current power mode configuration that identifies the current power source and software-imposed settings for managing device power, such as settings that specify whether the battery is in “battery saver” mode or “normal use” mode, wherein [0043] teaches the user device energy footprint of the application is provided to a carbon footprint computation engine that uses renewable energy data for a geographical location of the user device to convert the energy footprint to a user device carbon footprint representing a carbon dioxide emission equivalent of the user device energy footprint; see also: [0032, 0058-0059]).
Regarding claim 3, Athavale anticipates all the limitations of claim 2 above.
Athavale further anticipates wherein the energy context comprises an identification or metric indicative of at least one of: a time of day, a geographic location of the IHS, an energy consumption of the IHS, a battery charge of the IHS ([0084-0089] teach given the example energy footprints, the energy savings computation and recommendation engine determines that the device configuration presents an estimated energy savings including CPU carbon savings, GPU carbon savings, memory carbon savings, net carbon savings, and more, wherein based on this, the energy savings computation and recommendation engine generates a reconfiguration recommendation that says reduce the carbon footprint of App A, as well as in [0010] teaches measuring the energy consumption profile of an application of a user device based on the power consumed by processors, power rendering the graphics of the application, and more, as well as in [0022] teaches the user device is configured to collect and self-report energy consumption metrics for the application to the engine, wherein the metrics are sampled or computed as specified times, such as set intervals during execution, as well as in [0034] teaches the metrics are used to derive an energy footprint for the application that corresponds to multiple time intervals of interest, wherein the user device energy footprint may be determined with respect to a multi-day interval, wherein the energy footprint can be for a day, three days, a week, or even for a shorter time period, such as an hour, that the application was executing, as well as in [0021] teaches considering the current power mode configuration that identifies the current power source and software-imposed settings for managing device power, such as settings that specify whether the battery is in “battery saver” mode or “normal use” mode, wherein [0043] teaches the user device energy footprint of the application is provided to a carbon footprint computation engine that uses renewable energy data for a geographical location of the user device to convert the energy footprint to a user device carbon footprint representing a carbon dioxide emission equivalent of the user device energy footprint; see also: [0032, 0058-0059]).
Regarding claim 4, Athavale anticipates all the limitations of claim 2 above.
Athavale further anticipates wherein the energy context comprises an identification or metric indicative of at least one of: a carbon footprint associated with an energy source ([0084-0089] teach given the example energy footprints, the energy savings computation and recommendation engine determines that the device configuration presents an estimated energy savings including CPU carbon savings, GPU carbon savings, memory carbon savings, net carbon savings, and more, wherein based on this, the energy savings computation and recommendation engine generates a reconfiguration recommendation that says reduce the carbon footprint of App A, as well as in [0010] teaches measuring the energy consumption profile of an application of a user device based on the power consumed by processors, power rendering the graphics of the application, and more, as well as in [0022] teaches the user device is configured to collect and self-report energy consumption metrics for the application to the engine, wherein the metrics are sampled or computed as specified times, such as set intervals during execution, as well as in [0034] teaches the metrics are used to derive an energy footprint for the application that corresponds to multiple time intervals of interest, wherein the user device energy footprint may be determined with respect to a multi-day interval, wherein the energy footprint can be for a day, three days, a week, or even for a shorter time period, such as an hour, that the application was executing, as well as in [0021] teaches considering the current power mode configuration that identifies the current power source and software-imposed settings for managing device power, such as settings that specify whether the battery is in “battery saver” mode or “normal use” mode, wherein the current power mode can be AC when plugged in or DC when the device is depending on battery power, wherein [0043] teaches the user device energy footprint of the application is provided to a carbon footprint computation engine that uses renewable energy data for a geographical location of the user device to convert the energy footprint to a user device carbon footprint representing a carbon dioxide emission equivalent of the user device energy footprint; see also: [0032, 0058-0059]).
Regarding claim 7, Athavale anticipates all the limitations of claim 1 above.
Athavale further anticipates wherein the one or more files are configured to enforce, based upon the energy score, at least one of: a reduction of energy consumption by the IHS ([0028-0029] teaches the recommendation suggests that the upgrade to reduce energy consumption associated with the application, wherein the system may identify alternatives that reduce or mitigate the energy footprint of a particular application executing on the user device, as well as in [0071] teaches computing an energy savings metric including a configuration that, if implemented on the user device, provides a reduction in the energy footprint of the application, wherein [0017] teaches the locally installed software and user-configurable settings on the user device are configurable contributors that are device features that are configurable e.g. changeable by altering device settings or by installing/removing software, and that contribute to the energy footprint of the application, wherein [0084-0089] teach given the example energy footprints, the energy savings computation and recommendation engine determines that the device configuration presents an estimated energy savings including CPU carbon savings, GPU carbon savings, memory carbon savings, net carbon savings, and more, wherein based on this, the energy savings computation and recommendation engine generates a reconfiguration recommendation that says reduce the carbon footprint of App A, wherein [0095] teaches the energy savings reconfiguration recommendation may be transmitted to the user device and the user device automatically reconfigures the user device in accord with the recommendation, wherein the user device is configured to automatically install updates and/or software products determined to reduce energy consumption of the devices; see also: [0011, 0034, 0057], Figs. 2-4).
