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 .
Response to Amendment
This action is responsive to the Applicant’s Application filed on June 9, 2026.
Claims 1, 11, and 17 have been amended.
Applicant's amendments necessitated new grounds of rejection.
This action is made final in view of the new grounds of rejection.
Claims 1, 11, and 17 are independent. As a result claims 1-20 are pending in this office action.
Response to Arguments
Applicant's argument filed June 9, 2026 regarding the rejection of claims 1-20 under 35 U.S.C 101, has been fully considered and is persuasive.
Applicants argue in substance:
Regarding claims 1-20, the applicants submit that the steps are being performed are directed to statutory subject matter under 101 because the claims as a whole integrates the exception into a practical application and are a technical improvement.
The argument of claims 1-20 have been fully considered and is persuasive.
Therefore, the 35 U.S.C. 101 rejection of claims 1-20 have been withdrawn.
Applicant's arguments filed June 9, 2026 regarding the rejection of claims 1, 11, and 17 under 35 U.S.C 103 have been fully considered but they are moot in view of the new grounds of rejection.
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 of this title, 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 set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied 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 1-7, 11-15, and 17-20 are rejected under 35 U.S.C. 103 as being unpatentable over Wu et al. (US 11,030,169)(hereinafter Wu) in view of Shathakumar et al. (US 2025/0173338)(hereinafter Shathakumar), and in further view of Vig et al. (US 9,996,573)(hereinafter Vig).
Regarding claim 1, Wu teaches system for scaling hardware capacity in a distributed database system configured to store data divided among a plurality of data partitions, the distributed database system comprising database hardware for hosting the plurality of data partitions, the system comprising: at least one processor; and at least one non-transitory computer-readable storage medium storing instructions that (see Fig. 7, col. 17 ln 55-58, discloses processor and memory) , when executed by the at least one processor, cause the at least one processor to: determine, for each of at least some of the plurality of data partitions, a hardware capacity for hosting the data partition (see Fig. 1A, Fig. 2A, Fig. 3, col.4 ln 29-34, col. 8 ln 46-54, col. 14 ln 37-40, discloses determining for each respective shard (partition) capacity of a node hosting a given shard).
Wu does not explicitly teach the determining comprising: determine a first hardware capacity for hosting a first data partition of the plurality of data partitions based at least in part on a first set of operations for execution on the first data partition; and determine a second hardware capacity, different from the first hardware capacity, for hosting a second data partition of the plurality of data partitions based at least in part on second set of operations for execution on the second data partition; configure the database hardware based on hardware capacities determined for hosting the at least some data partitions, the configuring comprising: configure a first set of the database hardware, having the first hardware capacity, to host the first data partition; and configure a second set of the database hardware having the second hardware capacity to host the second data partition.
Shanthakumar teaches configure the database hardware based on hardware capacities determined for hosting the at least some data partitions (see Fig. 1, Fig.6-7, para [0023-0024], para [0070], discloses database capacity units, DCUs (database hardware) making scaling decisions based on performance metrics (capacities) determined for hosting shards (partitions)), the configuring comprising: configure a first set of the database hardware, having the first hardware capacity, to host the first data partition (see Fig. 1, Fig. 4, Fig.7-8, para [0023-0024], para [0072, 0074], discloses database capacity units, DCUs (database hardware) allocation for a first set of DCUs to host a first shard (partition)); and configure a second set of the database hardware having the second hardware capacity to host the second data partition (see Fig. 1, Fig. 4, Fig.7-8, para [0023-0024], para [0072, 0074], discloses database capacity units, DCUs (database hardware) allocation for a second set of DCUs to host a second shard (partition)).
Wu/Shanthakumar are analogous arts as they are each from the same field of endeavor of database systems.
