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
1. This action is in response to application 18/058,978, filed on 11/28/2022.
Oath/Declaration
Applicant’s oath or declaration filed on 11/28/2022 are approved by the office.
Drawings
The drawings and specifications filed on 11/28/2022 are approved by the office.
Information Disclosure Statement
IDS filed on 11/28/2022 has been considered.
Claim Rejections – 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale or otherwise available to the public before the effective filing date of the claimed invention.
5. Claims 1-20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Ozgur et al. (USPUB# 2021/0105338 A1).
Regarding Claim 1, Ozgur disclosed a computer-implemented method for multi-device ecosystem management, the computer-implemented method comprising:
identifying a plurality of devices in a multi-device ecosystem, including a set of specifications and a relative position corresponding to each respective device of the plurality of devices, wherein the multi-device ecosystem works together to perform an activity (see para [0024]-[0035] Table 2 and Table 4 showing location requirements to meet QOS parameters during playback);
selecting a primary device from the plurality of devices in the multi-device ecosystem based on an analysis of the set of specifications and the relative position corresponding to each respective device, wherein the primary device has sufficient data processing capabilities to coordinate and control actions of secondary devices in the multi-device ecosystem and has a communication connection with each of the secondary devices to facilitate completion of the activity (see para [0024]-[0035], [0073] and [0084]);
determining a set of requirements to complete the activity by the multi-device ecosystem; and completing the activity in accordance with the set of requirements by the multi-device ecosystem as coordinated and controlled by the primary device (see para [0024]-[0035] and [0084]).
Claim 10 recites A multi-device ecosystem that further includes limitations that are substantially similar to claim 1. Ozgur disclosed A multi-device ecosystem (see Fig.6 and [0079]). As such, is rejected under the same rationale as above.
Claim 15 recites A computer program product that further includes limitations that are substantially similar to claim 1. Ozgur disclosed A computer program product (see Fig.6 and [0079]). As such, is rejected under the same rationale as above. Applicant’s specifications at para. [0079] explicitly define the storage media as non-transitory, therefore no 35 USC 101 rejection is rendered regarding the computer storage medium claims.
7. Regarding Claims 2, 11 and 16, Ozgur disclosed the computer-implemented method of claim 1, further comprising: recording data corresponding to the completion of the activity by the primary device and the secondary devices of the multi-device ecosystem under a current contextual situation corresponding to the activity; and updating a knowledge corpus of each respective device of the plurality of devices in the multi-device ecosystem with the data corresponding to the completion of the activity under the current contextual situation corresponding to the activity (see para [0024]-[0035], [0073] and [0084]).
8. Regarding Claims 3, 12 and 17, Ozgur disclosed the computer-implemented method of claim 1, further comprising: performing an analysis of a knowledge corpus of the primary device selected to coordinate and control actions of the secondary devices to perform the activity under a current contextual situation corresponding to the activity; detecting that the primary device does not have needed information to coordinate and control the actions of the secondary devices to perform the activity under the current contextual situation corresponding to the activity based on the analysis of the knowledge corpus of the primary device; and adding by a secondary device the needed information to the knowledge corpus of the primary device for coordinating and controlling the actions of the secondary devices to perform the activity under the current contextual situation corresponding to the activity (see para [0024]-[0035], [0073-0078] and [0084]).
9. Regarding Claims 4, 13 and 18, Ozgur disclosed the computer-implemented method of claim 1, further comprising: determining that the primary device is leaving the multi-device ecosystem; and sharing by the primary device a knowledge corpus of the primary device with a newly selected primary device for continued coordination and control of the secondary devices to perform the activity under a current contextual situation without interruption prior to the primary device leaving the multi-device ecosystem (see para [0024]-[0035], [0073-0078] and [0084]).
