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 .
Status of Claims
Claims 1-17 are pending in this Office Action.
Claims 3-8 are elected without traverse.
Claims 2, 10-15 are withdrawn.
Claims 1, 3-9 and 16-17 are rejected.
Election/Restrictions
This application contains claims directed to the following patentably distinct species:
Species I: Claim 2 – the embodiment (possible implementation), in paragraphs [0083]-[0085], is directed to identifying information of at least one tenant associated with the resource consumer and at least one requested resource plan associated with the resource consumer.
Species II: Claims 3-8 – the embodiment (possible implementation), in paragraphs [0111]-[0121], is directed to scheduling each of the at least one resource consumer with a first bandwidth onto the endpoint and scheduling each of the at least one resource consumer with corresponding second bandwidths onto the levels of networks based on the first bandwidth.
Species III: Claims 10-15 – the embodiment (possible implementation), in paragraphs [0099]-[0104], is directed to training a model based on sampled network usage patterns of multiple groups of sampled resource consumers, bandwidth requirement information of sampled resource consumers in the multiple groups and sampled bandwidth utilization information of the sampled resource consumers in the multiple groups.
The species are independent or distinct because each species, as claimed, requires a mutually exclusive limitation(s). For example, species I requires identifying information of at least one tenant associated with the resource consumer and at least one requested resource plan associated with the resource consumer, species II requires scheduling each of the at least one resource consumer with a first bandwidth onto the endpoint and scheduling each of the at least one resource consumer with corresponding second bandwidths onto the levels of networks based on the first bandwidth, and species III requires training a model based on sampled network usage patterns of multiple groups of sampled resource consumers, bandwidth requirement information of sampled resource consumers in the multiple groups and sampled bandwidth utilization information of the sampled resource consumers in the multiple groups. In addition, these species are not obvious variants of each other based on the current record.
Applicant is required under 35 U.S.C. 121 to elect a single disclosed species, or a single grouping of patentably indistinct species, for prosecution on the merits to which the claims shall be restricted if no generic claim is finally held to be allowable. Currently, claims 1, 9, 16, 17 are generic.
There is a search and/or examination burden for the patentably distinct species as set forth above because at least the following reason(s) apply:
the species have acquired a separate status in the art in view of their different classification;
the species have acquired a separate status in the art due to their recognized divergent subject matter;
the species require a different field of search (e.g., searching different classes/subclasses or electronic resources, or employing different search strategies or search queries);
the prior art applicable to one specie would not likely be applicable to another specie;
the species are likely to raise different non-prior art issues under 35 U.S.C. 101 and/or 35 U.S.C. 112, first paragraph.
Applicant is advised that the reply to this requirement to be complete must include (i) an election of a species to be examined even though the requirement may be traversed (37 CFR 1.143) and (ii) identification of the claims encompassing the elected species or grouping of patentably indistinct species, including any claims subsequently added. An argument that a claim is allowable or that all claims are generic is considered nonresponsive unless accompanied by an election.
The election may be made with or without traverse. To preserve a right to petition, the election must be made with traverse. If the reply does not distinctly and specifically point out supposed errors in the election of species requirement, the election shall be treated as an election without traverse. Traversal must be presented at the time of election in order to be considered timely. Failure to timely traverse the requirement will result in the loss of right to petition under 37 CFR 1.144. If claims are added after the election, applicant must indicate which of these claims are readable on the elected species or grouping of patentably indistinct species.
Should applicant traverse on the ground that the species, or groupings of patentably indistinct species from which election is required, are not patentably distinct, applicant should submit evidence or identify such evidence now of record showing them to be obvious variants or clearly admit on the record that this is the case. In either instance, if the examiner finds one of the species unpatentable over the prior art, the evidence or admission may be used in a rejection under 35 U.S.C. 103 or pre-AIA 35 U.S.C. 103(a) of the other species.
