DETAILED ACTION
Statement of claims
The present application include :
Claims 1-20 remain pending in the application. Claims 1-20 are being considered on the merits.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 09/29/2025 . The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
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 .
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.
Claim(s) 1-8, and 10-20 are rejected under 35 U.S.C. 103 as being unpatentable over Berry et al. (US 2022/0206831, Berry hereinafter) in view of Banerjee et al. (US 2023/0121460, Banerjee hereinafter).
As to claim 1, Berry teaches a method, comprising:
identifying, by a system comprising a processor, a cluster (e.g., “The heterogeneous node pool 101 “, FIG. 1A) , the cluster having been deployed using a set of node devices that support the cluster (e.g., see FIG. 1A and 1B, para 41, “The heterogeneous node pool 101 may comprise many different types of nodes” and “clusters formed of heterogeneous nodes”, “ to identify a group of candidate nodes that can be feasibly configured into a computing cluster.” in para 26 and 45) ; and
deploying, by the system, a virtual machine on a node device that is not part of the set of node devices (e.g., see FIG. 7D, para 131, “the nodes of the distributed virtualization system can implement one or more user virtualized entities (e.g., VE 788.sub.111, . . . , VE 788.sub.11K, . . . , VE 788.sub.1M1, . . . , VE 788.sub.1MK), such as virtual machines (VMs)” , and
merging, by the system, the node device into the set of node devices, resulting in a merged set of node devices to support the cluster (e.g., para 29, “the networked computing cluster can change autonomously (e.g., by adding a node “ and “additional nodes or different types of nodes are needed in order to construct the specified cluster, step 211 can transfer processing control to step 202, where additional candidate nodes can be identified.” In para 52),”.
Thus, the “adding “ coupled with the “node include the merging ) .
However, Berry does not teach for a change in storage capacity, and achieve the change in storage capacity.
Banerjee teaches a change in storage capacity, and achieve the change in storage capacity (e.g., para 51 “ a cluster (e.g., cluster 104) increases the total storage capacity of the cluster. ”, and “addition of a new node with storage capacity to the cluster and following completion of dynamic storage capacity scaling responsive”, “storage capacity based on the capabilities of the new node as described further below with reference to FIGS. 4A-D and FIG. 5”, “determined dynamically based on the resource capacity (e.g., compute, storage, and/or memory capacity) of the particular node (e.g., a new node added to the cluster from a heterogeneous resource pool) in para 11, 27 and 47).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Berry by adopting the teachings of Banerjee to provide “ automated deployment and lifecycle management, scaling on-demand, higher levels of resiliency with increased scale, and automatic failure detection and self-healing” (of Banerjee , para 16).
As to claim 2, Berry teaches wherein deploying the virtual machine comprises: based on the set of node devices and the cluster, generating metadata associated with the virtual machine; and creating the virtual machine comprising storing the metadata with the virtual machine to be accessible via the virtual machine (e.g., see FIG. 7A, para 101, wherein “a controller virtual machine instance “ with “data “, “metadata”. Thus, generating metadata associated with the virtual machine; and creating the virtual machine comprising storing the metadata with the virtual machine to be accessible via the virtual machine ).
As to claim 3. , Berry teaches , wherein the metadata comprises a serial number generated for the virtual machine prior to deploying the virtual machine (e.g., para 131, “virtualized entities (e.g., VE 788.sub.111, . . . , VE 788.sub.11K, . . . , VE 788.sub.1M1, . . . , VE 788.sub.1MK),”) and “number or form of virtualized entities. “ in para 134) .
As to claim 4, Berry teaches further wherein the set of node devices comprises a range of network addresses to facilitate support of the cluster, the range of network addresses to accommodate merging the node device into the set of node devices (e.g., para 68, “ Internet Protocol version 4 (IPv4) identifies a subnet by means of the first address in the subnet (or “network address”) and a “network mask”, which specifies the range of available addresses in the subnet (with the first and last addresses reserved as the network address and broadcast address, respectively). ), . However, Berry does not teach and wherein the method further comprises: based on the capacity specification, expanding, by the system. Banerjee teaches based on the capacity specification, expanding, by the system (e.g., see rejection of claim 1 above, para 81, “facilitates dynamic storage capacity scaling”).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Berry by adopting the teachings of Banerjee to provide “ automated deployment and lifecycle management, scaling on-demand, higher levels of resiliency with increased scale, and automatic failure detection and self-healing” (of Banerjee , para 16).
