DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claims 1 – 20 are pending. Claims 1 and 13 are amended.
Examiner’s Note
The prior art rejection below cites particular paragraphs, columns, and/or line numbers in the references for the convenience of the applicant. Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested that, in preparing responses, the applicant fully consider the references in their entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art.
Priority
Should applicant desire to obtain the benefit of foreign priority under 35 U.S.C. 119(a)-(d) prior to declaration of an interference, a certified English translation of the foreign application must be submitted in reply to this action. 37 CFR 41.154(b) and 41.202(e).
Failure to provide a certified translation may result in no benefit being accorded for the non-English application.
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 therefore, subject to the conditions and requirements of this title.
Claims 1 - 20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
As to claim 1, the claim recites
An instance deployment method, wherein the method comprises:
Obtaining, by a server, a resource requirement of a service, wherein the server manages resources of a central cloud and an edge cloud; and
allocating, by the server, the resources of the central cloud and the edge cloud to deploying instances of the service across a central cloud and an edge cloud based on the resource requirement of the service.
Step 2A:
Prong 1: the limitations of " An instance deployment method” and
“allocating, by the server, the resources of the central cloud and the edge cloud to deploying instances of the service across a central cloud and an edge cloud based on the resource requirement of the service” recite mental processes since "calculating", "determining", and "identifying" are all functions that can be reasonably performed in the human mind including observations and with or without the use of pen and paper through observation, evaluation, judgement and opinion.
Prong 2: the additional element of "obtaining a resource requirement of a service" and “wherein the server manages resources of a central cloud and an edge cloud“ merely recite insignificant extra solution activity such as gathering, displaying, updating, transmitting and storing data which does not integrate the judicial exception into a practical application. See MPEP 2106.05(d).
The addition element “by a server” merely recite instructions to implement an abstract idea on a generic computer, or merely uses a generic computer or computer components as a tool to perform the abstract idea.
Thus, these additional elements do not integrate the judicial exception into a practical application.
Step 2B: the additional element of "obtaining a resource requirement of a service" and “wherein the server manages resources of a central cloud and an edge cloud“ merely recite insignificant extra solution activity such as gathering, displaying, updating, transmitting and storing data which does not integrate the judicial exception into a practical application. See MPEP 2106.05(d).
The addition element “by a server” merely recite instructions to implement an abstract idea on a generic computer, or merely uses a generic computer or computer components as a tool to perform the abstract idea.
Accordingly, the additional elements do not amount to significantly more than the abstract idea.
As to claim 2, The method according to claim 1, wherein the method further comprises:
obtaining deployment location information of the service merely recite insignificant extra solution activity such as gathering, displaying, updating, transmitting and storing data which does not integrate the judicial exception into a practical application. See MPEP 2106.05(d), wherein the deployment location information is used to separately determine one or more availability zones from the central cloud and the edge cloud to obtain N availability zones, and the N availability zones are used for deploying the instances of the service recite mental processes since "calculating", "determining", and "identifying" are all functions that can be reasonably performed in the human mind including observations and with or without the use of pen and paper through observation, evaluation, judgement and opinion.
As to claim 3, The method according to claim 2, wherein obtaining the deployment location information of the service comprises: obtaining the deployment location information of the service input by a user merely recite insignificant extra solution activity such as gathering, displaying, updating, transmitting and storing data which does not integrate the judicial exception into a practical application. See MPEP 2106.05(d).
As to claim 4, The method according to claim 2, wherein the deployment location information comprises at least one of a geographical location level or a geographical location name merely recite insignificant extra solution activity such as gathering, displaying, updating, transmitting and storing data which does not integrate the judicial exception into a practical application. See MPEP 2106.05(d).
As to claim 5, The method according to claim 2, wherein the deployment location information comprises at least one of a target area or a target availability zone merely recite insignificant extra solution activity such as gathering, displaying, updating, transmitting and storing data which does not integrate the judicial exception into a practical application. See MPEP 2106.05(d).
As to claim 6, The method according to claim 2, wherein the deployment location information further comprises a priority of each of the N availability zones merely recite insignificant extra solution activity such as gathering, displaying, updating, transmitting and storing data which does not integrate the judicial exception into a practical application. See MPEP 2106.05(d).