Upon the allowance of a generic claim, applicant will be entitled to consideration of claims to additional species which depend from or otherwise require all the limitations of an allowable generic claim as provided by 37 CFR 1.141.
Applicant’s election without traverse of species II in the reply filed on 01/16/2026 is acknowledged.
Drawings
The drawings are objected to because Figs. 1A,B are not clear and Figs. 1C, 2, 4A-D, 5, 6 are missing numeric labels. Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. The figure or figure number of an amended drawing should not be labeled as “amended.” If a drawing figure is to be canceled, the appropriate figure must be removed from the replacement sheet, and where necessary, the remaining figures must be renumbered and appropriate changes made to the brief description of the several views of the drawings for consistency. Additional replacement sheets may be necessary to show the renumbering of the remaining figures. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
Specification
The title of the invention is not descriptive. A new title is required that is clearly indicative of the invention to which the claims are directed.
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.
Claim(s) 1, 9, 16, 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Rastogi (US 20190146848) in view of Patel (US 9338068), and further in view of Li (US 12072954) and Raymond (US 20180331885).
1, 16, 17. Rastogi teaches:
A method for scheduling network resources, comprising: – in paragraphs [0008]-[0125] (Resource scheduling is done based on historical statistics collected.)
receiving, by a resource scheduler from a client, a resource request indicating at least one resource consumer; – in paragraphs [0008]-[0125] (The resource manager is configured to receive at least one resource request from at least an application, the application is received with at least an application name and a tag, and the resource request contains at least a resource requirement of an application task for execution.)
receiving, by the resource scheduler from a predictor, resource prediction based on the resource request, – in paragraphs [0008]-[0125] (The resource manager also comprises a resource prediction module configured to provide at least a soft limit for application task based on at least a historical resource usage statistics pre-stored in a history data store or return to a hard limit for application task configured by at least one user.)
Rastogi does not explicitly teach:
wherein the resource prediction comprises a predicted network bandwidth and a predicted network usage pattern for each of the at least one resource consumer.
However, Patel teaches:
wherein the resource prediction comprises a predicted network bandwidth and a predicted network usage pattern for each of the at least one resource consumer, – on lines 1-67 in columns 1-7 (The method of FIG. 2 also includes identifying (206) based on the historical network usage pattern (250), by the network monitor (299), a first set (252) of future time periods predicted to correspond with low network usage. Identifying (206) based on the historical network usage pattern (250), by the network monitor (299), a first set (252) of future time periods predicted to correspond with low network usage may be carried out by searching for patterns that differentiate grouping of past time periods; using the classification of the groups to develop patterns and classifications indicating future periods as corresponding to a particular level of bandwidth utilization.)
It would have been obvious for one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify Rastogi with Patel to include wherein the resource prediction comprises a predicted network bandwidth and a predicted network usage pattern for each of the at least one resource consumer, as taught by Patel, on lines 1-67 in columns 1-2, to provide a technique for efficient network bandwidth utilization in a distributed processing system.
Combination of Rastogi and Patel does not explicitly teach:
wherein the resource prediction is obtained by the predictor through prediction inferring based on a pre-trained model, and the pre-trained model is obtained from local and central training.
However, Li teaches:
wherein the resource prediction is obtained by the predictor through prediction inferring based on a pre-trained model, and – on lines 1-67 in columns 3-98 (Trained machine learning models corresponding to one or more neural networks may be used to infer or predict information.)
the pre-trained model is obtained from local and central training; and – on lines 1-67 in columns 3-98 (Federated learning is performed wherein a plurality of edge devices train local models of neural networks on locally-maintained training data and provide their local models to a central server after a federated round of training. A central server can aggregate a plurality of local models to generate a global model that can then be shared with edge devices to continue training in subsequent training rounds.)