Regarding claim 10, Athavale anticipates all the limitations of claim 1 above.
Athavale further anticipates wherein the program instructions, upon execution by the processor, cause the IHS to: receive, at the local management agent from the workspace orchestration service, a second one or more files configured to enable the local management agent to instantiate a second workspace, at least in part, in response to a change in the energy score (Fig. 1 and [0028] teaches energy savings discovery engine generates an energy saving reconfiguration recommendation that recommends the user device to be re-configured to match the configuration, wherein if the user device, for example, utilizes a specific type of windows, the energy savings reconfiguration recommendation suggests that the user upgrade the operating system to reduce energy consumption, wherein the recommendation is transmitted to the user device and presented on the display, wherein [0017] teaches the locally installed software and user-configurable settings on the user device are configurable contributors that are device features that are configurable e.g. changeable by altering device settings or by installing/removing software, and that contribute to the energy footprint of the application, wherein [0084-0089] teach given the example energy footprints, the energy savings computation and recommendation engine determines that the device configuration presents an estimated energy savings including CPU carbon savings, GPU carbon savings, memory carbon savings, net carbon savings, and more, wherein based on this, the energy savings computation and recommendation engine generates a reconfiguration recommendation that says reduce the carbon footprint of App A, wherein [0095] teaches the energy savings reconfiguration recommendation may be transmitted to the user device and the user device automatically reconfigures the user device in accord with the recommendation, wherein the user device is configured to automatically install updates and/or software products determined to reduce energy consumption of the devices, wherein [0058] teaches determining different energy savings for different applications, as well as in [0061] teaches impacting the energy footprint for the application and for other applications of interest, as well as in [0019] teaches the configurable contributors are also shown to include co-executing applications which are intended to encompass any applications on the user device that co-execute with the application and that also perform functions in support of the application that impact the energy footprint of the application; see also: [0011, 0034], Figs. 2-4); and
instantiate the second workspace (Fig. 1 and [0028] teaches energy savings discovery engine generates an energy saving reconfiguration recommendation that recommends the user device to be re-configured to match the configuration, wherein if the user device, for example, utilizes a specific type of windows, the energy savings reconfiguration recommendation suggests that the user upgrade the operating system to reduce energy consumption, wherein the recommendation is transmitted to the user device and presented on the display, wherein [0017] teaches the locally installed software and user-configurable settings on the user device are configurable contributors that are device features that are configurable e.g. changeable by altering device settings or by installing/removing software, and that contribute to the energy footprint of the application, wherein [0084-0089] teach given the example energy footprints, the energy savings computation and recommendation engine determines that the device configuration presents an estimated energy savings including CPU carbon savings, GPU carbon savings, memory carbon savings, net carbon savings, and more, wherein based on this, the energy savings computation and recommendation engine generates a reconfiguration recommendation that says reduce the carbon footprint of App A, wherein [0095] teaches the energy savings reconfiguration recommendation may be transmitted to the user device and the user device automatically reconfigures the user device in accord with the recommendation, wherein the user device is configured to automatically install updates and/or software products determined to reduce energy consumption of the devices, wherein [0058] teaches determining different energy savings for different applications, as well as in [0061] teaches impacting the energy footprint for the application and for other applications of interest, as well as in [0019] teaches the configurable contributors are also shown to include co-executing applications which are intended to encompass any applications on the user device that co-execute with the application and that also perform functions in support of the application that impact the energy footprint of the application; see also: [0011, 0034], Figs. 2-4).