As to claim 7, The method according to claim 2, wherein the method further comprises: obtaining a deployment strategy merely recite insignificant extra solution activity such as gathering, displaying, updating, transmitting and storing data which does not integrate the judicial exception into a practical application. See MPEP 2106.05(d), wherein the deployment strategy is used to determine distribution of the instances of the service in the N availability zones recite mental processes since "calculating", "determining", and "identifying" are all functions that can be reasonably performed in the human mind including observations and with or without the use of pen and paper through observation, evaluation, judgement and opinion.
As to claim 8, The method according to claim 7, wherein the deployment strategy recite mental processes since "calculating", "determining", and "identifying" are all functions that can be reasonably performed in the human mind including observations and with or without the use of pen and paper through observation, evaluation, judgement and opinion comprises any one of geographical centralization, geographical dispersion, costs first, data synchronization, latency first, and performance first merely recite insignificant extra solution activity such as gathering, displaying, updating, transmitting and storing data which does not integrate the judicial exception into a practical application. See MPEP 2106.05(d).
As to claim 9, The method according to claim 7, wherein the resource requirement comprises a resource type, a quantity of required resources, and M resource specifications, and M is a positive integer merely recite insignificant extra solution activity such as gathering, displaying, updating, transmitting and storing data which does not integrate the judicial exception into a practical application. See MPEP 2106.05(d).
As to claim 10, The method according to claim 9, wherein deploying the instances of the service across the central cloud and the edge cloud comprises:
for each of the M resource specifications, determining a quantity of first instantiations of each resource specification in each of the N availability zones; and if a sum of quantities of first instantiations of each resource specification in all the availability zones is greater than or equal to the quantity of required resources, determining, based on the first instantiations of each resource specification in each availability zone, the resource requirement, and the deployment strategy, a quantity of second instantiations of each resource specification in each availability zone, and deploying the instances of the service based on the quantity of second instantiations of each resource specification in each availability zone recite mental processes since "calculating", "determining", and "identifying" are all functions that can be reasonably performed in the human mind including observations and with or without the use of pen and paper through observation, evaluation, judgement and opinion.
As to claim 11, The method according to claim 9, wherein the resource type comprises at least one of a virtual machine, a docker, or a bare metal server merely recite insignificant extra solution activity such as gathering, displaying, updating, transmitting and storing data which does not integrate the judicial exception into a practical application. See MPEP 2106.05(d).
As to claim 12, The method according to claim 2, wherein the method further comprises: if the N availability zones cannot meet the resource requirement of the service, prompting a user of a deployment failure recite mental processes since "calculating", "determining", and "identifying" are all functions that can be reasonably performed in the human mind including observations and with or without the use of pen and paper through observation, evaluation, judgement and opinion.
As to claim 13, this is a computing device of claim 1. See rejection for claim 1 above.
As to claims 14 – 20, these claims recite similar scope of claims 2 – 9. See rejection for claims 2 - 9 above.
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.
Claims 1 and 13 are rejected under 35 U.S.C. 103 under 35 U.S.C. 103 as being unpatentable over Spoczynski et al., (US PUB 2020/0228602 hereinafter Spoczynski in view of Choi et al., (US PUB 2021/0124617 hereinafter Choi).
Spoczynski was cited in previous office action.
