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 .
DETAILED ACTION
This action is a responsive to the application filed on 10/30/2023.
Claims 1-20 are pending.
Claims 1-20 are rejected.
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.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied 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.
Claims 1-9, 14-17, and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Street et al (US Pub 20180332117) hereinafter Street, in view of Raghuram et al (US Pub 20240022550) hereinafter Raghuram.
Regarding claim 1, Street teaches a method comprising: hosting, on an edge computing system, a user interface instance (paragraphs 0031, and 0035-0041 teach a computing device with a user interface in a “distributed system” including edge devices; “Moreover, input interface 260 and/or output interface 270 may include or be interfaced to any number or type of peripherals”);
providing, by the user interface instance, a cryptographic authentication token to an endpoint instance of a high-performance computing system external to the edge computing system (paragraphs 0052, 0055-0058, and 0069 teach detecting new edge devices (high-performance computing system external to the edge computing system), where “the cryptographic information about edge device 411 is communicated from provisioning service 415 to edge device 411 (providing…a cryptographic authentication token to an endpoint instance)…The cryptographic information may also include credentials, the hostname of the selected IoT support service 451, connectivity information for edge device 411 to connect with IoT support service 451, and/or the like”);
responsive to providing the cryptographic authentication token, forming a connection between the user interface instance and the endpoint instance (paragraphs 0041 teach “Each of the IoT devices 341-343, and/or the devices that comprise IoT support service 351 and/or application back-end 313 and/or gateway devices 311 and 312 and/or provision service device 315 may include examples of computing device 200 of FIG. 2”; further paragraphs 0052, 0055-0058, and 0069 teach communication connections between the edge device (endpoint instance) and IoT support service devices (user interface));
mounting a directory of a first file system of the high-performance computing system to a second file system of the edge computing system to provide an extended file system (paragraphs 0052, 0055-0058, 0060, and 0069 teach detecting new edge devices, where “the cryptographic information about edge device 411 is communicated from provisioning service 415 (second file system of the edge computing system) to edge device 411 (first file system of the high-performance computing system)…The cryptographic information may also include credentials, the hostname of the selected IoT support service 451, connectivity information for edge device 411 to connect with IoT support service 451, and/or the like (provide an extended file system)” and stored on the respective devices (file systems)); and
responsive to receiving, by the user interface instance, a request from the high-performance computing system via the connection, initiating, by the user interface instance, an operation to exchange data between the edge computing system and the high-performance computing system (paragraphs 0052, 0055-0058, 0060, and 0069 teach detecting new edge devices, where “Edge device 411 may have an endpoint uniform resource indicator (URI) that is installed in the factory. In some examples, on first power-up and first boot-up, edge device 411 is cryptographically guaranteed to connect to provisioning service 415 and not elsewhere (responsive to receiving, by the user interface instance, a request from the high-performance computing system via the connection, initiating, by the user interface instance)”; wherein “the cryptographic information about edge device 411 is communicated from provisioning service 415 to edge device 411 (an operation to exchange data between the edge computing system and the high-performance computing system)).
Street at least implies mounting a directory of a first file system of the high-performance computing system to a second file system of the edge computing system to provide an extended file system (see mappings above); however, Raghuram teaches mounting a directory of a first file system of the high-performance computing system to a second file system of the edge computing system to provide an extended file system (paragraphs 0051 and 0055-0058 teach creating an API connection (extended file system) and “TKAB interfaces with a key management system (KMS) to perform a cryptographic key operation. The TKAB may use a plugin to interface with an API at the KMS. A response is received from the KMS”).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to implement Raghuram’s teachings of API connection between devices and cryptographic key management into Street‘s teaching of establishing cryptographic communications between IoT and new edge devices in a system in order to “the risk of exposing it to the rest of the system, thereby reducing the potential for sensitive data to be exposed while providing a higher degree of control and transparency for users” (Raghuram, paragraphs 0020, 0051 and 0055-0058).
Regarding claim 2, the combination of Street and Raghuram teach all the claim limitations of claim 1 above; and further teach wherein forming the connection between the user interface instance and the endpoint instance comprises forming a connection with a service mesh gateway of the high-performance computing system (Raghuram, paragraphs 0109, 0119-0122, and 0139 the “IoT network, arranged as a mesh network” and “managing service meshes” including edge devices).
Street and Raghuram are combinable for the same rationale as set forth above with respect to claim 1.
