DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Examiner Notes
Examiner cites particular columns and line numbers in the references as applied to the claims below 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 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 or disclosed by the examiner.
The examiner encourages Applicant to submit an authorization to communicate with the examiner via the Internet by making the following statement (from MPEP 502.03):
“Recognizing that Internet communications are not secure, I hereby authorize the USPTO to communicate with the undersigned and practitioners in accordance with 37 CFR 1.33 and 37 CFR 1.34 concerning any subject matter of this application by video conferencing, instant messaging, or electronic mail. I understand that a copy of these communications will be made of record in the application file.”
Please note that the above statement can only be submitted via Central Fax, Regular postal mail, or EFS Web (PTO/SB/439).
Response to Arguments
Applicant’s arguments filed March 28, 2026 have been fully considered and are persuasive. Examiner has issued a second non-final rejection and has removed the Bernat reference.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-6, 8-13, 15-19, and 21 are rejected under 35 U.S.C. 103 as being unpatentable over Lange et al. (US 20220229707) in view of Yang et al. (US 20170063615).
As per claim 1, Lange teaches the invention substantially as claimed including an apparatus to manage a processing unit ([0024], networked system 100 may include a plurality of member nodes 102, 104, and 106, hereinafter, collectively referred to as member nodes 102-106. Further, the networked system 100 may also include a management node 108 coupled to the member nodes 102-106 via a network 110...networked system 100 in any form, be it the distributed system, the turnkey solution, or the integrated product; and [0036], the management node 108 may manage migration of the one or more candidate workload resources, if identified, to another different member nodes), the apparatus comprising:
interface circuitry ([0025], the network 110 may include one or more network switches, routers, or network gateways to facilitate data communication ...private communication links may be direct communication links between the management node 108 and the member nodes 102-106);
first processor circuitry to implement a central processing unit ([0026], Each of the member nodes 102-106 may be a device including a processor or microcontroller and/or any other electronic component, or a device or system that may facilitate various compute and/or data storage services);
instructions ([0037], management node 108 may include a processing resource 118 and a machine-readable medium 120. The machine-readable medium 120 ... may store data and/or executable instructions 122);
second processor circuitry ([0037], the management node 108 may include a processing resource 118) to at least one of instantiate or execute the instructions to:
obtain a resource request associated with a first workload ([0012], management node may receive a workload resource deployment request to deploy a workload resource and schedule deployment of the workload resource on one or more of other computing nodes, hereinafter referred to as, member nodes);
determine if a second workload can be migrated from execution on the programmable network device ([0020], management node may determine a migration plan for a candidate workload resource of the workload resources based on the capability tag of each of the plurality of member nodes... The migration plan may include a list of one or more candidate workload resources, if any, that are identified to be migrated. The migration plan may also include target member nodes to which the one or more candidate workload resources are to be migrated; and [0026], member nodes 102-106 may facilitate resources, for example, compute, storage, and/or networking capabilities, for one or more workload resources to execute thereon; Examiner Note: Lange’s “workload resources” include various types of workloads: [0001], Examples of the workload resources may include an application (e.g., software program), a virtual machine (VM), a container, a pod, a database, a data store, a logical disk, or a containerized application);
based on the determination that the second workload can be migrated, cause the second workload to be migrated ([0020], the management node may determine a migration plan for a candidate workload resource of the workload resources based on the capability tag of each of the plurality of member nodes, the resource requirement classification and the temporal usage pattern classification of each workload resource... Once the migration plan is determined, the management node may cause migration of the candidate workload resource(s) to the respective target member nodes at the respective determined time-schedule); and
cause the first workload to execute on the processing resource of the programmable network device ([0012], management node may receive a workload resource deployment request to deploy a workload resource and schedule deployment of the workload resource on one or more of other computing nodes, hereinafter referred to as, member nodes).
Lange fails to specifically teach, determine if a processing resource of a programmable network device is available to process the first workload.
However, Yang teaches, determine if a processing resource of a programmable network device is available to process the first workload ([0007], SDI schedules the processing tasks associated with each request. In certain embodiments, the SDI may assign various states to a service request based on assigned states of tasks associated with the service request. Upon successful execution of the tasks associated with a service request, the SDI can provisions resources (e.g., memory and processing resources) for the request; and [0174], a task can be retried after a certain delay when the resource may become available).