As to claim 1, Spoczynski teaches An instance deployment method, wherein the method comprises:
Obtaining, [by a server], a resource requirement of a service (“...To achieve results with low latency, the services executed within the edge cloud 110 balance varying requirements in terms of: (a) Priority (throughput or latency) and Quality of Service (QoS) (e.g., traffic for an autonomous car may have higher priority than a temperature sensor in terms of response time requirement; or, a performance sensitivity/bottleneck may exist at a compute/accelerator, memory, storage, or network resource, depending on the application); (b) Reliability and Resiliency (e.g., some input streams need to be acted upon and the traffic routed with mission-critical reliability, where as some other input streams may be tolerate an occasional failure, depending on the application); and (c) Physical constraints (e.g., power, cooling and form-factor).” para. 0056) and (“..the measurement of the fulfillment of the agreement (to identify what elements are required by the system to conduct a service, how the system responds to service conditions and changes, and the like).” Para. 0069) and (“...This arrangement and other service management features described herein are designed to meet the various requirements of edge computing with its unique and complex resource and service interactions. This service management arrangement is intended to inherently address several of the resource basic services within its framework, instead through an agent or middleware capability. Services such as locate, find, address, trace, track, identify, register may be placed immediately in effect as resources appear on the framework...” para. 0079 and 0113) and (“..The main design challenges to run other services on the base station relate to: (1) limited space; (2) physical exposure that requires more security and better thermal solutions; (3) limited amount of power; (4) operating expense (OPEX) or total cost of ownership (TCO) derived from managing such a highly distributed compute environment....” para. 0107) and (“..Furthermore, 5G EDGE devices may also be included in the slice depending on the service latency requirements.” Para. 0211), [wherein the server manages resources of a central cloud and an edge cloud]; and
[allocating, by the server, the resources of the central cloud and the edge cloud]; and
deploying instances of the service across a central cloud and an edge cloud based on the resource requirement of the service (The following describes aspects of an edge cloud architecture that covers multiple potential deployments and addresses restrictions that some network operators or service providers may have in their own infrastructures. These include, variation of configurations based on the edge location (because edges at a base station level, for instance, may have more constrained performance and capabilities in a multi-tenant scenario); configurations based on the type of compute, memory, storage, fabric, acceleration, or like resources available to edge locations, tiers of locations, or groups of locations; the service, security, and management and orchestration capabilities; and related objectives to achieve usability and performance of end services” para. 0052) and (“..The deployment of a multi-stakeholder edge computing system may be arranged and orchestrated to enable the deployment of multiple services and virtual edge instances, among multiple edge nodes and subsystems, for use by multiple tenants and service providers. In a system example applicable to a cloud service provider (CSP), the deployment of an edge computing system may be provided via an “over-the-top” approach, to introduce edge nodes as a supplemental tool to cloud computing. In a contrasting system example applicable to a telecommunications service provider (TSP), the deployment of an edge computing system may be provided via a “network-aggregation” approach, to introduce edge nodes at locations in which network accesses (from different types of data access networks) are aggregated....” para. 0083) and (“..Different locations therefore may be usable across the edge cloud 110 to perform services management, as both compute resources are mapped to the workload data, and workload data instances are mapped to the compute resources. In a highly distributed architecture, the features are based on mapping services on the base station. In this case, the platform physical requirements in terms of power and space will mostly limit the amount of hardware that can be placed in this particular edge node. Furthermore, in order to get more service density, acceleration schemes such as hardware inference acceleration may be utilized. In a central office architecture, the architecture is less distributed but less power and space constrained according to the capabilities and servicing location of the central office...” para. 0121) and (“... On the other hand, a computing edge for a CDN workload may be hosted at a base station, at a central office, or at any other intermediate point of aggregation (POA or POP) of the operator infrastructure.” Para. 0179) and (“...Said any compute node may therefore have knowledge of various physical infrastructure devices of the edge computing system that are capable of providing a service to each service-requesting client. According to some other embodiments, orchestration by a compute node according to embodiments may be both logically and physically centralized.” Para. 0242).
While Spoczynski teaches edge cloud computing and edge node can be server, gateway and client (p. 0039, 0046, 0053, 0143), Spoczynski does not but Choi teaches wherein the server manages resources of a central cloud and an edge cloud (“…The server 100 is a central server performing data communication through a plurality of fog devices 210 and 220 or with the edge device 340, and may be a cloud server. The server 100 having a high-performance processor and hardware may process a plurality of tasks that are difficult to be processed by the plurality of fog devices 210 and 220 or the plurality of edge devices 310, 320, 330 and 340, and provide its result to the fog devices 210 and 220 or the plurality of edge devices 310, 320, 330 and 340. Specific configurations and functions of the server 100 will be described later with reference to FIGS. 3 to 17, and thus the detailed description thereof is omitted here” para. 0039) and by the server, allocating, by the server, the resources of the central cloud and the edge cloud (“…computing resource allocation function to an edge computing device, the edge computing system 1000 uses the central server 100 and the intermediate fog devices 210 and 220 to calculate current resource usage and future resource requirements of the edge devices 310, 320, 330 and 340, distributes edge modules to each of the edge devices 310, 320, 330 and 340, and provides a resource allocation value of a container, in which an edge module will be driven, in a way that computing resources can be the most efficiently utilized…”, figure 1 and associated text, especially para. 0050).
