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 .
Claims 1-15 are pending.
Response to Arguments
Applicant’s double patenting and 102 anticipation arguments with respect to claims 1, 6 and 11 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
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Claims 1-3, 5-8, 10-13 and 15 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-3, 5-8, 10-13 and 15 of U.S. Patent No. 12141620 (hereinafter ‘620), in view of Narasimhan US 20170201597.
Each of the instant, enumerated claims in following table is anticipated by a correspondingly mapped ‘620 claim except for independent claim limitations:
“the distributed computing system is to execute one or more of: one or more container applications for use in association with the IoT resources and the providing of the at least one cloud service; and one or more virtual machine applications for use in association with the IoT resources and the providing of the at least one cloud service; and the distributed computing system is to dynamically deploy, based upon service level agreement data and quality of service data, the one or more container applications and the one or more virtual machine applications to physical resources of the distributed computing system”.
However, in a related field, Narasimhan discloses a system for provisioning of application containers within a datacenter for use in cloud services. (par. 0024). SLAs, including quality of service options, associated with a customer, business unit, or type of application are assigned to application containers (par. 0027, 0049).
It would have been obvious to one of ordinary skill before effective filing date of instant claimed invention to have introduced ‘s teachings alongside ‘620. The motivation to combine would have been to utilize well-known SLA governed provisioning of resources to achieve expected goal of ensuring delivery of legally contracted performance and availability of services to customers/tenants (Narasimhan, par. 0026, 0027).
Instant claims
‘620 claims
1, 6, 11. Distributed computing system configurable for use in association with providing at least one cloud service associated with Internet of Things (IoT) resources, the distributed computing system comprising: processing hardware; and machine-readable memory storing instructions for being executed by the processing hardware, the instructions, when executed by the processing hardware, resulting in the distributed computing system being configured for performance of operations comprising:
determining, based upon telemetry data, metrics data, and machine-learning, whether at least one condition is present; and
in event that the at least one condition is determined to be present, determining at least one responsive action to be taken; wherein:
[1] the telemetry data is associated with IoT-resource-related object data; and
the IoT-resource-related object data is configurable to indicate one or more of:
behaviors related to the IoT resources;
states related to the IoT resources; and interactions related to the IoT resources.
2, 7, 12. The distributed computing system of claim 1, wherein: the at least one responsive action is configurable to result in one or more of: alert data; and taking at least one other action (maps to ‘620, claims 1, 6 and 11 limitation “determining at least one action to be taken in response to the determination that the at least one condition is present”) .
3, 8, 13. The distributed computing system of claim 1, wherein: modeling data is to be used in association with the IoT-resource-related object data; and the modeling data is for use in association with one or more of: behavior modeling; and failure event data.
3, 8, 13. The distributed computing system of claim 1, wherein: modeling data is to be used in association with the IoT-resource-related object data; and the modeling data is for use in association with one or more of: behavior modeling; and failure event data.
5, 10, 15. The distributed computing system of claim 1, wherein: one or more of the IoT resources are associated with one or more of: at least one vehicle; at least one emergency vehicle; at least one temperature sensor; at least one weather sensor; at least one alarm system; at least one camera; at least one traffic monitor; and at least one traffic light.
1, 6, 11. Distributed computing system configurable for use in association with providing at least one cloud service associated with Internet of Things (IoT) resources, the distributed computing system comprising: computing hardware; and machine-readable memory storing instructions for being executed by the computing hardware, the instructions, when executed by the computing hardware, resulting in the distributed computing system being configured for performance of operations comprising:
associating the IoT resources with IoT-related objects;
[1] receiving telemetry data associated, at least in part, with the IoT-related objects;
generating, based upon the telemetry data, at least one of IoT resource health-related data and event management-related data; and
based upon determination, based upon the telemetry data and associated metrics data, that at least one condition is present,
determining at least one action to be taken in response to the determination that the at least one condition is present; wherein:
the IoT-related objects are configurable to comprise object data to indicate at least one of behaviors, states, and interactions that are in association with the IoT resources;
the distributed computing system is configurable to utilize machine-learning in association with the determination that the at least one condition is present; and
the distributed server system is configurable to monitor central processing unit (CPU) usage and memory usage in association with the telemetry data.
2, 7, 12. The distributed computing system of claim 1, wherein: the operations also comprise generating modeling data for use in association with the IoT-related objects; and the modeling data is for use in association with failure event data.
3, 8, 13. The distributed computing system of claim 2, wherein: the modeling data is for use in association with behavior modeling.
5, 10, 15. The distributed computing system of claim 1, wherein: one or more of the IoT resources are associated with one or more of: at least one vehicle; at least one emergency vehicle; at least one temperature sensor; at least one weather sensor; at least one alarm system; at least one camera; at least one traffic monitor; and/or at least one traffic light.
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.
Claims 1-15 are rejected under 35 U.S.C. 103 as being unpatentable over Yang US 20180375720, in view of Narasimhan US 20170201597.