Lange and Yang are analogous because they are each related to resource management and workload placement. Lange teaches a method of workload deployment and migration based on workload requirements. (Abstract, management node may determine a resource requirement classification of each workload resource of the workload resources based on analysis of runtime performance data of each workload resource. Furthermore, the management node may determine a temporal usage pattern classification of each workload resource. Moreover, the management node may determine a migration plan for a candidate workload resource of the workload resources; and [0021], enhanced migration of the workload resources as caused by the management node, in some examples, may advantageously place the workload resources on a well-equipped member node having sufficient resources (e.g., hardware and software) to fulfill requirements of the workload resources). Yang teaches a method allocating resources to a workload based on workload requirements and available resources. (Abstract, The SDI request engine performs the tracking, management and provisioning of services subscribed to by customers of the cloud infrastructure system. The SDI request engine is deployed to process large volumes of provisioning requests and deliver time critical applications for customers. The SDI request engine translates each request into a list of tasks of various sizes based on the requirement and configuration of the request. In some embodiments; and [0114], the subscription order is provisioned based on the series of tasks. In one embodiment, and as discussed in FIG. 6, SDI connector module 612 includes one or more connectors for handling the deployment of tasks specified by SDI task manager module 604 to provision resources for the services in the subs). It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention that based on the combination, Lange’s management node would be modified with the load balancer mechanism taught by Yang resulting in a system that assigns workloads to resources based at least in part on an availability of resources. Therefore, it would have been obvious to combine the teachings of Lange and Yang.
As per clam 2, Yang teaches wherein the second processor circuitry includes an infrastructure processing unit ([0044], cloud infrastructure system 100 may comprise multiple components, which working in conjunction, enable provision of services provided by cloud infrastructure system 100. In the embodiment illustrated in FIG. 1A, cloud infrastructure system 100 includes ...cloud management functionality 108. These components may be implemented in hardware, or software, or combinations thereof; and [0155], tasks can include movement of data, configuration of a cloud infrastructure module, processing of tasks, or other operations associated with the cloud infrastructure system).
As per clam 3, Lange teaches, wherein the second processor circuitry is a component of a second programmable network device ([0024], the networked system 100 may be a distributed system where one or more of the member nodes 102-106 and the management node 108 are located at physically different locations (e.g., on different racks, on different enclosures, in different buildings, in different cities, in different countries, and the like) while being connected via the network 110; and [0038], where the management node 108 may be a virtual machine or a containerized application, the processing resource 118 and the machine-readable medium 120 may represent a processing resource and a machine-readable medium of the hardware or a computing system that hosts the management node 108 as the virtual machine or the containerized application).
As per clam 4, Lange teaches, wherein the second processor circuitry is to manage resources associated with the first processor circuitry ([0012], management node may receive a workload resource deployment request to deploy a workload resource and schedule deployment of the workload resource on one or more of other computing nodes, hereinafter referred to as, member nodes; and [0014], [t]he published hardware and software capabilities of the member nodes can in turn be used by a scheduler running on the management node to facilitate intelligent scheduling of workload resources).
As per clam 5, Yang teaches, wherein the resource request specifies a type of processing resource to be utilized ([0004], Provisioning a cloud services is one relatively processor intensive task that may require provisioning of many different resources and/or resources types to enable a specific service request; [0006], The SDI can identify tasks for enabling services. The tasks can be of varying number and/or complexity depending upon requirements, configurations, and options associated with each request; [0073], TAS module 204 sends a request to SDI module 206 to allocate resources and configure those resources needed to fulfill the subscription order. SDI module 206 enables the allocation of resources for the services ordered by the customer; and [0120], t. Certain tasks can be associated with provisioning resources to enable a service request. In certain embodiments, resource provisioning tasks are performed sequentially in an order specified for each request type in order to violate resource allocation dependencies associated with provisioning the resources. Alternatively, one or more tasks can be performed in parallel. Each service request can, via a policy, be determined to be delineated into a plurality of tasks. The policy can determine which tasks are to be performed, the order of the tasks, or other information related to performance of the tasks. For example, a policy can include one or more processes for provisioning a service. Each of the processes can be associated, via a policy, with a plurality of tasks).
As per clam 6, Lange teaches, wherein the second processor circuitry is to update a class of service for the second workload ([0023], the migration plan may cause a migration of the candidate workload resource during a time period when the given candidate workload is inactive or idle. For example, the workload resource that are periodic in nature may be migrated to low-power or less compute intensive member nodes when such periodic workload resources are inactive or idle).
As per clam 8, this is the “non-transitory computer readable medium claim” corresponding to claim 1 and rejected for the same reasons. The same motivation used in the rejection of claim 1 is applicable to the instant claim.