As to claim 5, Berry does not teach wherein the node device comprises a first node device, and wherein the method further comprises: based on the capacity specification, deploying, by the system, a second node device different from the first node device, wherein merging the first node device into the set of node devices comprises asynchronously merging the first node device and the second node device into the set of node devices to support the cluster and achieve the change in storage capacity. However, Banerjee teaches based on the capacity specification, deploying, by the system, a second node device different from the first node device, wherein merging the first node device into the set of node devices comprises asynchronously merging the first node device and the second node device into the set of node devices to support the cluster and achieve the change in storage capacity (e.g., para 78, “f FIG. 4A after the addition of a new node “, “ completion of dynamic application performance scaling responsive thereto” and para 81 “he cluster 404 of FIG. 4A after addition of a new node with storage capacity to the cluster 404 and following completion of dynamic storage capacity scaling responsive thereto” in para 81. Thus, based on the capacity specification, deploying, by the system, a second node device different from the first node device, wherein merging the first node device into the set of node devices comprises asynchronously merging the first node device and the second node device into the set of node devices to support the cluster and achieve the change in storage capacity would have been inherent).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Berry by adopting the teachings of Banerjee to provide “ automated deployment and lifecycle management, scaling on-demand, higher levels of resiliency with increased scale, and automatic failure detection and self-healing” (of Banerjee , para 16).
As to claim 6, Berry does not teach validating, by the system, the deploying of the node device, and the change in storage capacity of the cluster as a result of merging the node device. However, Banerjee teaches validating, by the system, the deploying of the node device, and the change in storage capacity of the cluster as a result of merging the node device (e.g., para 81, wherein “ the cluster 404 of FIG. 4A after addition of a new node with storage capacity “, “ completion of dynamic storage capacity scaling responsive thereto” , “facilitates dynamic storage capacity scaling”, “ the existing deployment “ and “Based on resource capacity of the new node, a configuration of the new node may be established that is indicative of whether one or both of a new storage management subsystem (SMS) and a new data management subsystem (DMS) are to be enabled on the new node. The new node is deployed virtually in accordance with the configuration. “ in para 4.
Thus, validating, by the system, the deploying of the node device, and the change in storage capacity of the cluster as a result of merging the node device).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Berry by adopting the teachings of Banerjee to provide “ automated deployment and lifecycle management, scaling on-demand, higher levels of resiliency with increased scale, and automatic failure detection and self-healing” (of Banerjee , para 16).
As to claim 7, Berry does not teach before deploying the virtual machine on the node device, determining, by the system, that merging the node device into the set of node devices is not going to result in a limit on number of node devices, which are allowed to be included in the set of node devices, being exceeded. However, Banerjee teaches deploying the virtual machine on the node device, determining, by the system, that merging the node device into the set of node devices is not going to result in a limit on number of node devices, which are allowed to be included in the set of node devices, being exceeded ( e.g., para 92, “determined whether sufficient storage capacity is available on the new node”. “evaluating whether the storage capacity of the new node accommodates, supports, or otherwise justifies provisioning the new node with block and storage management services”, “ the storage capacity may be compared against a minimum storage capacity threshold. In one embodiment, the minimum storage capacity threshold is sufficient storage capacity to form a file system aggregate”. Thus, deploying the virtual machine on the node device, determining, by the system, that merging the node device into the set of node devices is not going to result in a limit on number of node devices, which are allowed to be included in the set of node devices, being exceeded would have been inherent).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Berry by adopting the teachings of Banerjee to provide “ automated deployment and lifecycle management, scaling on-demand, higher levels of resiliency with increased scale, and automatic failure detection and self-healing” (of Banerjee , para 16).
As to claim 8, Berry teaches further comprising, before deploying the virtual machine on the node device, determining, by the system, that the set of node devices are functioning in accordance with a node specification (see rejection of claim 1 above).