For claims 1, 6 and 11, Yang discloses:
Distributed computing system configurable for use in association with providing at least one cloud service associated with Internet of Things (IoT) resources (par. 0020: distributed IoT management system disclosed; par. 0022: Cloud-based geolocation and computational services disclosed; par. 0014: IoT system comprising plurality of devices/assets 105), the distributed computing system comprising:
processing hardware (par. 0036: computer processor apparatus disclosed); and
machine-readable memory storing instructions for being executed by the processing hardware, the instructions, when executed by the processing hardware, resulting in the distributed computing system being configured for performance of operations comprising:
determining, based upon telemetry data, metrics data, and machine-learning, whether at least one condition is present (par. 0056: “During operation of an asset 105 in an IoT system governed by application 418, telemetry logic 426 of the asset 105 can collect data generated by various sensors provisioned within the asset 105 describing performance attributes and state of the asset 105 during operation. Operating status 428 and status changes can be determined from the sensor data (e.g., by machine learning logic of the asset 105”). Par. 0056: Furthermore, assets 105 periodically send local model 432 data to management system 1540 of IoT system.)); and
in event that the at least one condition is determined to be present, determining at least one responsive action to be taken (par. 0059: “An out-of-service condition (e.g., at 446) or other operating status 428 detected at a particular asset (e.g., 105) can prompt remediation at the system level by the management system 150….Assets can also escalate issues (e.g., out-of-service conditions) detected in real-time at the asset to prompt the management system to initiate a wider reconfiguration or redeployment (e.g., in response to self-healing or other tasks performed at the asset failing to resolve the issue(s)).”);
wherein:
the telemetry data is associated with IoT-resource-related object data (par. 0056: “…telemetry logic 426 of the asset 105 can collect data generated by various sensors provisioned within the asset 105”);
the IoT-resource-related object data is configurable to indicate one or more of:
behaviors related to the IoT resources; states related to the IoT resources; and interactions related to the IoT resources (par. 0058 and 0059: Local asset 105 reconfiguration taught in light of observed/reporting operating status conditions. Management system 150 performs remediation of detected asset 105 problems).
Yang fails to explicitly disclose:
“the distributed computing system is to execute one or more of:
one or more container applications for use in association with the IoT resources and the providing of the at least one cloud service; and
one or more virtual machine applications for use in association with the IoT resources and the providing of the at least one cloud service; and
the distributed computing system is to dynamically deploy, based upon service level agreement data and quality of service data, the one or more container applications and the one or more virtual machine applications to physical resources of the distributed computing system”
However, in a related field, Narasimhan discloses a system for provisioning of application containers within a datacenter for use in cloud services. (par. 0024). SLAs, including quality of service options, associated with a customer, business unit, or type of application are assigned to application containers (par. 0027, 0049).
It would have been obvious to one of ordinary skill before effective filing date of instant claimed invention to have introduced ‘s teachings alongside ‘620. The motivation to combine would have been to utilize well-known SLA governed provisioning of resources to achieve expected goal of ensuring delivery of legally contracted performance and availability of services to customers/tenants (Narasimhan, par. 0026, 0027).
For claims 2, 7 and 12, Yang-Narasimhan discloses:
The distributed computing system of claim 1, wherein:
the at least one responsive action is configurable to result in one or more of: alert data; and taking at least one other action (Yang, par. 0059: Response to a change in operating status include “[r]edeployment 458…can involve redeploying the same collection of assets (including asset 105), but with an adjustment to the configuration of the overall system (or one or more devices) as determined by the management system 150 from the global model.)”.
For claims 3, 8 and 13, Yang-Narasimhan discloses:
The distributed computing system of claim 1, wherein:
modeling data is to be used in association with the IoT-resource-related object data (Yang, par. 0043: “The global model 225 can include component models modeling each of a collection of taxonomies, or device abstractions, as well as model specific one or more of the devices known to the management system 150 and falling within one or more of the taxonomies. The global model 255 can be derived from or updated based on copies of local models 230 maintained locally at IoT assets (e.g., 105a-b, 125)…”; and
the modeling data is for use in association with one or more of: behavior modeling; and failure event data (Yang, par. 0049: “…the global resiliency manager 210 can utilize the global model to identify and forecast events affecting a portion of a broader IoT system (e.g., two or more assets) and can utilize functionality of the IoT management system 150 to restart or reconfigure two or more devices in a system (e.g., using device manager 214)…”).
For claims 4, 9 and 14, Yang-Narasimhan discloses:
The distributed computing system of claim 1, wherein:
the distributed computing system is to execute one or more workloads for use in association with the IoT resources and the providing of the at least one cloud service (Yang, par. 0031: “…a scalable system management framework for resilient Internet of Things (IOT) systems is provided that facilitates the ability of IOT applications or services to dynamically adapt to changes in the system (e.g., battery level change, microprocessor idle time, network topology, device workload change, etc.)”; Yang, par. 0022: IoT systems interface with cloud-based services).
For claims 5, 10 and 15, Yang-Narasimhan discloses:
The distributed computing system of claim 1, wherein:
one or more of the IoT resources are associated with one or more of: at least one vehicle; at least one emergency vehicle; at least one temperature sensor; at least one weather sensor; at least one alarm system; at least one camera; at least one traffic monitor; and at least one traffic light (Yang, par. 0018: IoT devices include HVAC controllers and vehicle interior/exterior sensors).
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CLAYTON R WILLIAMS whose telephone number is (571)270-3801. The examiner can normally be reached M-F 10:00am - 6:00pm.
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/CLAYTON R WILLIAMS/Primary Examiner, Art Unit 2443
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