DETAILED ACTION
1. This action is responsive to the communications filed on 02/03/2026.
2. Claims 1, 6-20, are pending in this application.
3. Claims 1, 8, 9, have been amended.
4. Claims 2-5 have been previously cancelled.
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 .
Response to Arguments
Applicant’s arguments with respect to claims 1, 6-20, have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Allowable Subject Matter
Claim 20 is objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-20, are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Specifically, the term “uncertainty” in claims 1, 8, 9, is a relative term which renders the claim indefinite. The term “uncertainty” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. For example, “uncertainty” could be a prediction itself as a prediction is not considered certain until after it has occurred. “Uncertainty” could also mean that some values are known but not all or even no values are known.
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, 6-19, are rejected under 35 U.S.C. 103 as being unpatentable over Marquezan et al. (US 2011/0246647) in view of Mimura et al. (US 2015/0222515) and McMullin et al. (US 2012/0253532).
Regarding claim 1, Marquezan disclosed:
An apparatus (Figure 2, virtual manager) for assigning (Paragraph 22, movement of virtual nodes) a virtual network (Figure 1, virtual networks 1-2) to a physical network (Figure 1, substrate network), the apparatus comprising (Paragraph 22, using heuristics to determine to move virtual nodes to certain substrate nodes):
a processor (Paragraph 54, CPU); and
a memory (Paragraph 54, memory space) storing program instructions that cause the processor to
assign the virtual network to at least a part of the physical network (Paragraph 9, operating at least one virtual network on a physical substrate network. Paragraph 35, each physical substrate node makes a local analysis of potential candidates to migrate and substrate node neighbors exchange information about which virtual nodes they want to receive. Paragraph 41, movement of a virtual node to a neighboring substrate node is based on the local monitored resource usage patterns).
While Marquezan disclosed movement of virtual nodes to physical networks based on monitored resource usage patterns (Paragraph 41), Marquezan did not explicitly disclose assign the virtual network to at least a part of the physical network based on a first prediction value of a traffic volume of a service, a second prediction value of electric power of a respective physical node of a plurality of physical nodes, and information on the physical network.
However, in an analogous art, Mimura disclosed assign the virtual network to at least a part of the physical network based on a first prediction value of a traffic volume of a service, a second prediction value of electric power of a respective physical node of a plurality of physical nodes, and information on the physical network (Figure 2, showing physical server group 210 (i.e., physical network) including a plurality of virtual machines 211a-e (i.e., virtual network). Paragraphs 82-83, the measuring node 201 measures traffic loads and notifies management and orchestration server 220 of the traffic load (i.e., information on the physical network). The load data is stored in a traffic load transition table. The traffic load transition table includes future data subdivided into time periods (i.e., prediction value of traffic volume). Paragraph 84, using past and present data to forecast power approximation (i.e., prediction value of electric power). Paragraph 85, the management and orchestration server 220 forecasts the number of virtual machines required in the future in each virtualized node (of the physical server group) by using the traffic load transition table and if the amount of resources required in the future is more than the current resources held by the physical server group, a scale out is requested (i.e, adding VMs to the physical server)).
One of ordinary skill in the art would have been motivated to combine the teachings of Marquezan with Mimura because the references involve adding virtual nodes to physical networks based on metrics, and as such, are within the same environment.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the predictions of traffic volume and power of Mimura with the teachings of Marquezan in order to allow for highly efficient operations (Mimura, Paragraph 73).
While Marquezan and Mimura disclosed a second prediction value of electric power (Marquezan, see above), Mimura and Marquezan did not explicitly disclose electric power to be consumed by a respective physical node and wherein the second prediction value of electric power is based on deviation of power supply from a predetermined nominal power supply caused by uncertainty of supplying renewable energy as a power source in a natural environment.
However, in an analogous art, McMullin disclosed value of electric power to be consumed by a respective physical node of a plurality of physical nodes (Paragraph 46, amount of produced power to be consumed by customers, such as amount of power to be stored in one or more batteries (i.e., plurality of physical nodes));
wherein the second prediction value of electric power is based on deviation of power supply from a predetermined nominal power supply caused by uncertainty of supplying renewable energy as a power source in a natural environment (Paragraph 46, information associated with renewable resource availability is obtained. Paragraph 48, one or more expected outputs of the renewable energy resources for the future time period is calculated (i.e., second prediction value of electric power). Paragraph 49, the initial load forecast is then modified or adjusted based on the expected outputs for the renewable resources (i.e., deviation)).
One of ordinary skill in the art would have been motivated to combine the teachings of Marquezan and Mimura with McMullin because the references involve monitoring resources, and as such, are within the same environment.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the power to be consumed of McMullin with the teachings of Marquezan and Mimura in order to have relatively higher operational efficiencies (McMullin, Paragraph 12).
Regarding claims 8, 9, the claims are substantially similar to claim 1. Claim 8 further recites the assigning being robust to a prediction error of the first prediction value of the traffic volume and the second prediction value of the electric power (Mimura, Figure 13, showing that the data that goes into the determination to scale out includes present data, future data (1 week) and even further future data (15 weeks) along with past data thereby being robust to a prediction error as it is over a large span of time).