As to claim 10, Berry does not teach wherein identifying the cluster for the change in storage capacity comprises: based on a capacity condition, monitoring the storage capacity of the cluster; and based on the monitoring and the capacity condition, generating the capacity specification. However, Banerjee teaches wherein identifying the cluster for the change in storage capacity comprises: based on a capacity condition, monitoring the storage capacity of the cluster; and based on the monitoring and the capacity condition, generating the capacity specification (e.g., para 92, “the storage capacity may be compared against a minimum storage capacity threshold. In one embodiment, the minimum storage capacity threshold is sufficient storage capacity to form a file system aggregate. If sufficient storage capacity is determined to be available on the new node, process 500 continues with operation 530; otherwise, process 500 branches to operation 540.”. Thus, wherein identifying the cluster for the change in storage capacity comprises: based on a capacity condition, monitoring the storage capacity of the cluster; and based on the monitoring and the capacity condition, generating the capacity specification) .
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Berry by adopting the teachings of Banerjee to provide “ automated deployment and lifecycle management, scaling on-demand, higher levels of resiliency with increased scale, and automatic failure detection and self-healing” (of Banerjee , para 16).
As to claim 11, see rejection of claims 1 and 6 above. Berry teaches further Storage equipment, comprising: a processor; and a memory that stores executable instructions that, when executed by the processor, facilitate performance of operations, comprising (e.g., see claim 25. A system comprising: a storage medium having stored thereon a sequence of instructions; and a processor that executes the sequence of instructions to cause the processor to perform acts comprising”). However, Berry does not teach receiving a capacity specification that specifies storage resources to be allocated to support a virtual machine, wherein allocation of the storage resources results in allocated storage resources that support the virtual machine, based on the capacity specification, validating the allocated storage resources and the configuration, and based on the validating, merging the storage equipment into the group of storage equipment supporting the storage cluster. Banerjee teaches receiving a capacity specification that specifies storage resources to be allocated to support a virtual machine, wherein allocation of the storage resources results in allocated storage resources that support the virtual machine, based on the capacity specification (e.g., para 51 “ a cluster (e.g., cluster 104) increases the total storage capacity of the cluster. ”, and “addition of a new node with storage capacity to the cluster and following completion of dynamic storage capacity scaling responsive”, “storage capacity based on the capabilities of the new node as described further below with reference to FIGS. 4A-D and FIG. 5”, “determined dynamically based on the resource capacity (e.g., compute, storage, and/or memory capacity) of the particular node (e.g., a new node added to the cluster from a heterogeneous resource pool) in para 11, 27 and 47), validating the allocated storage resources and the configuration, and based on the validating, merging the storage equipment into the group of storage equipment supporting the storage cluster ( see rejection of claim 6 above).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Berry by adopting the teachings of Banerjee to provide “ automated deployment and lifecycle management, scaling on-demand, higher levels of resiliency with increased scale, and automatic failure detection and self-healing” (of Banerjee , para 16).
As to claim 12, Berry does not teach wherein receiving the capacity specification comprises receiving the capacity specification based on a determination that the storage cluster requested additional storage capacity beyond a current storage capacity of the storage cluster. However, Banerjee teaches wherein receiving the capacity specification comprises receiving the capacity specification based on a determination that the storage cluster requested additional storage capacity beyond a current storage capacity of the storage cluster (e.g., para 92, wherein “the storage capacity may be compared against a minimum storage capacity threshold. In one embodiment, the minimum storage capacity threshold is sufficient storage capacity to form a file system aggregate. If sufficient storage capacity is determined to be available on the new node, process 500 continues with operation 530; otherwise, process 500 branches to operation 540.”. Thus, wherein receiving the capacity specification comprises receiving the capacity specification based on a determination that the storage cluster requested additional storage capacity beyond a current storage capacity of the storage cluster).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Berry by adopting the teachings of Banerjee to provide “ automated deployment and lifecycle management, scaling on-demand, higher levels of resiliency with increased scale, and automatic failure detection and self-healing” (of Banerjee , para 16).