Regarding claim 13, Athavale anticipates a memory storage device having program instructions stored thereon that, upon execution by one or more processors of an Information Handling System (IHS) of a workspace orchestration service, cause the IHS to:
create a workspace definition based, at least in part, upon an energy target (Fig. 1 and [0028] teaches energy savings discovery engine generates an energy saving reconfiguration recommendation that recommends the user device to be re-configured to match the configuration, wherein if the user device, for example, utilizes a specific type of windows, the energy savings reconfiguration recommendation suggests that the user upgrade the operating system to reduce energy consumption, wherein the recommendation is transmitted to the user device and presented on the display, wherein [0017] teaches the locally installed software and user-configurable settings on the user device are configurable contributors that are device features that are configurable e.g. changeable by altering device settings or by installing/removing software, and that contribute to the energy footprint of the application, wherein [0084-0089] teach given the example energy footprints, the energy savings computation and recommendation engine determines that the device configuration presents an estimated energy savings including CPU carbon savings, GPU carbon savings, memory carbon savings, net carbon savings, and more, wherein based on this, the energy savings computation and recommendation engine generates a reconfiguration recommendation that says reduce the carbon footprint of App A, wherein [0095] teaches the energy savings reconfiguration recommendation may be transmitted to the user device and the user device automatically reconfigures the user device in accord with the recommendation, wherein the user device is configured to automatically install updates and/or software products determined to reduce energy consumption of the devices; see also: [0011, 0034], Figs. 2-4; and
transmit, to a client IHS, one or more files configured to enable the client IHS to instantiate a workspace based upon the workspace definition (Fig. 1 and [0028] teaches energy savings discovery engine generates an energy saving reconfiguration recommendation that recommends the user device to be re-configured to match the configuration, wherein if the user device, for example, utilizes a specific type of windows, the energy savings reconfiguration recommendation suggests that the user upgrade the operating system to reduce energy consumption, wherein the recommendation is transmitted to the user device and presented on the display, wherein [0017] teaches the locally installed software and user-configurable settings on the user device are configurable contributors that are device features that are configurable e.g. changeable by altering device settings or by installing/removing software, and that contribute to the energy footprint of the application, wherein [0084-0089] teach given the example energy footprints, the energy savings computation and recommendation engine determines that the device configuration presents an estimated energy savings including CPU carbon savings, GPU carbon savings, memory carbon savings, net carbon savings, and more, wherein based on this, the energy savings computation and recommendation engine generates a reconfiguration recommendation that says reduce the carbon footprint of App A, wherein [0095] teaches the energy savings reconfiguration recommendation may be transmitted to the user device and the user device automatically reconfigures the user device in accord with the recommendation, wherein the user device is configured to automatically install updates and/or software products determined to reduce energy consumption of the devices; see also: [0011, 0034], Figs. 2-4.
Regarding claim 20, Athavale anticipates a method, comprising: creating a workspace definition based upon at least one of: an energy target (Fig. 1 and [0028] teaches energy savings discovery engine generates an energy saving reconfiguration recommendation that recommends the user device to be re-configured to match the configuration, wherein if the user device, for example, utilizes a specific type of windows, the energy savings reconfiguration recommendation suggests that the user upgrade the operating system to reduce energy consumption, wherein the recommendation is transmitted to the user device and presented on the display, wherein [0017] teaches the locally installed software and user-configurable settings on the user device are configurable contributors that are device features that are configurable e.g. changeable by altering device settings or by installing/removing software, and that contribute to the energy footprint of the application, wherein [0084-0089] teach given the example energy footprints, the energy savings computation and recommendation engine determines that the device configuration presents an estimated energy savings including CPU carbon savings, GPU carbon savings, memory carbon savings, net carbon savings, and more, wherein based on this, the energy savings computation and recommendation engine generates a reconfiguration recommendation that says reduce the carbon footprint of App A, wherein [0095] teaches the energy savings reconfiguration recommendation may be transmitted to the user device and the user device automatically reconfigures the user device in accord with the recommendation, wherein the user device is configured to automatically install updates and/or software products determined to reduce energy consumption of the devices; see also: [0011, 0034], Figs. 2-4; and
transmitting, to a local management agent of a client Information Handling System (IHS), one or more files or policies configured to enable the local management agent to instantiate a workspace based upon the workspace definition (Fig. 1 and [0028] teaches energy savings discovery engine generates an energy saving reconfiguration recommendation that recommends the user device to be re-configured to match the configuration, wherein if the user device, for example, utilizes a specific type of windows, the energy savings reconfiguration recommendation suggests that the user upgrade the operating system to reduce energy consumption, wherein the recommendation is transmitted to the user device and presented on the display, wherein [0017] teaches the locally installed software and user-configurable settings on the user device are configurable contributors that are device features that are configurable e.g. changeable by altering device settings or by installing/removing software, and that contribute to the energy footprint of the application, wherein [0084-0089] teach given the example energy footprints, the energy savings computation and recommendation engine determines that the device configuration presents an estimated energy savings including CPU carbon savings, GPU carbon savings, memory carbon savings, net carbon savings, and more, wherein based on this, the energy savings computation and recommendation engine generates a reconfiguration recommendation that says reduce the carbon footprint of App A, wherein [0095] teaches the energy savings reconfiguration recommendation may be transmitted to the user device and the user device automatically reconfigures the user device in accord with the recommendation, wherein the user device is configured to automatically install updates and/or software products determined to reduce energy consumption of the devices; see also: [0011, 0034], Figs. 2-4.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim(s) 5-6, 8-9, and 11 are rejected under 35 U.S.C. 103 as being unpatentable over Athavale (US 20250216921 A1) in view of Labriji et al. (US 20240272928 A1).
Regarding claim 5, Athavale anticipates all the limitations of claim 1 above.
However, Athavale does not explicitly teach wherein the energy score is calculated, at least in part, based upon an energy context of a remote IHS configured to execute the workspace orchestration service.