Regarding claim 3, the combination of Street and Raghuram teach all the claim limitations of claim 1 above; and further teach wherein hosting the user interface instances comprises hosting a container environment on the edge computing system (Street, paragraphs 0023, 0031, and 0035-0041 teach a “host” computing device with a user interface in a “distributed system” including edge devices; “Moreover, input interface 260 and/or output interface 270 may include or be interfaced to any number or type of peripherals”).
Regarding claim 4, the combination of Street and Raghuram teach all the claim limitations of claim 1 above; and further teach wherein mounting the first file system comprises communicating between the edge computing system and the high-performance computing system using a network file transfer protocol (Raghuram, paragraphs 0107-0109, 0126-0127, 0136, and 0139 teach utilizing different “protocols” for data communications between network devices and edge devices).
Street and Raghuram are combinable for the same rationale as set forth above with respect to claim 1.
Regarding claim 5, the combination of Street and Raghuram teach all the claim limitations of claim 1 above; and further teach responsive to a second request received by the user interface instance from the connection, controlling a compute resource of the edge computing system (Street, paragraphs 0052, 0055-0058, 0060, and 0066-0069 teach “After provisioning is complete, in some examples, communications between edge device 411 and IoT support service 451 may occur directly and/or in a “normal” fashion”, wherein the edge device can send data (second request) and the IoT device can send modules for adding “new functionality” to the device (controlling a compute resource of the edge computing system)).
Regarding claim 6, the combination of Street and Raghuram teach all the claim limitations of claim 1 above; and further teach responsive to a compute resource of the edge computing system performing an operation, reporting, by the user interface instance and over the connection, a status of the operation (Street, paragraphs 0060-0068 teach processing the edge devices message, and the “IoT support service 451 returns a message to edge device 411 with steps that edge device 411 is to follow before edge device 411 may begin sending data to IoT support service 451. Such steps may include, for example, updating the firmware of edge device 411, changing a configuration file, and/or the like (performing an operation, reporting, by the user interface instance and over the connection, a status of the operation)”. Further, it is taught that deploying “module twins” between the devices (alternative operation), and “an IoT device (edge computing system…user interface instance) that is a lock, the module twin associated with a module for the locking function of the smart lock may have a corresponding property indicating whether the reported status is locked or unlocked. In some examples, a desired property indicates the status that the property that the actual device should have at that time. The desired property may be the same as or different than the reported property. If the desired property is different than the corresponding reported property, actions may be taken to resolve the discrepancy”).
Regarding claim 7, the combination of Street and Raghuram teach all the claim limitations of claim 1 above; and further teach wherein the high-performance computing system comprises a plurality of compute nodes, and the second file system comprises a file system shared by the plurality of compute nodes (Street, paragraphs 0060-0069 teach the edge device (high-performance computing system) having multiple module installed for performing operations (compute nodes) and memory (file system) with accessible communicated data of device device statuses).
Regarding claim 8, the combination of Street and Raghuram teach all the claim limitations of claim 1 above; and further teach mounting, by the user interface instance, a resource of the edge computing system to the first file system (Street, paragraphs 0052, 0055-0058, and 0060-0069 teach the IoT device (by the user interface instance…the edge computing system) obtaining edge device status information stored in the edge memory (first file system) via a communication channel (mounting…a resource)).
Regarding claim 9, the combination of Street and Raghuram teach all the claim limitations of claim 1 above; and further teach wherein the mounting comprises mounting a subdirectory of the first file system to a mount point of the second file system (Street, paragraphs 0052, 0055-0058, and 0060-0069 teach the IoT device establishing “module twins” for obtaining edge device module status information (subdirectory) stored in the edge memory (first file system) via a learning communication channel and storing the status data in the IoT device and or provisioning system (second file system)).