As per clam 9, this claim is similar to claim 2 and is rejected for the same reasons.
As per clam 10, this claim is similar to claim 3 and is rejected for the same reasons.
As per clam 11, this claim is similar to claim 4 and is rejected for the same reasons.
As per clam 12, this claim is similar to claim 5 and is rejected for the same reasons.
As per clam 13, this claim is similar to claim 6 and is rejected for the same reasons.
As per clam 15, this is the “method claim” corresponding to claim 1 and rejected for the same reasons. The same motivation used in the rejection of claim 1 is applicable to the instant claim.
As per clam 16, Lange teaches, wherein the determination if the processing resource is available is performed by an infrastructure processing unit ([0078], Load balancer 1404 to pre-process a workload and identify one or more combinations of hardware resources and configurations to perform one or more operations of layers of a multiple stage data processing to attempt to achieve applicable SLA parameters associated with the one or more layers...load balancer 1404 can be implemented in one or more of: ... IPU).
As per clam 17, Lange teaches, wherein the determination if the processing resource is available is performed by a component of a second programmable network device ([0014], published hardware and software capabilities of the member nodes can in turn be used by a scheduler running on the management node to facilitate intelligent scheduling of workload resources; and [0018], management node may determine the capability tag for each of the plurality of member nodes based on platform capability data published by each of the plurality of member nodes).
As per clam 18, Lange teaches, further comprising managing resources associated with a first processing circuitry ([0012], management node may receive a workload resource deployment request to deploy a workload resource and schedule deployment of the workload resource on one or more of other computing nodes, hereinafter referred to as, member nodes; and [0014], [t]he published hardware and software capabilities of the member nodes can in turn be used by a scheduler running on the management node to facilitate intelligent scheduling of workload resources).
As per claim 19, this claim is similar to claim 5 and is rejected for the same reasons.
As per claim 21, Lange teaches, wherein the programmable network device comprises a control plane to handle resource allocation, monitoring, and policy enforcement ([0012], management node may receive a workload resource deployment request to deploy a workload resource and schedule deployment of the workload resource on one or more of other computing nodes, hereinafter referred to as, member nodes.... The member nodes may facilitate resources, for example, compute, storage, and/or networking capability, for the workload resources to execute workloads; [0013], management node may also manage migration of the workload resources based on an operating status of the member nodes. The scheduling (e.g., deployment) and/or migration of the workload resources may be managed to address the need for rapid deployment of services, at cloud scale, keeping in mind factors like agility, ease of application upgrades or rollbacks and cloud-native workload resources; [0036], the management node 108 may manage migration of the one or more candidate workload resources, if identified, to another different member nodes; and [0046], the management node 108 may receive the runtime performance data about workload resources (WLR1-WLR6) from the respective performance monitors 112-116 hosted on the respective member nodes 102-106), and a data plane to handle data flow between the programmable network device and logical units associated with the programmable network device ([0025], the network 110 may be enabled via private communication links including, but not limited to, communication links established via Bluetooth, cellular communication, optical communication, radio frequency communication, wired (e.g., copper), and the like. In some examples, the private communication links may be direct communication links between the management node 108 and the member nodes 102-106; [0029], one or more of the member nodes 102-106 may host a node-monitoring agent (NMA) and a capability publisher agent (CPA). In the example of FIG. 1, the member node 102 is shown to host NMA1 and CPA1, the member node 104 is shown to host NMA2 and CPA2, and the member node 106 is shown to host NMA3 and CPA3. The node-monitoring agents NMA1, NMA2, and NMA3 and the capability publisher agents CPA1, CPA2, and CPA3 may represent a workload resource (e.g., a pod) being executed on the respective member nodes 102-106; and [0033], the capability publisher agent CPA1 may publish the platform capability data of the member node 102 monitored by the node-monitoring agent NMA1. In some examples, publishing of the capability data may include communicating the platform capability labels and their respective settings to the management node 108 by the capability publisher agent CPA1).
Claims 7 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over the combination of Lange-Yang as applied to independent claims 1 and 8 and in further view of Kraus et al. (US 20220012668).
As per claim 7, the combination of Lange-Yang fails to specifically teach, wherein the second processor circuitry is to store an association of the first workload and the processing resource in a blockchain.