It would have been obvious for one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify Rastogi and Patel with Li to include wherein the resource prediction is obtained by the predictor through prediction inferring based on a pre-trained model, and the pre-trained model is obtained from local and central training, as taught by Li, on lines 1-67 in column 1-2, to perform training using neural networks, wherein a plurality of one or more edge neural networks are locally trained on local training data and local training is aggregated at a central server.
Combination of Rastogi, Patel, and Li does not explicitly teach:
scheduling, by the resource scheduler based on resource requirement information, the resource prediction and resource availability, each of the at least one resource consumer onto an endpoint and levels of networks.
However, Raymond teaches:
scheduling, by the resource scheduler based on resource requirement information, the resource prediction and resource availability, each of the at least one resource consumer onto an endpoint and levels of networks. – in paragraphs [0020]-[0067] (The criteria of the rules may indicate, for example, required capabilities of resources, performance requirements (e.g., latency) of service components, regulations, or business criteria (e.g., according to a contract or service-level agreement (SLA)). A rule to satisfy requirements of a service-level agreement may, indicate that a cost (e.g., a monetary cost) of allocating the service component to a given resource must be less than a threshold cost. Based on various factors or consideration (e.g., available resources on computing devices, the nature of the service components and regulatory restrictions, performance objectives, latency, complexity of calculations, proximity of other service components, availability of data, high availability objectives, failure recovery constraints, affinity and non-affinity rules, cost of resources, traffic forecasts, trends and usage predictions, service-level agreements, administrative domains controlling resources, data privacy, environmental aspects, etc.), the hierarchical orchestrator 150 may assign one or groups of service components to a level. Additionally, the hierarchical orchestrator 150 may assign service components for a particular information service to more than one level. For example, if ten instances of a service component are required, the hierarchical orchestrator 150 may assign eight of the instances to level 2 and the remaining two instances to level 1.)
It would have been obvious for one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify Rastogi, Patel, and Li with Raymond to include scheduling, by the resource scheduler based on resource requirement information, the resource prediction and resource availability, each of the at least one resource consumer onto an endpoint and levels of networks, as taught by Raymond, in paragraphs [0002]-[0020], to effectively distribute service components among the computing devices while maintaining satisfactory performance and reliability.
9. The method according to claim 1, – refer to the indicated claim for reference(s).
Patel teaches:
wherein the predicted network usage pattern is one of a low bandwidth pattern, a sustained high bandwidth pattern, a fluctuated high bandwidth pattern, or a bursty bandwidth pattern. – on lines 1-67 in columns 1-7 (The method of FIG. 2 also includes identifying (206) based on the historical network usage pattern (250), by the network monitor (299), a first set (252) of future time periods predicted to correspond with low network usage. Identifying (206) based on the historical network usage pattern (250), by the network monitor (299), a first set (252) of future time periods predicted to correspond with low network usage may be carried out by searching for patterns that differentiate grouping of past time periods; using the classification of the groups to develop patterns and classifications indicating future periods as corresponding to a particular level of bandwidth utilization.)
Claim(s) 3 is/are rejected under 35 U.S.C. 103 as being unpatentable over Rastogi (US 20190146848) in view of Patel (US 9338068), and further in view of Li (US 12072954), Raymond (US 20180331885), and Barness (US 20090113438).
3. The method according to claim 1, – refer to the indicated claim for reference(s).
Combination of Rastogi, Patel, Li, and Raymond does not explicitly teach:
wherein the scheduling, by the resource scheduler based on the resource requirement information, the resource prediction and the resource availability, each of the at least one resource consumer onto the endpoint and the levels of networks comprises: scheduling, by the resource scheduler, each of the at least one resource consumer with a first bandwidth onto the endpoint based on the predicted network bandwidth and the predicted network usage pattern; and scheduling, by the resource scheduler, each of the at least one resource consumer with corresponding second bandwidths onto the levels of networks based on the first bandwidth.