Regarding claim 14, Street teaches a non-transitory storage medium that stores machine-readable instructions that, when executed by a machine, cause the machine to: provide a user interface instance on an edge computing system (paragraphs 0030-0031, and 0035-0041 teach a computing device, including a processor and memory, with a user interface in a “distributed system” including edge devices; “Moreover, input interface 260 and/or output interface 270 may include or be interfaced to any number or type of peripherals”);
cause the user interface instance to:
provide, to a high-performance computing system, a first request to register the user interface instance with an endpoint manager instance of the high-performance computing system (paragraphs 0052, 0055-0058, and 0069 teach detecting new edge devices (high-performance computing system external to the edge computing system), where “the cryptographic information about edge device 411 is communicated from provisioning service 415 to edge device 411 (providing…a cryptographic authentication token to an endpoint instance)…The cryptographic information may also include credentials, the hostname of the selected IoT support service 451, connectivity information for edge device 411 to connect with IoT support service 451, and/or the like”);
mount a file system of the edge computing system and a file system of the high-performance computing system to provide an extended file system accessible by the edge computing system (paragraphs 0052, 0055-0058, 0060, and 0069 teach detecting new edge devices, where “the cryptographic information about edge device 411 is communicated from provisioning service 415 (second file system of the edge computing system) to edge device 411 (first file system of the high-performance computing system)…The cryptographic information may also include credentials, the hostname of the selected IoT support service 451, connectivity information for edge device 411 to connect with IoT support service 451, and/or the like (provide an extended file system)” and stored on the respective devices (file systems)); and
responsive to a second request sent , move data between locations of the extended file system to exchange data between the edge computing system and the high-performance computing system (paragraphs 0052, 0055-0058, 0060, and 0069 teach detecting new edge devices, where “Edge device 411 may have an endpoint uniform resource indicator (URI) that is installed in the factory. In some examples, on first power-up and first boot-up, edge device 411 is cryptographically guaranteed to connect to provisioning service 415 and not elsewhere (responsive to receiving, by the user interface instance, a request from the high-performance computing system via the connection, initiating, by the user interface instance)”; wherein “the cryptographic information about edge device 411 is communicated from provisioning service 415 to edge device 411 (an operation to exchange data between the edge computing system and the high-performance computing system)).
However, Street does not explicitly teach to a service mesh gateway of a high-performance computing system, and via the service mesh gateway.
Raghuram teaches to a service mesh gateway of a high-performance computing system, and via the service mesh gateway (Raghuram, paragraphs 0109, 0119-0122, and 0139 the “IoT network, arranged as a mesh network” and “managing service meshes” including edge devices).
Further, Street at least implies mounting a directory of a first file system of the high-performance computing system to a second file system of the edge computing system to provide an extended file system (see mappings above); however, Raghuram teaches mounting a directory of a first file system of the high-performance computing system to a second file system of the edge computing system to provide an extended file system (paragraphs 0051 and 0055-0058 teach creating an API connection (extended file system) and “TKAB interfaces with a key management system (KMS) to perform a cryptographic key operation. The TKAB may use a plugin to interface with an API at the KMS. A response is received from the KMS”).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to implement Raghuram’s teachings of API connection between mesh devices and cryptographic key management into Street‘s teaching of establishing cryptographic communications between IoT and new edge devices in a system in order to “the risk of exposing it to the rest of the system, thereby reducing the potential for sensitive data to be exposed while providing a higher degree of control and transparency for users” (Raghuram, paragraphs 0020, 0051 and 0055-0058).
Regarding claim 15, the combination of Street and Raghuram teach all the claim limitations of claim 14 above; and further teach wherein the instructions, when executed by the machine, further cause the machine to, responsive to the communications, provide, to the high-performance computing system, data representing a file directory of the first file system (Street, paragraphs 0052, 0055-0058, 0060, and 0069 teach detecting new edge devices, where “the cryptographic information about edge device 411 is communicated from provisioning service 415 (second file system of the edge computing system) to edge device 411 (first file system of the high-performance computing system)…The cryptographic information may also include credentials, the hostname of the selected IoT support service 451, connectivity information for edge device 411 to connect with IoT support service 451, and/or the like (provide an extended file system)” and stored on the respective devices (file systems)).
Regarding claim 16, the combination of Street and Raghuram teach all the claim limitations of claim 14 above; and further teach wherein the instructions, when executed by the machine, further cause the machine to transfer a file stored in a storage resource associated with the edge computing system to the high-performance computing system (Street, paragraphs 0052, 0055-0058, 0060, and 0069 teach detecting new edge devices, where “the cryptographic information about edge device 411 is communicated from provisioning service 415 (transfer a file stored in a storage resource associated with the edge computing system) to edge device 411 (to the high-performance computing system)…The cryptographic information may also include credentials, the hostname of the selected IoT support service 451, connectivity information for edge device 411 to connect with IoT support service 451, and/or the like (provide an extended file system)” and stored on the respective devices (file systems)).
Regarding claim 17, the combination of Street and Raghuram teach all the claim limitations of claim 14 above; and further teach wherein the instructions, when executed by the machine, further cause the machine to transfer a file stored in a storage resource associated with the high-performance computing system to the edge computing system (Street, paragraphs 0052, 0055-0058, and 0060-0069 teach communicating data from the edge node to the IoT device).