Before the effective filing date of the invention it would have been obvious to a person of ordinary skill in the art to modify the system of Wu to configure sets of database hardware capacities from disclosure of Shanthakumar. The motivation to combine these arts is disclosed by Shanthakumar as “dynamically scaling a distributed database according to a cluster-wide resource allocation” (para [0020]) and configuring sets of database hardware capacities are well known to persons of ordinary skill in the art, and therefore one of ordinary skill would have good reason to pursue the known options within his or her technical grasp that would lead to anticipated success.
Wu/Shanthakumar does not explicitly teach the determining comprising: determine a first hardware capacity for hosting a first data partition of the plurality of data partitions based at least in part on a first set of operations for execution on the first data partition; and determine a second hardware capacity, different from the first hardware capacity, for hosting a second data partition of the plurality of data partitions based at least in part on second set of operations for execution on the second data partition.
Vig teaches the determining comprising: determine a first hardware capacity for hosting a first data partition of the plurality of data partitions based at least in part on a first set of operations for execution on the first data partition (see Fig. 5-6, col. 6 ln 62-col. 7 ln 7, col. 8 ln 17-20, discloses determining a first capacity for a first data partition based on a first set of read and write operations); and determine a second hardware capacity, different from the first hardware capacity, for hosting a second data partition of the plurality of data partitions based at least in part on second set of operations for execution on the second data partition (see Figs. 6-7, col. 6 ln 62-col. 7 ln 7, col. 9 ln 1-7, discloses determining a second capacity different from first capacity for a second data partition based on a second set of read and write operations).
Wu/Shanthakumar/Vig are analogous arts as they are each from the same field of endeavor of database systems.
Before the effective filing date of the invention it would have been obvious to a person of ordinary skill in the art to modify the system of Wu/ Shanthakumar to include sets of operations for execution of data partitions from disclosure of Vig. The motivation to combine these arts is disclosed by Vig as “improve the scalability of the system by allowing workload to be shared among multiple computing nodes” (col. 2 ln 45-47) and including sets of operations for execution of data partitions is well known to persons of ordinary skill in the art, and therefore one of ordinary skill would have good reason to pursue the known options within his or her technical grasp that would lead to anticipated success.
Regarding claim 11, Wu teaches a method for scaling hardware capacity in a distributed database system configured to store data divided among a plurality of data partitions, the distributed database system comprising database hardware for hosting the plurality of data partitions, the method comprising: using at least one processor to perform (see Fig. 7, col. 17 ln 55-58, discloses processor): determining, for each of at least some of the plurality of data partitions, a hardware capacity for hosting the data partition (see Fig. 1A, Fig. 2A, Fig. 3, col.4 ln 29-34, col. 8 ln 46-54, col. 14 ln 37-40, discloses determining for each respective shard (partition) capacity of a node hosting a given shard).
Wu does not explicitly teach the determining comprising: determining a first hardware capacity for hosting a first data partition of the plurality of data partitions based at least in part on a first set of operations for execution on the first data partition; and determining a second hardware capacity, different from the first hardware capacity, for hosting a second data partition of the plurality of data partitions based at least in part on second set of operations for execution on the second data partition; configuring the database hardware based on hardware capacities determined for hosting the at least some data partitions, the configuring comprising: configuring a first set of the database hardware, having the first hardware capacity, to host the first data partition; and configuring a second set of the database hardware having the second hardware capacity to host the second data partition.
Shanthakumar teaches configure the database hardware based on hardware capacities determined for hosting the at least some data partitions (see Fig. 1, Fig.6-7, para [0023-0024], para [0070], discloses database capacity units, DCUs (database hardware) making scaling decisions based on performance metrics (capacities) determined for hosting shards (partitions)), the configuring comprising: configure a first set of the database hardware, having the first hardware capacity, to host the first data partition (see Fig. 1, Fig. 4, Fig.7-8, para [0023-0024], para [0072, 0074], discloses database capacity units, DCUs (database hardware) allocation for a first set of DCUs to host a first shard (partition)); and configure a second set of the database hardware having the second hardware capacity to host the second data partition (see Fig. 1, Fig. 4, Fig.7-8, para [0023-0024], para [0072, 0074], discloses database capacity units, DCUs (database hardware) allocation for a second set of DCUs to host a second shard (partition)).