However, Barness teaches:
wherein the scheduling, by the resource scheduler based on the resource requirement information, the resource prediction and the resource availability, each of the at least one resource consumer onto the endpoint and the levels of networks comprises: scheduling, by the resource scheduler, each of the at least one resource consumer with a first bandwidth onto the endpoint based on the predicted network bandwidth and the predicted network usage pattern; and scheduling, by the resource scheduler, each of the at least one resource consumer with corresponding second bandwidths onto the levels of networks based on the first bandwidth. – in paragraphs (The job scheduler to allocate critical jobs on the compute nodes. These other resource attributes may include a predicted network utilization of the job 416 and a status of non-constant data job state 418. The predicted network utilization indicates a relative factor on how much the job is expected to utilize the network of the I/O node. Jobs that drive high network utilization can benefit from running near the I/O node due to less latency and fewer points of failure.)
It would have been obvious for one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify Rastogi, Patel, Li, and Raymond with Barness to include wherein the scheduling, by the resource scheduler based on the resource requirement information, the resource prediction and the resource availability, each of the at least one resource consumer onto the endpoint and the levels of networks comprises: scheduling, by the resource scheduler, each of the at least one resource consumer with a first bandwidth onto the endpoint based on the predicted network bandwidth and the predicted network usage pattern; and scheduling, by the resource scheduler, each of the at least one resource consumer with corresponding second bandwidths onto the levels of networks based on the first bandwidth, as taught by Barness, in paragraphs [0002]-[0017], to optimization of job distribution on a multi-node computer system.
Claim(s) 4-8 is/are rejected under 35 U.S.C. 103 as being unpatentable over Rastogi (US 20190146848) in view of Patel (US 9338068), and further in view of Li (US 12072954), Raymond (US 20180331885), Barness (US 20090113438), and Casillas (US 20200334088).
4. The method according to claim 3, – refer to the indicated claim for reference(s).
Combination of Rastogi, Patel, Li, Raymond and Barness does not explicitly teach:
wherein the scheduling, by the resource scheduler, each of the at least one resource consumer with the corresponding second bandwidths onto the levels of networks based on the first bandwidth comprises: determining, by the resource scheduler for each of the at least one resource consumer, the corresponding second bandwidths onto the levels of networks based on the first bandwidth; for each of the levels of networks, determining, by the resource scheduler based on the predicted network usage pattern for each of the at least one resource consumer, whether a second bandwidth at a network level meets a preset bandwidth requirement for the network level; and upon determining that the corresponding second bandwidths meet preset bandwidth requirements for the levels of networks, scheduling, by the resource scheduler, each of the at least one resource consumer with the corresponding second bandwidths onto the levels of networks.
However, Casillas teaches:
wherein the scheduling, by the resource scheduler, each of the at least one resource consumer with the corresponding second bandwidths onto the levels of networks based on the first bandwidth comprises: determining, by the resource scheduler for each of the at least one resource consumer, the corresponding second bandwidths onto the levels of networks based on the first bandwidth; for each of the levels of networks, determining, by the resource scheduler based on the predicted network usage pattern for each of the at least one resource consumer, whether a second bandwidth at a network level meets a preset bandwidth requirement for the network level; and upon determining that the corresponding second bandwidths meet preset bandwidth requirements for the levels of networks, scheduling, by the resource scheduler, each of the at least one resource consumer with the corresponding second bandwidths onto the levels of networks. – in paragraphs [0041]-[0079] (The zone limits optimization engine 206 is configured to define the limits of the reservations zones for different groups or tiers of online entities. For example, the optimization engine 206 may set the values of L.sub.1 through L.sub.4 for the reservation zones shown in FIG. 1. In some implementations, the optimization engine 206 sets the boundaries between reservation zones (i.e., the limits of the reservation zones) at points where the probabilistically expected value from an entity's usage of the shared resource 202 in a higher tier equals the actual value that would be derived from an entity's usage of the shared resource 202 in the tier immediately below the higher tier. For example, the optimization engine 206 may set the boundary L.sub.1 between reservation zones 1 and 2 at the point where the expected value from a tier 1 entity's usage of the shared resource equals the value from a tier 2 entity's usage of the shared resource 202. Likewise, the optimization engine 206 may set the boundary L.sub.2 between reservation zones 2 and 3 at the point where the expected value from a tier 2 entity's usage of the shared resource equals the value from a tier 3 entity's usage of the shared resource 202. The expected value of an entity's usage of the shared resource 202 can be a function of the entity's priority and the probability that the entity will actually use or request to use a given level of capacity of the shared resource 202 (e.g. they may be proportional to each other). The expected value of an entity's usage can be derived from the usage forecast data 220 and entity data 224 that indicates a relative priority (e.g., the priority tier or priority score) of the entity. Thus, in general, when a low-value opportunity presents (e.g. from a lower tier entity), the system may compare the value of that opportunity to the probabilistic expected value of a potential higher-value opportunity arising in the future. The low-value opportunity may be granted if it meets or exceeds the probabilistic expected value of a potential higher-value opportunity arising in the future.)