Regarding claim 18, Street teaches a first computing system comprising: a plurality of compute nodes that perform parallel processing jobs associated with an edge computing system (paragraphs 0031, 0035-0041, 0052, 0055-0058, and 0060-0069 teach a computing device with a user interface in a “distributed system” including edge devices executing multiple module tasks; “Moreover, input interface 260 and/or output interface 270 may include or be interfaced to any number or type of peripherals”); and
an edge manager endpoint that:
authenticates an interface instance of the edge computing system based on a cryptographic authentication token provided by the interface instance (paragraphs 0052, 0055-0058, and 0069 teach detecting new edge devices (high-performance computing system external to the edge computing system), where “the cryptographic information about edge device 411 is communicated from provisioning service 415 to edge device 411 (providing…a cryptographic authentication token to an endpoint instance)…The cryptographic information may also include credentials, the hostname of the selected IoT support service 451, connectivity information for edge device 411 to connect with IoT support service 451, and/or the like”);
responsive to successful authentication of the interface instance, forms a connection between the edge manager endpoint and the interface instance (paragraphs 0041 teach “Each of the IoT devices 341-343, and/or the devices that comprise IoT support service 351 and/or application back-end 313 and/or gateway devices 311 and 312 and/or provision service device 315 may include examples of computing device 200 of FIG. 2”; further paragraphs 0052, 0055-0058, and 0069 teach communication connections between the edge device (endpoint instance) and IoT support service devices (user interface)); and
sends, to the interface instance, a request over the connection to move a file between a first location of an extended file system associated with the edge computing system and a second location of the extended file system associated with the first computing system (paragraphs 0052, 0055-0058, 0060, and 0069 teach detecting new edge devices, where “Edge device 411 may have an endpoint uniform resource indicator (URI) that is installed in the factory. In some examples, on first power-up and first boot-up, edge device 411 is cryptographically guaranteed to connect to provisioning service 415 and not elsewhere (responsive to receiving, by the user interface instance, a request from the high-performance computing system via the connection, initiating, by the user interface instance)”; and “the cryptographic information about edge device 411 is communicated from provisioning service 415 (second file system of the edge computing system) to edge device 411 (first file system of the high-performance computing system)…The cryptographic information may also include credentials, the hostname of the selected IoT support service 451, connectivity information for edge device 411 to connect with IoT support service 451, and/or the like (provide an extended file system)” and stored on the respective devices (file systems)).
Street at least implies a first location of an extended file system associated with the edge computing system and a second location of the extended file system associated with the first computing system (see mappings above); however, Raghuram teaches a first location of an extended file system associated with the edge computing system and a second location of the extended file system associated with the first computing system (paragraphs 0051 and 0055-0058 teach creating an API connection (extended file system) and “TKAB interfaces with a key management system (KMS) to perform a cryptographic key operation. The TKAB may use a plugin to interface with an API at the KMS. A response is received from the KMS”).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to implement Raghuram’s teachings of API connection between mesh devices and cryptographic key management into Street‘s teaching of establishing cryptographic communications between IoT and new edge devices in a system in order to “the risk of exposing it to the rest of the system, thereby reducing the potential for sensitive data to be exposed while providing a higher degree of control and transparency for users” (Raghuram, paragraphs 0020, 0051 and 0055-0058).
Regarding claim 19, the combination of Street and Raghuram teach all the claim limitations of claim 18 above; and further teach the parallel processing jobs process input data provided by the edge computing system; and the edge computing system manager, responsive to the access, transfers the input data from the edge computing system to the first computing system (Street, paragraphs 0052, 0055-0058, and 0060-0069 teach “After provisioning is complete, in some examples, communications between edge device 411 and IoT support service 451 may occur directly and/or in a “normal” fashion”, wherein the edge device can send data and the IoT device can send modules for adding “new functionality” to the device (transfers the input data from the edge computing system to the first computing system)).
Claims 10-13 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Street et al (US Pub 20180332117) hereinafter Street, in view of Raghuram et al (US Pub 20240022550) hereinafter Raghuram, in view of Sommer et al (US Pub 20170357910) hereinafter Sommer.
Regarding claim 10, the combination of Street and Raghuram teach all the claim limitations of claim 1 above; however, while Raghuram teaches machine learning training and processes on devices, the combination does not explicitly teach performing, by the edge computing system, machine learning inference associated with a machine learning model; and training, by the high-performance computing system, the machine learning model.