From the same or similar field of endeavor, Labriji teaches wherein the energy score is calculated, at least in part, based upon an energy context of a remote IHS configured to execute the workspace orchestration service ([0014] teaches requiring remote execution services required by a mobile device via cellular communication network, wherein the migration of services occurs based on minimizing the cost in terms of replication energy while ensuring a level of continuity of service, as well as in [0029] teaches the determination, for a migration at the selected migration moment of time, for each service request, of a number of replications of the virtual machine to be performed at the selected migration moment of time, each replication being performed on a selected host server, implements a minimization of a target function depending on energy consumed for said number of replications, under the constraint of a risk metric associated with the accessibility of the host server(s) chosen for the replication and of an availability metric at the selected migration moment of time; see also: [0032, 0039, 0073]).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify Athavale to incorporate the teachings of Labriji to include wherein the energy score is calculated, at least in part, based upon an energy context of a remote IHS configured to execute the workspace orchestration service. One would have been motivated to do so in order to identify a migration process while maintaining a goal of minimizing the cost of replication energy and limiting the risk of loss of continuity of service (Labriji, [0013]). By incorporating the teachings of Labriji, one would have been able to implementing a minimization of a target function depending on an energy consumed under the constraint of a risk metric associated with the accessibility of host servers during the migration moment (Labriji, [0029]).
Regarding claim 6, Athavale anticipates all the limitations of claim 1 above.
However, Athavale does not explicitly teach wherein the energy score is calculated, at least in part, based upon an energy context of a remote IHS configured to execute a component of the workspace.
From the same or similar field of endeavor, Labriji teaches wherein the energy score is calculated, at least in part, based upon an energy context of a remote IHS configured to execute a component of the workspace ([0014] teaches requiring remote execution services required by a mobile device via cellular communication network, wherein the migration of services occurs based on minimizing the cost in terms of replication energy while ensuring a level of continuity of service, as well as in [0029] teaches the determination, for a migration at the selected migration moment of time, for each service request, of a number of replications of the virtual machine to be performed at the selected migration moment of time, each replication being performed on a selected host server, implements a minimization of a target function depending on energy consumed for said number of replications, under the constraint of a risk metric associated with the accessibility of the host server(s) chosen for the replication and of an availability metric at the selected migration moment of time; see also: [0032, 0039, 0073]).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify Athavale to incorporate the teachings of Labriji to include wherein the energy score is calculated, at least in part, based upon an energy context of a remote IHS configured to execute a component of the workspace. One would have been motivated to do so in order to identify a migration process while maintaining a goal of minimizing the cost of replication energy and limiting the risk of loss of continuity of service (Labriji, [0013]). By incorporating the teachings of Labriji, one would have been able to implementing a minimization of a target function depending on an energy consumed under the constraint of a risk metric associated with the accessibility of host servers during the migration moment (Labriji, [0029]).
Regarding claim 8, Athavale anticipates all the limitations of claim 1 above.
However, Athavale does not explicitly teach wherein the one or more files are configured to enforce a security target calculated using at least one of: an identification of a software application requested by a user of the IHS, an identification of a datafile requested by the user of the IHS, an identification of a locale of the IHS, an identification of a user of the IHS, an identification of a network of the IHS, an identification of hardware of the IHS, an identification of a storage system of the requested datafile, a risk metric associated with a locale of the IHS, a risk metric associated with a user of the IHS, a risk metric associated with a network of the IHS, a risk metric associated with hardware of the IHS, a risk metric associated with a requested datafile, or a regulatory risk metric.
From the same or similar field of endeavor, Labriji teaches wherein the one or more files are configured to enforce a security target calculated using at least one of: a risk metric associated with a network of the HIS ([0010] teaches choosing a server host for migration but having a risk of service interruption in the event of host server prediction error, wherein [0029] teaches the determination for a migration at the selected migration moment of time is constrained under a risk metric associated with the accessibility of the host servers chosen for replication and of an availability metric, as well as in [0030-0035] teach the risk metric uses a probability representative of a prediction of mobility associated with each selected host server, which represents the probability that the mobile device sending the service request enters a geographical coverage area associated with the selected hosted server, wherein [0039] teaches the system provides remote execution of services required by the mobile device, wherein the system comprises a cellular communication network according to a communication protocol; see also: [0145-0156], Fig. 1-3).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify Athavale to incorporate the teachings of Labriji to include wherein the one or more files are configured to enforce a security target calculated using at least one of: an identification of a software application requested by a user of the IHS, an identification of a datafile requested by the user of the IHS, an identification of a locale of the IHS, an identification of a user of the IHS, an identification of a network of the IHS, an identification of hardware of the IHS, an identification of a storage system of the requested datafile, a risk metric associated with a locale of the IHS, a risk metric associated with a user of the IHS, a risk metric associated with a network of the IHS, a risk metric associated with hardware of the IHS, a risk metric associated with a requested datafile, or a regulatory risk metric. One would have been motivated to do so in order to identify a migration process while maintaining a goal of minimizing the cost of replication energy and limiting the risk of loss of continuity of service (Labriji, [0013]). By incorporating the teachings of Labriji, one would have been able to implementing a minimization of a target function depending on an energy consumed under the constraint of a risk metric associated with the accessibility of host servers during the migration moment (Labriji, [0029]).