It 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 was made to modify Spoczynski by applying the teachings of Choi because Choi teaches the same field of resource allocation to edge computing device in edge cloud computing based on resource requirement (title, figure 1 and associated text). Spoczynski would implement server for allocating resources to edge computing devices before deploying the resources.
As to claim 13, this is a computing device claim of claim 1. See rejection for claim 1 above. Further, Spoczynski teaches at least one processor; and at least one memory coupled to the at least one processor and storing program instructions for execution by the at least one processor (“...the compute node 1500 includes or is embodied as a processor 1504 and a memory 1506...” para. 0135).
Claims 2 – 11 and 14 - 19 are rejected under 35 U.S.C. 103 as being unpatentable over Spoczynski in view of Choi, as applied to claims 1 and 13, and further in view of Dunsmore et al., (US PAT 11,425,054).
Qian was cited in previous office action.
As to claim 2, Spoczynski modified by Choi teaches The method according to claim 1, Spoczynski teaches wherein the method further comprises:
obtaining deployment location information of the service Within this arrangement, multiple considerations and capabilities are evaluated for the location and type of workload execution among devices of the edge computing system 10” para. 0109),
Spoczynski and Choi do not but Dunsmore teaches wherein the deployment location information is used to separately determine one or more availability zones from the central cloud and the edge cloud to obtain N availability zones, and the N availability zones are used for deploying the instances of the service (“...These deployment zone types can include traditional cloud provider regions and availability zones...” abstract) and (“.These deployment zones generally correspond to physical locations where the cloud provider network provides data centers or other compute capacity and can include deployment zones of various types, e.g., traditional cloud provider regions and availability zones as well as so-called edge locations (e.g., cloud provider operated edge locations, customer-operated edge locations, third-party operated edge locations, communications service provider (CSP) associated edge locations)....” col. 2 lines27 - 52).
It 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 was made to modify Spoczynski and Choi by applying the teachings of Dunsmore because Dunsmore would determine locations as well as availability zones to automatically deploy and scale and provide single or multi-services for users across both centralized and edge cloud in any of deployment zones (abstract, figure 13 and associated text).
As to claim 3, Spoczynski modified by Choi and Dunsmore teaches The method according to claim 2, Spoczynski teaches wherein obtaining the deployment location information of the service comprises:
obtaining the deployment location information of the service input by a user (“...FIG. 11 illustrates workload deployments and mapping to operational layers (e.g., corresponding to layers 1020-1070) of an edge computing system 1100. Within this arrangement, multiple considerations and capabilities are evaluated for the location and type of workload execution among devices of the edge computing system 10” para. 0109) and (A utility value according to some embodiments may be calculated for each subgroup of service-requesting clients against each candidate physical infrastructure device, using, as input, the average attribute values for location-related attributes...” para. 0246).
As to claim 4, Spoczynski modified by Dunsmore teaches The method according to claim 2, Spoczynski and Choi do not but Dunsmore teaches wherein the deployment location information comprises at least one of a geographical location level or a geographical location name (“...This SOADM service 102 can then dynamically select locations to deploy user applications, orchestrate underlying compute and networking resources, and streamline the collection of observability telemetry to a central location...” col. 23 lines 54 – 64).
See motivation for claim 2 above.
As to claim 5, Spoczynski modified by Choi and Dunsmore teaches The method according to claim 2, Spoczynski teaches wherein the deployment location information comprises at least one of a target area (“...As a result, the configuration of FIG. 14B may provide a suitable target for base station deployments...” para. 0130) or a target availability zone.