Wu/Shanthakumar are analogous arts as they are each from the same field of endeavor of database systems.
Before the effective filing date of the invention it would have been obvious to a person of ordinary skill in the art to modify the system of Wu to configure sets of database hardware capacities from disclosure of Shanthakumar. The motivation to combine these arts is disclosed by Shanthakumar as “dynamically scaling a distributed database according to a cluster-wide resource allocation” (para [0020]) and configuring sets of database hardware capacities are well known to persons of ordinary skill in the art, and therefore one of ordinary skill would have good reason to pursue the known options within his or her technical grasp that would lead to anticipated success.
Wu/Shanthakumar does not explicitly teach the determining comprising: determine a first hardware capacity for hosting a first data partition of the plurality of data partitions based at least in part on a first set of operations for execution on the first data partition; and determine a second hardware capacity, different from the first hardware capacity, for hosting a second data partition of the plurality of data partitions based at least in part on second set of operations for execution on the second data partition.
Vig teaches the determining comprising: determine a first hardware capacity for hosting a first data partition of the plurality of data partitions based at least in part on a first set of operations for execution on the first data partition (see Fig. 5-6, col. 6 ln 62-col. 7 ln 7, col. 8 ln 17-20, discloses determining a first capacity for a first data partition based on a first set of read and write operations); and determine a second hardware capacity, different from the first hardware capacity, for hosting a second data partition of the plurality of data partitions based at least in part on second set of operations for execution on the second data partition (see Figs. 6-7, col. 6 ln 62-col. 7 ln 7, col. 9 ln 1-7, discloses determining a second capacity different from first capacity for a second data partition based on a second set of read and write operations).
Wu/Shanthakumar/Vig are analogous arts as they are each from the same field of endeavor of database systems.
Before the effective filing date of the invention it would have been obvious to a person of ordinary skill in the art to modify the system of Wu/ Shanthakumar to include sets of operations for execution of data partitions from disclosure of Vig. The motivation to combine these arts is disclosed by Vig as “improve the scalability of the system by allowing workload to be shared among multiple computing nodes” (col. 2 ln 45-47) and including sets of operations for execution of data partitions is well known to persons of ordinary skill in the art, and therefore one of ordinary skill would have good reason to pursue the known options within his or her technical grasp that would lead to anticipated success.
Regarding claim 17, Wu teaches a distributed database system configured to store data divided among a plurality of data partitions, the distributed database system comprising: database hardware configured to host the plurality of data partitions, wherein the database hardware is configurable to provide different hardware capacities for hosting different data partitions (see Fig. 5-6, col. 7 ln 54-65, col. 8 ln 46-54, discloses distributed database services distributed across resources of different capacities for hosting shards (partitions)).
Wu does not explicitly teach at least one processor configured to dynamically modify a configuration of the database hardware to update a hardware capacity used to host a particular data partition of the plurality of data partitions, at least in part based on a set of operations for execution on the particular data partition of the plurality of data partitions.
Shanthakumar teaches at least one processor configured to dynamically modify a configuration of the database hardware to update a hardware capacity used to host a particular data partition of the plurality of data partitions (see Fig. 1, Fig. 11, para [0022-0023], discloses dynamically scaling distributed database according to a cluster-wide resource allocation of capacity based on performance metrics).
Wu/Shanthakumar are analogous arts as they are each from the same field of endeavor of database systems.
Before the effective filing date of the invention it would have been obvious to a person of ordinary skill in the art to modify the system of Wu to dynamically modify configuration of database hardware update hardware capacity from disclosure of Shanthakumar. The motivation to combine these arts is disclosed by Shanthakumar as “dynamically scaling a distributed database according to a cluster-wide resource allocation” (para [0020]) and dynamically modify configuration of database hardware update hardware capacity is well known to persons of ordinary skill in the art, and therefore one of ordinary skill would have good reason to pursue the known options within his or her technical grasp that would lead to anticipated success.