Therefore, the claims are rejected under the same rationale.
Regarding claim 6, the limitations of claim 1 have been addressed. Marquezan, Mimura, and McMullin disclosed:
wherein the assignment of the virtual network to the at least a part of the physical network minimizes a cost of the virtual network (Marquezan, Paragraph 66, based on the traffic pattern characterization and the cost evaluation of a reorganization of virtual resources, the virtual manager takes the actions to reorganize the resources of the virtual networks. Paragraph 91, Algorithm 3 Moving Candidate Algorithm - step 4 showing a cost-efficient relation for determining to move resources).
Regarding claim 7, the limitations of claim 6 have been addressed. Marquezan, Mimura, and McMullin disclosed:
wherein the cost comprises a power consumption cost (Marquezan, Paragraph 42, movement of virtual nodes out of a substrate node is done for reduced energy consumption).
Regarding claims 10, 13, 15, the limitations of claims 1, 8, 9, have been addressed. Marquezan, Mimura, and McMullin disclosed:
the assign operation further comprises allocating a virtual node of a plurality of virtual nodes in the virtual network to a physical node of the plurality of physical nodes in the physical network based on a combination of the first prediction value, the second prediction value, and the information on the physical network (Mimura, Paragraphs 82-83, the measuring node 201 measures traffic loads and notifies management and orchestration server 220 of the traffic load (i.e., information on the physical network). The load data is stored in a traffic load transition table. The traffic load transition table includes future data subdivided into time periods (i.e., first prediction value). Paragraph 84, using past and present data to forecast power approximation (i.e., second prediction value). Paragraph 85, the management and orchestration server 220 forecasts the number of virtual machines required in the future in each virtualized node (of the physical server group) by using the traffic load transition table and if the amount of resources required in the future is more than the current resources held by the physical server group, a scale out is requested (i.e, adding VMs to the physical server)).
For motivation, please refer to claim 1.
Regarding claims 11, 14, 16, the limitations of claims 1, 8, 9, have been addressed. Marquezan, Mimura, and McMullin disclosed:
the assign operation further comprises determining a virtual path between a pair of virtual nodes of a plurality of virtual nodes (Marquezan, Paragraph 46, reallocating virtual resources to reduce overall traffic of the substrate network by the redefinition of virtual links (i.e., virtual paths) and migration of virtual nodes to locations near the user’s request)
based on a combination of the first prediction value, the second prediction value, and the information on the physical network (Mimura, Paragraphs 82-83, the measuring node 201 measures traffic loads and notifies management and orchestration server 220 of the traffic load (i.e., information on the physical network). The load data is stored in a traffic load transition table. The traffic load transition table includes future data subdivided into time periods (i.e., first prediction value). Paragraph 84, using past and present data to forecast power approximation (i.e., second prediction value)).
For motivation, please refer to claim 1.
Regarding claim 12, the limitations of claim 6 have been addressed. Marquezan, Mimura, and McMullin disclosed:
wherein the cost comprises a processing time cost (Mimura, Paragraph 73, based on the measurement results, reducing the convergence time of the scale out (i.e., reducing a processing time cost)).
For motivation, please refer to claim 1.
Regarding claim 17, the limitations of claim 1 have been addressed. Marquezan, Mimura, and McMullin disclosed:
wherein the electric power is based at least on renewable energy (McMullin, Paragraph 46, information associated with renewable resource availability is obtained).
Regarding claim 18, the limitations of claim 1 have been addressed. Marquezan, Mimura, and McMullin disclosed:
wherein the assign operation of the virtual network further comprises solving an optimization problem under an uncertainty of the first prediction value of the traffic volume of the service and an uncertainty of the second prediction value of electric power (McMullin, Paragraph 46, information associated with renewable resource availability is obtained. Paragraph 48, one or more expected outputs of the renewable energy resources for the future time period is calculated (i.e., second prediction value of electric power). Paragraph 49, the initial load forecast is then modified or adjusted based on the expected outputs for the renewable resources (i.e., adjusted due to not expected values)).
For motivation, please refer to claim 1.
Regarding claim 19, the limitations of claim 8 have been addressed. Marquezan, Mimura, and McMullin disclosed:
wherein the assign operation of the virtual network further comprises solving an optimization problem regarding the first prediction value of the traffic volume of the service and the second prediction value of electric power (Mimura, Paragraph 84, using past and present data to forecast power approximation (i.e., prediction value of electric power). Paragraph 85-89, the management and orchestration server 220 forecasts the number of virtual machines required in the future in each virtualized node (of the physical server group) by using the traffic load transition table and if the amount of resources required in the future is more than the current resources held by the physical server group, a scale out is requested (i.e., optimization problem)).
For motivation, please refer to claim 1.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/S.C.N/Examiner, Art Unit 2451
/Chris Parry/Supervisory Patent Examiner, Art Unit 2451
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