As to claim 6, Spoczynski modified by Choi and Dunsmore teaches The method according to claim 2, Spoczynski teaches wherein the deployment location information further comprises a priority (“...Top priorities for edge computing among various network layers include central office...” para. 0181)
Spoczynski and Choi do not but Dunsmore teaches of each of the N availability zones (“...availability zones...” abstract).
See motivation for claim 2 above.
As to claim 7, Spoczynski modified by Choi and Dunsmore teaches The method according to claim 2, Spoczynski and Choi do not but Dunsmore teaches wherein the method further comprises:
obtaining a deployment strategy, wherein the deployment strategy is used to determine distribution of the instances of the service in the N availability zones (“...Using such configurations, the SOADM service automatically deploys and scales simple or complex, single or multi-service applications for users across any number of deployment zones and deployment zone types.” abstract).
It 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 was made to modify Spoczynski and Choi by applying the teachings of Dunsmore because Dunsmore would determine locations as well as availability zones to automatically deploy and scale and provide single or multi-services for users across both centralized and edge cloud in any of deployment zones (abstract, figure 13 and associated text).
As to claim 8, Spoczynski modified by Choi and Dunsmore teaches The method according to claim 7, Spoczynski and Choi do not but Dunsmore teaches wherein the deployment strategy comprises any one of geographical centralization, geographical dispersion, costs first, data synchronization, latency first (“...he SOADM service 102 also provides latency-based scaling for components of a user application, which allows the application to be scaled to new locations to accommodate changes in localized demand, site availability, capacity availability, etc...” col. 24 lines 12 – 35), and performance first.
See motivation for claim 2 above.
As to claim 9, Spoczynski modified by Choi and Dunsmore teaches The method according to claim 7, Spoczynski teaches wherein the resource requirement comprises a resource type (“...In this case, the platform physical requirements in terms of power and space will mostly limit the amount of hardware that can be placed in this particular edge node...” para. 0121), a quantity of required resources, M resource specifications, and M is a positive integer.
As to claim 10, Spoczynski modified by Choi and Dunsmore teaches The method according to claim 9, Spoczynski and Choi do not but Dunsmore teaches wherein deploying the instances of the service across the central cloud and the edge cloud comprises:
for each of the M resource specifications, determining a quantity of first instantiations of each resource specification in each of the N availability zones (“In this example of FIG. 1, the deployment causes a set of service instances 152A-152N for an example “first” service of the service group (represented as black squares) to various deployment zone 118 locations—here, two instances to a CSP edge location 142A as shown at circle (3A), one instance to a cloud provider network-managed edge location 140A as shown at circle (3B), and one instance to each of a first AZ 114A and a second AZ 114B of a first region 112A as shown at circle (3C)....” col. 27 lines 37 – 67); and
if a sum of quantities of first instantiations of each resource specification in all the availability zones is greater than or equal to the quantity of required resources, determining, based on the first instantiations of each resource specification in each availability zone, the resource requirement, and the deployment strategy, a quantity of second instantiations of each resource specification in each availability zone, and deploying the instances of the service based on the quantity of second instantiations of each resource specification in each availability zone (“..As introduced earlier, the cloud provider network 100 (sometimes referred to simply as a “cloud”) refers to a pool of network-accessible computing resources (such as compute, storage, and networking resources, applications, and services), which can be virtualized or bare-metal. The cloud can provide convenient, on-demand network access to a shared pool of configurable computing resources that can be programmatically provisioned and released in response to user commands. These resources can be dynamically provisioned and reconfigured to adjust to variable load....” col. 6 lines 40 – 67) and (“...This placement may be localized at the beginning (e.g., only deploy to locations within or associated with a first region) and then scaled as needed based on client traffic/latency, distributed at the beginning (e.g., by placing resources in a wide number of locations, such as all locations or a random sampling of locations) and again scaled out or back based on traffic...” col. 27 lines 12 - 22).
It 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 was made to modify Spoczynski and Choi by applying the teachings of Dunsmore because Dunsmore’s system can be dynamically provisioned and reconfigured resources to scale up or down depending on demand of workload to save resources (col. 6 lines 35 – col. 7 lines 18 and col. 27).