10. Regarding Claims 5, 14 and 19, Ozgur disclosed the computer-implemented method of claim 1, further comprising: detecting that a current contextual situation corresponding to the activity has changed to a new contextual situation in relation to the primary device and the secondary devices of the multi-device ecosystem; determining whether selection of a different primary device is needed based on the new contextual situation corresponding to the activity; and selecting the different primary device to coordinate and control the actions of the secondary devices to perform the activity under the new contextual situation corresponding to the activity in response to determining that selection of the different primary device is needed based on the new contextual situation corresponding to the activity (see para [0024]-[0035], [0073-0078] and [0084]).
11. Regarding Claims 6 and 20, Ozgur disclosed the computer-implemented method of claim 5, further comprising: changing to the different primary device to coordinate and control the actions of the secondary devices to perform the activity under the new contextual situation corresponding to the activity prior to completion of the activity (see para [0024]-[0035], [0073-0078] and [0084]).
12. Regarding Claims 7, Ozgur disclosed the computer-implemented method of claim 1, wherein the completion of the activity includes identification of each different contextual situation addressed by each different primary device to coordinate and control the completion of the activity by the multi-device ecosystem (see para [0024]-[0035], [0073-0078] and [0084]).
13. Regarding Claims 8, Ozgur disclosed the computer-implemented method of claim 1, further comprising: identifying a relay secondary device that can receive commands from the primary device; and relaying by the relay secondary device the commands to other secondary devices in the multi-device ecosystem that are beyond communication range of the primary device (see para [0024]-[0035], [0073-0078] and [0084]).
14. Regarding Claims 9, Ozgur disclosed the computer-implemented method of claim 1, further comprising: sending by each of the secondary devices in the multi-device ecosystem a data stream to the primary device in order for the primary device to coordinate and control the secondary devices effectively and efficiently during performance of the activity (see para [0024]-[0035], [0073-0078] and [0084]).
Conclusion
Relevant Prior Art Not Relied Upon
The prior art made of record and not relied upon is considered pertinent to Applicant's disclosure. The additional cited art, including but not limited to the excerpts below, further establishes the state of the art at the time of Applicant’s invention and shows the following was known:
A controller intermediary to clients and servers of a cloud environment can receive account information related to each of a plurality of instances of one or more services provided by the servers of the cloud environment. The controller can determine a weight for each of the instances based on the account information. The weight can indicate a performance of the instance of the service provided via the cloud environment. The controller can select an instance of the plurality of instances to direct network traffic from a client. The controller can select the instance based on the weight for each of the instances. (Paramasivam ‘451)
Techniques for serving a manifest file of an adaptive streaming video include receiving a request for the manifest file from a user device. The video is encoded at different reference bitrates and each encoded reference bitrate is divided into segments to generate video segment files. The manifest file includes an ordered list of universal resource locators (URLs) that reference a set of video segment files encoded at a particular reference bitrate. A source manifest file that indicates the set of video segment files is identified based on the request. An issued manifest file that includes a first URL and a second URL is generated based on the source manifest file. The first URL references a first domain and the second URL references a second domain that is different from the first domain. The issued manifest file is transmitted to the user device as a response to the request.. (Gordon ‘516)
The design and operation of any network are complex processes that require the evaluation, utilization and configuration of a variety of usually expensive network devices. Through the use of an emulation platform, network operators are able to examine different scenarios and network parameters and benefit from multi-objective decision mechanisms. These enable the decrease of the network design phase duration and the optimal operation of the network under different well examined conditions. In this work, we present an emulation platform for SDN-enabled 5G integrated Fiber-Wireless networks that provides a transparent view of the 5G infrastructure to any SDN-based control plane. We present the overall architecture and design of the emulator, along with the implementation details of its main components. Network devices are described through YANG models and are emulated using containerized processes, configured and managed through the Network Configuration (NETCONF) protocol. Finally, a number of emulation scenarios are described and evaluated, utilizing a joint fiber and wireless resource allocation algorithm that drives the SDN-enabled devices. (Kretsis et al. “An SDN Emulation Platform for Converged Fiber-Wireless 5G Networks”)
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/DAVOUD A ZAND/Primary Examiner, Art Unit 2445
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