As to claim 13, Berry does not teach wherein the capacity specification was generated to achieve a specified change in a storage capacity of the storage cluster. However, Banerjee teaches wherein the capacity specification was generated to achieve a specified change in a storage capacity of the storage cluster ( e.g., para 81, “ dynamic storage capacity scaling responsive thereto”).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Berry by adopting the teachings of Banerjee to provide “ automated deployment and lifecycle management, scaling on-demand, higher levels of resiliency with increased scale, and automatic failure detection and self-healing” (of Banerjee , para 16).
As to claim 14, Berry teaches wherein merging the storage equipment into the group of storage equipment supporting the storage cluster comprises integrating the virtual machine to support the storage cluster by performing a function of the storage cluster (e.g., see FIG. 1A, para 39, “heterogeneous network environments can be selected, loaded with node-specific virtualization system software, and deployed so as to form a computing cluster.”) .
As to claim 15, see rejection of claims 1 and 11 above. Berry teaches further a non-transitory machine-readable medium, comprising executable instructions that, when executed by a processor of capacity scaling equipment, facilitate performance of operations, comprising (e.g., claim 13. A non-transitory computer readable medium having stored thereon a sequence of instructions which, when stored in memory and executed by a processor cause the processor to perform acts comprising). However, Berry does not teach based on a request for a change in storage capacity of a cluster deployed using node devices supporting the cluster, obtaining a capacity specification. Banerjee teaches based on a request for a change in storage capacity of a cluster deployed using node devices supporting the cluster, obtaining a capacity specification; and based on the capacity specification, deploying a virtual machine on a node device (see para 4, wherein “Based on resource capacity of the new node, a configuration of the new node may be established that is indicative of whether one or both of a new storage management subsystem (SMS) and a new data management subsystem (DMS) are to be enabled on the new node. The new node is deployed virtually in accordance with the configuration”. Thus, based on a request for a change in storage capacity of a cluster deployed using node devices supporting the cluster, obtaining a capacity specification; and based on the capacity specification, deploying a virtual machine on a node device ).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Berry by adopting the teachings of Banerjee to provide “ automated deployment and lifecycle management, scaling on-demand, higher levels of resiliency with increased scale, and automatic failure detection and self-healing” (of Banerjee , para 16).
As to claims 16-20 see rejection of claims 2, 4 and 6-8 above.
Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over Berry et al. (US 2022/0206831, Berry hereinafter) in view of Banerjee et al. (US 2023/0121460, Banerjee hereinafter), as applied to claim 1 above, and further in view of Lewites (US 2005/0138620, Lewites hereinafter).
As to claim 9, Berry and Banerjee do not teach wherein deploying the virtual machine on the node device comprises creating a virtual network interface card to support the virtual machine. However, Lewites teaches deploying the virtual machine on the node device comprises creating a virtual network interface card to support the virtual machine (e.g., abstract, “a virtual machine, “a virtual network interface card that is configurable to enable communication between the driver and the virtual machine”).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to further modify the method of Berry and Banerjee by adopting the teachings of Lewites to provide “ Enables efficient routing of the data packets between the virtual machine and the computer” (Lewites, para 15-16).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Zuo et al. (US 2013/0298123) discloses Computerized methods, systems, and computer-storage media for allowing virtual machines (VMs) residing on a common physical node to fairly share network bandwidth are provided. Restrictions on resource consumption are implemented to ameliorate stressing the network bandwidth or adversely affecting the quality of service (QoS) guaranteed to tenants of the physical node.
Olmsted-Thompson (US 11, 740,921) discloses The computing system for allocating resources includes one or more processors configured to receive a first scheduling request to initiate a first container on a first virtual machine having a set of resources. A first amount of resources is allocated from the set of resources to the first container on the first virtual machine in response to the first scheduling request. A hypervisor is notified in a host of the first amount of resources allocated to the first container. A second amount of resources from the set of resources is allocated to a second virtual machine in the host. A reduced amount of resources available in the set of resources is determined. A container scheduler is notified by the hypervisor for the reduced amount of resources of the set of resources available on the first virtual machine.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ABDOU K SEYE whose telephone number is (571)270-1062. The examiner can normally be reached M-F 9-5:30.
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/ABDOU K SEYE/Examiner, Art Unit 2198
/PIERRE VITAL/Supervisory Patent Examiner, Art Unit 2198