As to claim 11, Spoczynski modified by Choi and Dunsmore teaches The method according to claim 9, Spoczynski teaches wherein the resource type comprises at least one of a virtual machine, a docker, or a bare metal server (“...the isolation environments may include: bare metal (dedicated) equipment, virtual machines, containers, virtual machines on containers, or combinations thereof...” para. 0090).
As to claims 14 – 19, these claims recite similar scope of claims 2 – 8. See rejection for claims 2 - 8 above.
Claims 12 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Spoczynski in view of Choi and Dunsmore, as applied to claims 2 and 14, and further in view of Qian et al., (US PUB 20160127201 hereinafter Qian).
Qian was cited in previous office action.
As to claim 12, Spoczynski modified by Choi and Dunsmore teaches The method according to claim 2, Spoczynski and Choi do not but Dunsmore teaches wherein the method further comprises: if the N availability zones cannot meet the resource requirement of the service (“...In some implementations, an edge location 116 can be an extension of the cloud provider network substrate including a limited quantity of capacity provided outside of an AZ (e.g., in a small data center or other facility of the cloud provider that is located close to a user workload and that may be distant from any AZs)...” col. 16 lines 46 – 65).
Spoczynski, Choi and Dunsmore do not but Qian teaches prompting a user of a deployment failure (“..deploy services 112 responsive to service orders 108, request and/or orchestrate allocation of physical network resources 114 and/or virtual network resources 116 to host the services 112, detect failure conditions on the network 104 (e.g., by receiving one or more alerts 118)....” para. 0034).
It 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 was made to modify Spoczynski, Choi and Dunsmore by applying the teachings of Qian because Qian would detect system failure to and alert users for fixing (para. 0034).
As to claim 20, this claim recites similar scope of claim 12. See rejection for claim 12 above.
Response to Arguments
Claim Rejections - 35 U.S.C. 101
Applicants’ arguments have been fully considered but they are not persuasive.
Applicant argued
"Claims 1-20 are rejected under 35 U.S.C. §101 as being directed to nonstatutory subject matter without significantly more. Without conceding the merits of the rejection, and in the interest of furthering prosecution, independent claims 1 and 13 have been amended.
As an initial matter, Applicant respectfully submits that the claims have been amended, and do not recite the mental process as alleged by the Office Action on page 4 under Step 2A Prong 1.
In addition, Applicant respectfully submits that the amended claims recite eligible subject. For example, and as amended, claim 1 makes clear that "a server [obtains] a resource requirement of a service, and allocate[es] resources of [a] central cloud and [an] edge cloud to deploy instances of the service[.]" Therefore, Applicant respectfully submits that claims 1-20 disclose allocating cloud resources to a service based on a resource requirement of the service, which is eligible subject matter under 35 U.S.C. § 101.
Accordingly, and in light of these amendments, Applicant respectfully requests that the 35 U.S.C. § 101 rejections be withdrawn with respect to claims 1-20 (page 6 of remark).
In response,
Amended independent claims still recites abstract ideas. For example, allocating step can be implemented by human mind with/without help of pen and paper.
Therefore, claims 1 – 20 are directed to nonstatutory subject matter subject matter.
Claim Rejections - 35 U.S.C. 102 / 103
Applicants’ arguments, regarding to the rejection under 102/103 have been fully considered but they are not persuasive.
Applicant argued
“Claims 1 and 13 are rejected under 35 U.S.C. §102(a)(1) as being anticipated by U.S. Publication No. 20200228602 to Spoczynski et al. (hereinafter "Spoczynski"). Claims 2-11 and 14-19 are rejected under 35 U.S.C. §103 over Spoczynski in view of U.S. Patent No. 11,425,054 issued to Dunsmore et al. (hereinafter "Dunsmore"). Claims 12 and 20 are rejected under 35 U.S.C. §103 over Spoczynski in view of Dunsmore, and further in view of U.S. Patent No. 0160127201 issued to Qian et al. (hereinafter "Qian"). Applicant respectfully traverses these rejections for the comments set forth below.