It would have been obvious for one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify Rastogi, Patel, Li, Raymond and Barness with Casillas to include wherein the scheduling, by the resource scheduler, each of the at least one resource consumer with the corresponding second bandwidths onto the levels of networks based on the first bandwidth comprises: determining, by the resource scheduler for each of the at least one resource consumer, the corresponding second bandwidths onto the levels of networks based on the first bandwidth; for each of the levels of networks, determining, by the resource scheduler based on the predicted network usage pattern for each of the at least one resource consumer, whether a second bandwidth at a network level meets a preset bandwidth requirement for the network level; and upon determining that the corresponding second bandwidths meet preset bandwidth requirements for the levels of networks, scheduling, by the resource scheduler, each of the at least one resource consumer with the corresponding second bandwidths onto the levels of networks, as taught by Casillas, in paragraphs [0001]-[0041], to provide techniques for managing allocation of capacity of shared computing resources, such as resources provided to tenants of a cloud computing platform.
5. The method according to claim 4, – refer to the indicated claim for reference(s).
Casillas teaches:
wherein the preset bandwidth requirement comprises: in a case that the predicted network usage pattern for a resource consumer is a low bandwidth pattern, the second bandwidth being allocated to the resource consumer at each of the levels of networks is from a reserved bandwidth quota, wherein the reserved bandwidth quota is shared among resource consumers with the low bandwidth pattern; in a case that the predicted network usage pattern for the resource consumer is a sustained high bandwidth pattern, for each of the levels of networks, the second bandwidth being allocated to the resource consumer at the network level is from an available bandwidth and a sustained high available bandwidth; or in other cases, for each of the levels of networks, the second bandwidth being allocated to the resource consumer at the network level is from the available bandwidth. – in paragraphs [0041]-[0079] (As usage forecasts change, new reservations are made or reservations cancelled, changes occur in the priorities or makeup of online entities, changes in available capacity, or a combination of these and other factors, the boundaries of the reservation zones may be updated to reflect recent conditions. In this way, rather than assessing fixed usage quotas to individual entities or groups of entities, the system 200 may be responsive to changing conditions and can update the reservation zone limits to account for changed conditions.)