Sommer teaches performing, by the edge computing system, machine learning inference associated with a machine learning model; and training, by the high-performance computing system, the machine learning model (paragraphs 0010-0014, 0024, and Fig. 1 teach an “AI cloud service” (edge computing system) on a server simulating ML models (performing…machine learning inference) and interfacing with mobile devices (high-performance computing system) by transmitting an AI model update or update trigger over a network to replace or change the AI models and/or the AI model weights on different mobile devices that host and run AI model such as neural networks (training…the machine learning model)).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Street‘s teaching of establishing cryptographic communications between IoT and new edge devices in a system, as modified by Raghuram’s teachings of API connection between devices and cryptographic key management, to include ML model parameter transmissions and training between devices taught by Sommer in order to improve “speed, accuracy, precision, or processing time of the AI model” (Sommer, paragraphs 0010-0014, 0024, and Fig. 1).
Regarding claim 11, the combination of Street, Raghuram, and Sommer teach all the claim limitations of claim 10 above; and further teach wherein initiating the operation comprises: initiating an operation to transfer data associated with the machine learning inference from the edge computing system to the high-performance computing system (Sommer, paragraphs 0010-0014, 0024, and Fig. 1 teach an “AI cloud service” (edge computing system) on a server simulating ML models (machine learning inference) and interfacing with mobile devices (high-performance computing system) by transmitting an AI model update or update trigger over a network (initiating an operation to transfer data associated with the machine learning inference) to replace or change the AI models and/or the AI model weights on different mobile devices that host and run AI model such as neural networks).
Street, Raghuram, and Sommer are combinable for the same rationale as set forth above with respect to claim 10.
Regarding claim 12, the combination of Street and Raghuram teach all the claim limitations of claim 10 above; and further teach wherein initiating the operation comprises: initiating an operation to transfer data associated with parameters of the machine learning model from the high-performance computing system to the edge computing system (Sommer, paragraphs 0010-0014, 0024, and Fig. 1 teach an “AI cloud service” (edge computing system) on a server simulating ML models (machine learning inference) and interfacing with mobile devices (high-performance computing system) by transmitting an AI model update or update trigger over a network (initiating an operation to transfer data associated with parameters) to replace or change the AI models and/or the AI model weights on different mobile devices that host and run AI model such as neural networks).
Street, Raghuram, and Sommer are combinable for the same rationale as set forth above with respect to claim 10.
Regarding claim 13, the combination of Street and Raghuram teach all the claim limitations of claim 10 above; and further teach receiving, by the user interface instance, a request to transfer a file associated with the machine learning inference to the high-performance computing system; and transferring, by the edge computing system, the file to the high-performance computing responsive to the request (Sommer, paragraphs 0010-0014, 0024, and Fig. 1 teach an “AI cloud service” (edge computing system) on a server simulating ML models (machine learning inference) receiving data from mobile devices for model updates (receiving…a request to transfer a file associated with the machine learning inference to the high-performance computing system) by transmitting an AI model update or update trigger over a network (transferring, by the edge computing system, the file to the high-performance computing responsive to the request) to replace or change the AI models and/or the AI model weights on different mobile devices that host and run AI model such as neural networks).
Street, Raghuram, and Sommer are combinable for the same rationale as set forth above with respect to claim 10.
Regarding claim 20, the combination of Street and Raghuram teach all the claim limitations of claim 18 above; and further teach the edge computing system performs machine learning-based inference based on a machine learning model; the parallel processing determines parameters for the machine learning model; and the edge computing system manager, responsive to the access, transfers the data representing the parameters from the first computing system to the edge computing system (Sommer, paragraphs 0010-0014, 0024, and Fig. 1 teach an “AI cloud service” (edge computing system) on a server simulating ML models (machine learning inference) receiving data from mobile devices for model updates (receiving…a request to transfer a file associated with the machine learning inference to the high-performance computing system) by transmitting an AI model update or update trigger over a network (transferring, by the edge computing system, the file to the high-performance computing responsive to the request) to replace or change the AI models and/or the AI model weights on different mobile devices that host and run AI model such as neural networks).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Street‘s teaching of establishing cryptographic communications between IoT and new edge devices in a system, as modified by Raghuram’s teachings of API connection between devices and cryptographic key management, to include ML model parameter transmissions and training between devices taught by Sommer in order to improve “speed, accuracy, precision, or processing time of the AI model” (Sommer, paragraphs 0010-0014, 0024, and Fig. 1).
Prior Art
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Amini et al (US Pub 20230386207) teach cryptographic hash utilizing machine learning and edge computing in a mesh network.
Conclusion
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/C.M./Examiner, Art Unit 2123
/ALEXEY SHMATOV/Supervisory Patent Examiner, Art Unit 2123
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