Wu/Shanthakumar does not explicitly teach at least in part based on a set of operations for execution on the particular data partition of the plurality of data partitions.
Vig teaches at least in part based on a set of operations for execution on the particular data partition of the plurality of data partitions (see Fig. 5-7, col. 6 ln 62-col. 7 ln 7, col. 8 ln 17-20, discloses determining a first and second capacity for a first data partition and a second data partition based on a first and second set of read and write operations).
Wu/Shanthakumar/Vig are analogous arts as they are each from the same field of endeavor of database systems.
Before the effective filing date of the invention it would have been obvious to a person of ordinary skill in the art to modify the system of Wu/ Shanthakumar to include sets of operations for execution of data partitions from disclosure of Vig. The motivation to combine these arts is disclosed by Vig as “improve the scalability of the system by allowing workload to be shared among multiple computing nodes” (col. 2 ln 45-47) and including sets of operations for execution of data partitions is well known to persons of ordinary skill in the art, and therefore one of ordinary skill would have good reason to pursue the known options within his or her technical grasp that would lead to anticipated success.
Regarding claims 2 and 12, Wu/Shanthakumar/Vig teach a system of claim 1 and a method of claim 11.
Wu does not explicitly teach configuring the first set of database hardware, having the first hardware capacity, to host the first data partition comprises configuring database hardware with first computer processing unit (CPU) hardware to host the first data partition; and configuring the second set of database hardware, having the second hardware capacity, to host the second data partition comprises configuring database hardware with second CPU hardware, different from the first CPU hardware, to host the second data partition.
Shanthakumar teaches configuring the first set of database hardware, having the first hardware capacity, to host the first data partition comprises configuring database hardware with first computer processing unit (CPU) hardware to host the first data partition (see Fig. 4, Figs. 6-7. para [0070, 0072], para [0091], discloses configuring a first set of DCUs having a first capacity to house a first shard); and configuring the second set of database hardware, having the second hardware capacity, to host the second data partition comprises configuring database hardware with second CPU hardware, different from the first CPU hardware, to host the second data partition (see Fig. 4, Figs. 6-7. para [0070, 0072], para [0091], discloses configuring a second set of DCUs having a first capacity to house a second shard).
Regarding claims 3 and 13, Wu/Shanthakumar/Vig teach a system of claim 1 and a method of claim 11.
Wu does not explicitly teach configuring the first set of database hardware, having the first hardware capacity, to host the first data partition comprises configuring database hardware with a first amount of random access memory (RAM) to host the first data partition; and configuring the second set of database hardware, having the second hardware capacity to host the second data partition comprises configuring database hardware with a second amount of RAM, different from the first amount of RAM, to host the second data partition.
Shanthakumar teaches configuring the first set of database hardware, having the first hardware capacity, to host the first data partition comprises configuring database hardware with a first amount of random access memory (RAM) to host the first data partition (see Fig. 6, Fig. 15, para [0071], para [0108-0109], discloses database stored configured with a first amount of memory to host a first shard); and configuring the second set of database hardware, having the second hardware capacity to host the second data partition comprises configuring database hardware with a second amount of RAM, different from the first amount of RAM, to host the second data partition (see Fig. 6, Fig. 15, para [0071], para [0108-0109], discloses database stored configured with a second amount of memory to host a second shard).
Regarding claims 4 and 14, Wu/Shanthakumar/Vig teach a system of claim 1 and a method of claim 11.
Wu does not explicitly teach wherein determining the first hardware capacity for hosting the first data partition comprises: analyze operations performed on the first data partition over a time period to determine an indication of memory utilization during the time period; and determine the first hardware capacity based on the indication of memory utilization during the time period.