Regarding claim 9, Athavale anticipates all the limitations of claim 1 above.
However, Athavale does not explicitly teach wherein the one or more files are configured to enforce a productivity target calculated using at least one of: a resource metric associated with a locale of the IHS, a resource metric associated with a user of the IHS, a resource metric associated with a network of the IHS, a resource metric associated with hardware of the IHS, or a resource metric associated with a storage system of a requested datafile.
From the same or similar field of endeavor, Mader teaches wherein the one or more files are configured to enforce a productivity target calculated using at least one of: a resource metric associated with hardware of the HIS ([0010] teaches the HPC utilizes large amounts of energy, wherein if the system has decreased performance, this can lead to longer job completion times, wherein [0012] teaches efficiently determining optimal settings of multiple tunable hardware parameters for a wide variety of workloads, wherein the optimal parameter settings can be determined for a workload class, wherein what is considered optimal may be according to a predetermined or user-specified optimization performance metric, such as greatest energy efficiency, such as greatest performance per watt, greatest performance at a given power cap, lowest power usage at a given performance floor, or other similar metrics, wherein the optimal settings of the hardware parameters for a given workload class may be determined by varying settings of hardware parameters, while a workload is being run in order to find the best combination, as well as in [0016] teaches optimizing the runtime environment by enabling a set of conditions that make the HPC system, or runtime environment, as effective as possible when measured against a particular performance characteristic, wherein the runtime environment may be optimized for a number of optimization metrics, wherein the optimization metrics include optimal energy efficiency, minimal energy/power consumption, maximum workload performance given by a particular power cap, and other characteristics; see also: [0055-0069]).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify Athavale to incorporate the teachings of Mader to include wherein the one or more files are configured to enforce a productivity target calculated using at least one of: a resource metric associated with a locale of the IHS, a resource metric associated with a user of the IHS, a resource metric associated with a network of the IHS, a resource metric associated with hardware of the IHS, or a resource metric associated with a storage system of a requested datafile. One would have been motivated to do so in order to avoid excessive computational overhead and inefficiency, thereby improving the performance of the HPC system (Mader, [0014]). By incorporating the teachings of Mader, one would have been able to find the combination of settings producing the best results according to the energy efficiency metrics (Mader, [0012]).
Regarding claim 11, Athavale anticipates all the limitations of claim 10 above.
However, Athavale does not explicitly teach wherein in response to a changed energy score being worse than a previous energy score, the second one or more files replace a local component of the workspace with a remote component in the second workspace.
From the same or similar field of endeavor, Labriji teaches wherein in response to a changed energy score being worse than a previous energy score, the second one or more files replace a local component of the workspace with a remote component in the second workspace ([0014] teaches requiring remote execution services required by a mobile device via cellular communication network, wherein the migration of services occurs based on minimizing the cost in terms of replication energy while ensuring a level of continuity of service, as well as in [0029] teaches the determination, for a migration at the selected migration moment of time, for each service request, of a number of replications of the virtual machine to be performed at the selected migration moment of time, each replication being performed on a selected host server, implements a minimization of a target function depending on energy consumed for said number of replications, under the constraint of a risk metric associated with the accessibility of the host server(s) chosen for the replication and of an availability metric at the selected migration moment of time; see also: [0032, 0039, 0073]).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify Athavale to incorporate the teachings of Labriji to include wherein in response to a changed energy score being worse than a previous energy score, the second one or more files replace a local component of the workspace with a remote component in the second workspace. One would have been motivated to do so in order to identify a migration process while maintaining a goal of minimizing the cost of replication energy and limiting the risk of loss of continuity of service (Labriji, [0013]). By incorporating the teachings of Labriji, one would have been able to implementing a minimization of a target function depending on an energy consumed under the constraint of a risk metric associated with the accessibility of host servers during the migration moment (Labriji, [0029]).
Claim(s) 12 is rejected under 35 U.S.C. 103 as being unpatentable over Athavale (US 20250216921 A1) in view of Morgan (US 20120311154 A1).
Regarding claim 12, Athavale anticipates all the limitations of claim 10 above.
However, Athavale does not explicitly teach wherein in response to the changed energy score being better than a previous energy score, the second one or more files replace a remote component of the workspace with a local component in the second workspace.