6. The method according to claim 4, – refer to the indicated claim for reference(s).
Casillas teaches:
wherein the determining the corresponding second bandwidths for each of the at least one resource consumer comprises: for a first network level among the levels of networks, a second bandwidth for the resource consumer at the first network level is obtained by multiplying the first bandwidth for the endpoint and a bandwidth percentage for the first network level; for network levels other than the first network level, a second bandwidth for the resource consumer at an (n+1)-th network level is obtained by multiplying a second bandwidth for the resource consumer at an n-th network level and a bandwidth percentage for the (n+1)-th network level, wherein n is an integer greater than or equal to 1; wherein the bandwidth percentage is greater than or equal to 0.0 or 0%, and smaller than or equal to 1.0 or 100%. – in paragraphs [0041]-[0079] (An entity may self-impose an activity-specific capacity limit and a total capacity limit that restricts the amount of capacity the entity may consume across all activities over a period of time. The shared resource manager can verify that the amount of capacity requested is within all applicable limits including the individual activity-specific limit, the self-imposed total capacity limit, and the limits of the reservation zone for the corresponding priority tier of the requesting entity. Only if the request satisfies all applicable limits does the shared resource manager grant capacity for the request. In some implementations, the administrator of the shared resource can also impose additional limits, such as limits that restrict the share of capacity in a reservation zone that an individual entity can reserve or that can be reserved for an individual activity. For example, the platform may restrict any entity from using more than 90-percent of the capacity in the corresponding reservation zone for the entity. Amounts greater or less than 90-percent may also be assigned as appropriate.)
7. The method according to claim 6, – refer to the indicated claim for reference(s).
Casillas teaches:
wherein a second bandwidth for the resource consumer at the n-th network level is obtained by further multiplying a promotion rate for the n-th network level, wherein the promotion rate is greater than 0.0, and smaller than or equal to 1.0. – in paragraphs [0041]-[0079] (An entity may self-impose an activity-specific capacity limit and a total capacity limit that restricts the amount of capacity the entity may consume across all activities over a period of time. The shared resource manager can verify that the amount of capacity requested is within all applicable limits including the individual activity-specific limit, the self-imposed total capacity limit, and the limits of the reservation zone for the corresponding priority tier of the requesting entity. Only if the request satisfies all applicable limits does the shared resource manager grant capacity for the request. In some implementations, the administrator of the shared resource can also impose additional limits, such as limits that restrict the share of capacity in a reservation zone that an individual entity can reserve or that can be reserved for an individual activity. For example, the platform may restrict any entity from using more than 90-percent of the capacity in the corresponding reservation zone for the entity. Amounts greater or less than 90-percent may also be assigned as appropriate.)
8. The method according to claim 6, – refer to the indicated claim for reference(s).
Casillas teaches:
wherein for each of the at least one resource consumer, the resource request indicates whether communication partners of a resource consumer in a placement domain at the n-th network level are all inside the placement domain; in a case that the first bandwidth is smaller than or equal to a threshold, or the communication partners of the resource consumer are all inside the placement domain, the bandwidth percentage for the n-th network level is set to 0.0; in a case that the communication partners of the resource consumer are all outside the placement domain, the bandwidth percentage for the n-th network level is set to 1.0; or in other cases, the bandwidth percentage for the placement domain at the n-th network level is set to an oversubscription rate between the n-th network level and an (n+1)-th network level. – in paragraphs [0041]-[0079] (An entity may self-impose an activity-specific capacity limit and a total capacity limit that restricts the amount of capacity the entity may consume across all activities over a period of time. The shared resource manager can verify that the amount of capacity requested is within all applicable limits including the individual activity-specific limit, the self-imposed total capacity limit, and the limits of the reservation zone for the corresponding priority tier of the requesting entity. Only if the request satisfies all applicable limits does the shared resource manager grant capacity for the request. In some implementations, the administrator of the shared resource can also impose additional limits, such as limits that restrict the share of capacity in a reservation zone that an individual entity can reserve or that can be reserved for an individual activity. For example, the platform may restrict any entity from using more than 90-percent of the capacity in the corresponding reservation zone for the entity. Amounts greater or less than 90-percent may also be assigned as appropriate.)
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MUHAMMAD RAZA whose telephone number is (571)272-7734. The examiner can normally be reached Monday-Friday, 7:00 A.M.-5:00 P.M..
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Vivek Srivastava can be reached on (571)272-7304. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/MUHAMMAD RAZA/Primary Examiner, Art Unit 2449