However, Kraus teaches, wherein the second processor circuitry is to store an association of the first workload and the processing resource in a blockchain ([0091], every modification to a work item would be registered on the blockchain of the person/resource effecting it (e.g. creation and initial work item description may be stored on the user/operator creating the work item, performance of a task related to the work item may be stored on the blockchain of the resource performing the task, etc.). As such, in those embodiments, the work item records may act as the index referring to the related blocks in the blockchains from users and resources; Examiner Note: Kraus’ “resources” include various types of resources: [0050], the term “resource” is defined as including an entity that either performs work or is used to perform work. This includes staff (humans performing the work), but also vehicles, rooms or places, equipment and materials required to perform the work).
The combination of Lange-Yang and Kraus are analogous because they are each related to workload and resource management. Lange teaches a method of workload deployment and migration based on workload requirements. Yang teaches a method allocating resources to a workload based on workload requirements and available resources. Kraus teaches a method workload and resource management that leverages blockchain technology. (Abstract, uses a blockchain data structure providing a fully immutable and cryptographically secured system, instead of a traditional database structure. Separate chains of blocks can be used for different actors, parties or resources while linking data between the various blockchains to provide a connected data structure related to each work item; [0010], the use of a blockchain implementation for the work and resource data management system may not allow any data to ever be overwritten or deleted. It thus becomes possible to retain a full history of every action that happened in the system, maintaining a complete audit trail and enabling the investigation on the state-of-knowledge at any given time in the past. In some embodiments, the investigation may even be performed across different viewpoints in temporary inconsistent states (e.g. from different resources, where some of which may have been in an asynchronous state due to the lack of a network connection; and [0012], use of plural blockchains may allow for the data to be securely created and stored in a distributed manner across a network of devices, for example across resource devices and at one or more operator or control centers). It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention that based on the combination, the management node taught by the combination of Lange-Yang would be modified with the known blockchain orchestration mechanism taught by Kraus resulting in a system that assigns that leverages the security and reliability of blockchains in order to maintain workload and resource data for provisioning and load-balancing. Therefore, it would have been obvious to combine the teachings of Lange-Yang and Kraus.
As per clam 14, this claim is similar to claim 7 and is rejected for the same reasons. The same motivation used in the rejection of claim 7 is applicable to the instant claim.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure and is as follows:
Zhang et al. (US 20220238550): Teaches workload management for AI workloads using blockchain technology: [0045], The gateway system described herein enables the blockchain to be an efficient and reliable infrastructure to run AI workloads. The gateway system may translate an AI training workload to blockchain transactions and submit the transactions to a blockchain which is accessible to the blockchain peers. This allows training to happen on the blockchain via the blockchain peers; and [0056], each training iteration is recorded on the blockchain, real-time monitoring at each iteration which eliminates wasted efforts to train compromised AI models, better efficiency because the peers can be dynamically chosen at each iteration based on current conditions and availability, flexible training assignments (e.g., a peer could be assigned a first sub-model during a first training iteration and then be assigned a second sub-model during a second training iteration, etc.));
Baine et al. (US 11194791): Teaches workload management using a blockchain orchestrator: Column 7, Lines 12-17, The resource provider 218 in turn may then determine the number of physical and/or virtual machines that would be required to fulfil the desired CPU and memory requirements and assign these physical or virtual machines to the executor 212; and Column 14, Lines 32-43, When a new blockchain node of a blockchain network is created or deployed, a blockchain protocol is deployed via the blockchain node. Deploying a blockchain protocol on a blockchain node of a blockchain network includes synchronizing the new blockchain node with one or more other blockchain nodes of the blockchain network. Synchronizing the new blockchain node with one or more other blockchain nodes of the blockchain network includes performing an initial synchronization operation by downloading blockchain history data comprising all blocks of a blockchain that is maintained by the one or more blockchain nodes of blockchain network); and
Bai et al. (US 20220091903): Teaches workload management using blockchain technology: [0016], Embodiments of the present invention solve the problems stated above by orchestrating and managing workloads in a decentralized multi-cloud environment using blockchain and smart contracts; [0054], Within blockchain 160, smart contracts and ledgers 166 are used to encapsulate the shared processes and shared information in a network, respectively; and [0072], orchestration component 140 executes and submits an orchestration request to endorse peers 162. Endorse peers 162, in blockchain 160, may receive workload request and run smart contracts. A smart contract reads workload templates, analyzes what kinds of cloud services should be used, reads cloud service competency from blockchain ledger, and generates an orchestration plan that is tailored and/or the best fit for the current workload).
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MELISSA A HEADLY whose telephone number is (571)272-1972. The examiner can normally be reached Monday- Friday 9-5:30pm.
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/MELISSA A HEADLY/Examiner, Art Unit 2197
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