From the same or similar field of endeavor, Morgan teaches wherein in response to the changed energy score being better than a previous energy score, the second one or more files replace a remote component of the workspace with a local component in the second workspace (Fig. 8 and [0057] teach the system can execute the migration of a workload to a target cloud by interacting with the cloud management system of the target cloud, wherein [0056] teaches the migration is on a time limited basis, wherein [0018] teaches the cloud management system can extract and build a set of resources on demand, wherein a set of servers may respond to an instantiation request for a given quantity of cycles, wherein [0019] teaches after interrogating and receiving resource commitments, the system can select a group of servers that best match the instantiation request for each component, which are temporarily combined to produce and manage the requested virtual machine population or other cloud-based resources, wherein [0042] teaches migrating the workload to the one or more clouds in the target cloud, wherein [0032] teaches the users can operate on premise with a local area network, as well as in [0034] teaches the user can operate a client located within the user premise; see also: [0028-0030, 0036, 0048]).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify Athavale to incorporate the teachings of Morgan to include wherein in response to the changed energy score being better than a previous energy score, the second one or more files replace a remote component of the workspace with a local component in the second workspace. One would have been motivated to do so in order to reduce costs associated with the over-consumption of cloud resources by migrating the workload to a target cloud with larger capacities and increased resources (Morgan, [0040]). By incorporating the teachings of Morgan, one would have been able to manage executing a workload through migration to alternative cloud providers, thus allowing the user to manage consumption spikes (Morgan, [0004]).
Claim(s) 14-16 are rejected under 35 U.S.C. 103 as being unpatentable over Athavale (US 20250216921 A1) in view of Mader et al. (US 20240095081 A1).
Regarding claim 14, Athavale anticipates all the limitations of claim 13 above.
However, Athavale does not explicitly teach wherein the program instructions, upon execution, cause the IHS to: in response to a determination that an energy score does not meet the energy target, modify the workspace definition; and transmit, to the client IHS, one or more other files configured to enable the client IHS to instantiate a modified workspace based upon the modified workspace definition.
From the same or similar field of endeavor, Mader teaches wherein the program instructions, upon execution, cause the IHS to: in response to a determination that an energy score does not meet the energy target, modify the workspace definition ([0016] teaches optimizing the runtime environment by enabling a set of conditions that make the HPC system, or runtime environment, as effective as possible when measured against a particular performance characteristic, wherein the runtime environment may be optimized for a number of optimization metrics, wherein the optimization metrics include optimal energy efficiency, minimal energy/power consumption, maximum workload performance given by a particular power cap, and other characteristics, wherein Fig. 5 and [0059] teach determining whether the workload-specific fingerprint matches with cluster fingerprints that are present in the database, wherein the fingerprint may be compared to the range of values to determine whether it aligns, wherein [0063-0064] teach that the workload-specific fingerprint is not in the database and an optimization metric to optimize during the running of the workload in the HPC system can be identified, wherein the optimization metric for which the optimization is desired is provided by the executor of the workload, wherein [0065] teaches during runtime of the workload, an optimal setting for the tunable hardware execution parameters may be determined in view of the optimization metric by modifying or tuning the settings of the tunable hardware execution parameters, noting the effect of such modification on the performance and selecting the setting that gives the best performance; see also: Fig. 1, [0025-0026, 0066]); and
transmit, to the client IHS, one or more other files configured to enable the client IHS to instantiate a modified workspace based upon the modified workspace definition ([0016] teaches optimizing the runtime environment by enabling a set of conditions that make the HPC system, or runtime environment, as effective as possible when measured against a particular performance characteristic, wherein the runtime environment may be optimized for a number of optimization metrics, wherein the optimization metrics include optimal energy efficiency, minimal energy/power consumption, maximum workload performance given by a particular power cap, and other characteristics, wherein Fig. 5 and [0059] teach determining whether the workload-specific fingerprint matches with cluster fingerprints that are present in the database, wherein the fingerprint may be compared to the range of values to determine whether it aligns, wherein [0063-0064] teach that the workload-specific fingerprint is not in the database and an optimization metric to optimize during the running of the workload in the HPC system can be identified, wherein the optimization metric for which the optimization is desired is provided by the executor of the workload, wherein [0065] teaches during runtime of the workload, an optimal setting for the tunable hardware execution parameters may be determined in view of the optimization metric by modifying or tuning the settings of the tunable hardware execution parameters, noting the effect of such modification on the performance and selecting the setting that gives the best performance; see also: Fig. 1, [0025-0026, 0066]).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify Athavale to incorporate the teachings of Mader to include wherein the program instructions, upon execution, cause the IHS to: in response to a determination that an energy score does not meet the energy target, modify the workspace definition; and transmit, to the client IHS, one or more other files configured to enable the client IHS to instantiate a modified workspace based upon the modified workspace definition. One would have been motivated to do so in order to avoid excessive computational overhead and inefficiency, thereby improving the performance of the HPC system (Mader, [0014]). By incorporating the teachings of Mader, one would have been able to find the combination of settings producing the best results according to the energy efficiency metrics (Mader, [0012]).
Regarding claim 15, the combination of Athavale and Mader teaches all the limitations of claim 14 above.