For example, independent claim 1 as amended recites, in part:
obtaining, by a server, a resource requirement of a service, wherein the
server manages resources of a central cloud and an edge cloud[.]
(emphasis added).
Applicant respectfully submits that Spoczynski is silent with respect to the recited features of amended claim 1, and has not been shown to disclose at least these features of the claim.
For the teaching of these features prior to the current amendments, the Office Action on page 10 offers Spoczynski. However, Applicant respectfully submits that Spoczynski has not been shown to disclose at least the amended claim language.
For example, Spoczynski (para. [0056]) states:
The various use cases 205 may access resources under usage pressure from incoming streams, due to multiple services utilizing the edge cloud. To achieve results with low latency, the services executed within the edge cloud 110 balance varying requirements in terms of: (a) Priority (throughput or latency) and Quality of Service (QoS) (e.g., traffic for an autonomous car may have higher priority than a temperature sensor in terms of response time requirement; or, a performance sensitivity/bottleneck may exist at a compute/accelerator, memory, storage, or network resource, depending on the application); (b) Reliability and Resiliency (e.g., some input streams need to be acted upon and the traffic routed with mission- critical reliability, where as some other input streams may be tolerate an occasional failure, depending on the application); and (c) Physical constraints (e.g., power, cooling and form-factor).
Applicant respectfully submits that Spoczynski merely refers to multiple services utilizing an edge cloud and the services executed within the edge cloud balancing varying requirements. Spoczynski has not - however - been shown to disclose that a server obtains a resource requirement of a service, much less that the server manages resources of both a central cloud and an edge cloud.
Therefore, Applicant respectfully submits that Spoczynski has not been shown to disclose "obtaining, by a server, a resource requirement of a service," particularly where "the server manages resources of [both] a central cloud and an edge cloud" as recited in amended claim 1 (emphasis added).
In addition, claim 1 has been amended to recite "allocating, by the server, the resources of the central cloud and the edge cloud to deploy instances of the service across the central cloud and the edge cloud based on the resource requirement of the service" (emphasis added). Applicant respectfully submits that Spoczynski is silent with respect to these newly added features of the claim.
The Current Application at para. [0091] states that "global resources of the central cloud and the edge cloud are combined. This facilitates managing resources of the central cloud and the edge cloud in a unified manner by the cloud service provider, implements the deployment of the instances across the central cloud and the edge cloud, meets a requirement of the service, and increases the resource usage." Based on the claimed implementations, "the deployment of the instances across regions is supported. This meets the user for a requirement of the deployment of the instances of the service across regions, and resolves a problem that resources in a single region cannot ensure a large-scale resource demand. The method can further balance resource usage of each region and each availability zone, and appropriately allocate cloud computing resources to complete the deployment of the instances of the service." Id.
For at least the above-mentioned reasons, Applicant respectfully asserts that claim 1 distinguishes over Spoczynski, and is in condition for allowance. Independent claim 13 recites features similar but not identical to independent claim 1. Accordingly, Applicant respectfully requests that the rejection be withdrawn with respect to all pending claims.” (Pages 6 – 8 of remark).
In response,
Amended claimed limitations are taught by Choi. In Choi, the server obtained resource requirement in order to calculate the resource requirements for allocating resources (figure 1 and associated text). Choi further teaches central cloud and edge cloud service system (para. 0039).
Conclusion
The prior art made of record but not relied upon request is considered to be pertinent to applicant’s disclosure.
Yerli, (US PUB 2020/0403935), discloses a method for resource allocation across edges and cloud including servers’ computation, memory and storage (title, abstract and figures 1 – 9).
Joyce, (US PUB 2021/0240551), discloses allocate resources on a server rack deployed on the edge network (title, abstract and figures 1 – 6).
Chen, (US PUB 2023/0024965), discloses a method receive metrics information describing resource usage, then allocating resources and deploying instances of the service in the distributed computing environment (title, abstract and figures 1 – 3).
Applicants’ 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.
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/PHUONG N HOANG/Examiner, Art Unit 2194
/KEVIN L YOUNG/Supervisory Patent Examiner, Art Unit 2194
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