However, Athavale does not explicitly teach wherein the energy score is calculated based, at least in part, upon an identification or metric indicative of at least one of: a time of day, a day of the week, a day of the month, a month of the year, a geographic location of the client IHS, an energy consumption of the client IHS, a battery charge of the client IHS, a performance level of the client IHS, an energy source available to the IHS, a type of energy source available to the client IHS, or a carbon footprint associated with an energy source or utilities provider.
From the same or similar field of endeavor, Mader further teaches wherein the energy score is calculated based, at least in part, upon an identification or metric indicative of at least one of: a performance level of the client HIS ([0010] teaches the HPC utilizes large amounts of energy, wherein if the system has decreased performance, this can lead to longer job completion times, wherein [0012] teaches efficiently determining optimal settings of multiple tunable hardware parameters for a wide variety of workloads, wherein the optimal parameter settings can be determined for a workload class, wherein what is considered optimal may be according to a predetermined or user-specified optimization performance metric, such as greatest energy efficiency, such as greatest performance per watt, greatest performance at a given power cap, lowest power usage at a given performance floor, or other similar metrics, wherein the optimal settings of the hardware parameters for a given workload class may be determined by varying settings of hardware parameters, while a workload is being run in order to find the best combination, as well as in [0016] teaches optimizing the runtime environment by enabling a set of conditions that make the HPC system, or runtime environment, as effective as possible when measured against a particular performance characteristic, wherein the runtime environment may be optimized for a number of optimization metrics, wherein the optimization metrics include optimal energy efficiency, minimal energy/power consumption, maximum workload performance given by a particular power cap, and other characteristics; see also: [0055-0069]).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify the combination of Athavale and Mader to incorporate the further teachings of Mader to include wherein the energy score is calculated based, at least in part, upon an identification or metric indicative of at least one of: a time of day, a day of the week, a day of the month, a month of the year, a geographic location of the client IHS, an energy consumption of the client IHS, a battery charge of the client IHS, a performance level of the client IHS, an energy source available to the IHS, a type of energy source available to the client IHS, or a carbon footprint associated with an energy source or utilities provider. One would have been motivated to do so in order to avoid excessive computational overhead and inefficiency, thereby improving the performance of the HPC system (Mader, [0014]). By incorporating the teachings of Mader, one would have been able to find the combination of settings producing the best results according to the energy efficiency metrics (Mader, [0012]).
Regarding claim 16, the combination of Athavale and Mader teaches all the limitations of claim 14 above.
Athavale further teaches wherein the energy score is calculated based, at least in part, upon an energy context of at least one of: the HIS ([0084-0089] teach given the example energy footprints, the energy savings computation and recommendation engine determines that the device configuration presents an estimated energy savings including CPU carbon savings, GPU carbon savings, memory carbon savings, net carbon savings, and more, wherein based on this, the energy savings computation and recommendation engine generates a reconfiguration recommendation that says reduce the carbon footprint of App A, as well as in [0010] teaches measuring the energy consumption profile of an application of a user device based on the power consumed by processors, power rendering the graphics of the application, and more, as well as in [0022] teaches the user device is configured to collect and self-report energy consumption metrics for the application to the engine, wherein the metrics are sampled or computed as specified times, such as set intervals during execution, as well as in [0034] teaches the metrics are used to derive an energy footprint for the application that corresponds to multiple time intervals of interest, wherein the user device energy footprint may be determined with respect to a multi-day interval, wherein the energy footprint can be for a day, three days, a week, or even for a shorter time period, such as an hour, that the application was executing, as well as in [0021] teaches considering the current power mode configuration that identifies the current power source and software-imposed settings for managing device power, such as settings that specify whether the battery is in “battery saver” mode or “normal use” mode, wherein [0043] teaches the user device energy footprint of the application is provided to a carbon footprint computation engine that uses renewable energy data for a geographical location of the user device to convert the energy footprint to a user device carbon footprint representing a carbon dioxide emission equivalent of the user device energy footprint; see also: [0032, 0058-0059]).
Claim(s) 17 is rejected under 35 U.S.C. 103 as being unpatentable over Athavale (US 20250216921 A1) in view of Mader et al. (US 20240095081 A1) in view of Labriji et al. (US 20240272928 A1).
Regarding claim 17, the combination of Athavale and Mader teaches all the limitations of claim 14 above.
However, Athavale does not explicitly teach wherein the modified workspace definition re-instantiates or migrates a local component of the workspace for execution by a remote IHS in the modified workspace.
From the same or similar field of endeavor, Labriji teaches wherein the modified workspace definition migrates a local component of the workspace for execution by a remote IHS in the modified workspace ([0014] teaches requiring remote execution services required by a mobile device via cellular communication network, wherein the migration of services occurs based on minimizing the cost in terms of replication energy while ensuring a level of continuity of service, as well as in [0029] teaches the determination, for a migration at the selected migration moment of time, for each service request, of a number of replications of the virtual machine to be performed at the selected migration moment of time, each replication being performed on a selected host server, implements a minimization of a target function depending on energy consumed for said number of replications, under the constraint of a risk metric associated with the accessibility of the host server(s) chosen for the replication and of an availability metric at the selected migration moment of time; see also: [0032, 0039, 0073]).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify the combination of Athavale and Mader to incorporate the teachings of Labriji to include wherein the modified workspace definition re-instantiates or migrates a local component of the workspace for execution by a remote IHS in the modified workspace. One would have been motivated to do so in order to identify a migration process while maintaining a goal of minimizing the cost of replication energy and limiting the risk of loss of continuity of service (Labriji, [0013]). By incorporating the teachings of Labriji, one would have been able to implementing a minimization of a target function depending on an energy consumed under the constraint of a risk metric associated with the accessibility of host servers during the migration moment (Labriji, [0029]).
Claim(s) 18-19 are rejected under 35 U.S.C. 103 as being unpatentable over Athavale (US 20250216921 A1) in view of Mader et al. (US 20240095081 A1) in view of Morgan (US 20120311154 A1).
Regarding claim 18, the combination of Athavale and Mader teaches all the limitations of claim 14 above.
However, Athavale does not explicitly teach wherein the modified workspace definition re-instantiates or migrates a remote component of the workspace for execution by the client IHS in the modified workspace.
From the same or similar field of endeavor, Morgan teaches wherein the modified workspace definition re-instantiates or migrates a remote component of the workspace for execution by the client IHS in the modified workspace (Fig. 8 and [0057] teach the system can execute the migration of a workload to a target cloud by interacting with the cloud management system of the target cloud, wherein [0056] teaches the migration is on a time limited basis, wherein [0018] teaches the cloud management system can extract and build a set of resources on demand, wherein a set of servers may respond to an instantiation request for a given quantity of cycles, wherein [0019] teaches after interrogating and receiving resource commitments, the system can select a group of servers that best match the instantiation request for each component, which are temporarily combined to produce and manage the requested virtual machine population or other cloud-based resources, wherein [0042] teaches migrating the workload to the one or more clouds in the target cloud, wherein [0032] teaches the users can operate on premise with a local area network, as well as in [0034] teaches the user can operate a client located within the user premise; see also: [0028-0030, 0036, 0048]).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify the combination of Athavale and Mader to incorporate the teachings of Morgan to include wherein the modified workspace definition re-instantiates or migrates a remote component of the workspace for execution by the client IHS in the modified workspace. One would have been motivated to do so in order to reduce costs associated with the over-consumption of cloud resources by migrating the workload to a target cloud with larger capacities and increased resources (Morgan, [0040]). By incorporating the teachings of Morgan, one would have been able to manage executing a workload through migration to alternative cloud providers, thus allowing the user to manage consumption spikes (Morgan, [0004]).
Regarding claim 19, the combination of Athavale and Mader teaches all the limitations of claim 14 above.
However, Athavale does not explicitly teach wherein the modified workspace definition migrates a remote component of the workspace from a first remote IHS to a second remote IHS in the modified workspace.
From the same or similar field of endeavor, Morgan teaches wherein the modified workspace definition migrates a remote component of the workspace from a first remote IHS to a second remote IHS in the modified workspace (Fig. 8 and [0057] teach the system can execute the migration of a workload to a target cloud by interacting with the cloud management system of the target cloud, wherein [0056] teaches the migration is on a time limited basis, wherein [0018] teaches the cloud management system can extract and build a set of resources on demand, wherein a set of servers may respond to an instantiation request for a given quantity of cycles, wherein [0019] teaches after interrogating and receiving resource commitments, the system can select a group of servers that best match the instantiation request for each component, which are temporarily combined to produce and manage the requested virtual machine population or other cloud-based resources, wherein [0042] teaches migrating the workload to the one or more clouds in the target cloud, wherein [0032] teaches the users can operate on premise with a local area network, as well as in [0034] teaches the user can operate a client located within the user premise; see also: [0028-0030, 0036, 0048]).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify the combination of Athavale and Mader to incorporate the teachings of Morgan to include wherein the modified workspace definition migrates a remote component of the workspace from a first remote IHS to a second remote IHS in the modified workspace. One would have been motivated to do so in order to reduce costs associated with the over-consumption of cloud resources by migrating the workload to a target cloud with larger capacities and increased resources (Morgan, [0040]). By incorporating the teachings of Morgan, one would have been able to manage executing a workload through migration to alternative cloud providers, thus allowing the user to manage consumption spikes (Morgan, [0004]).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Morad et al. (US 11494199 B2) discloses the goal could be to maximize performance while the power of the server is capped at 250 watts or to minimize the energy per committed instruction, wherein the defined target metric is improved by dynamically measuring the workload
Hovhannisyan et al. (US 20210027401 A1) discloses automated measures to reduce carbon emissions and power wastage may be executed, such as migrating idle virtual objects to other hosts followed by spinning up virtual objects to run on the resources of the one or more hosts that were previously reserved for the idle virtual object
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/SARA GRACE BROWN/Primary Examiner, Art Unit 3625