Shanthakumar teaches wherein determining the first hardware capacity for hosting the first data partition comprises: analyze operations performed on the first data partition over a time period to determine an indication of memory utilization during the time period (see para [0076], discloses rules to scale up DCUs or scale down DCUs, increasing or decreasing allocated number of DCUs if a certain percentage of DCUs is consumed over a period of time); and determine the first hardware capacity based on the indication of memory utilization during the time period (see para [0091], discloses determining capacity limitations for a DCU over a period of time).
Regarding claims 5 and 15, Wu/Shanthakumar/Vig teach a system of claim 1 and a method of claim 11.
Wu further teaches wherein determining the first hardware capacity for hosting the first data partition comprises modifying a previous hardware capacity determined for hosting the first data partition (see col. 5 ln 14-16, discloses increasing (modifying) capacity of set of nodes that host shards).
Regarding claim 6, Wu/Shanthakumar/Vig teach a system of claim 1.
Wu further teaches wherein modifying the previous hardware capacity for hosting the first data partition comprises increasing the previous hardware capacity for hosting the first data partition (see col. 5 ln 14-16, col. 9 ln 27-28, discloses increasing capacity of set of nodes that host shards).
Regarding claim 7, Wu/Shanthakumar/Vig teach a system of claim 1.
Wu further teaches wherein modifying the previous hardware capacity for hosting the first data partition comprises decreasing the previous hardware capacity for hosting the first data partition (see col. 9 ln 27-28, discloses decreasing resource capacity used).
Regarding claim18, Wu/Shanthakumar/Vig teach a system of claim 17.
Wu does not explicitly teach wherein the at least one processor is configured to modify a configuration of the database hardware to update the hardware capacity used to host the particular data partition based on a record of operations performed on the particular data partition over a time period.
Shanthakumar teaches wherein the at least one processor is configured to modify a configuration of the database hardware to update the hardware capacity used to host the particular data partition based on a record of operations performed on the particular data partition over a time period (see para [0076], discloses updating hardware capacity based on a period of time).
Regarding claim19, Wu/Shanthakumar/Vig teach a system of claim 17.
Wu does not explicitly teach wherein the at least one processor is configured to modify the configuration of the database hardware to update the hardware capacity used to host the particular data partition based on the record of operations performed on the particular data partition over the time period by performing: determine a memory utilization of the operations performed on the at least one data partition over the time period; modify the configuration of the database hardware to update the hardware capacity used to host the particular data partition based on the memory utilization.
Shanthakumar teaches wherein the at least one processor is configured to modify the configuration of the database hardware to update the hardware capacity used to host the particular data partition based on the record of operations performed on the particular data partition over the time period by performing: determine a memory utilization of the operations performed on the at least one data partition over the time period; modify the configuration of the database hardware to update the hardware capacity used to host the particular data partition based on the memory utilization (see para [0075-0076], discloses memory utilization for a resource over a period of time).
Regarding claim20, Wu/Shanthakumar/Vig teach a system of claim 17.
Wu does not explicitly teach wherein modifying the configuration of the database hardware to update the hardware capacity used to host the particular data partition comprises: determine whether the memory utilization meets a threshold memory utilization; and trigger the modification of the configuration of the database hardware to update the hardware capacity used to host the particular data partition in response to determining that the memory utilization meets the threshold memory utilization.
Shanthakumar teaches wherein modifying the configuration of the database hardware to update the hardware capacity used to host the particular data partition comprises: determine whether the memory utilization meets a threshold memory utilization (see para [0091-0092], discloses utilization over a period of time with respect to a threshold); and trigger the modification of the configuration of the database hardware to update the hardware capacity used to host the particular data partition in response to determining that the memory utilization meets the threshold memory utilization (see para [0093-0094], discloses scaling decisions made that trigger a wait period of time before reevaluating and allocating DCUs).
Claims 8-10 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Wu et al. (US 11,030,169)(hereinafter Wu) in view of Shathakumar et al. (US 2025/0173338)(hereinafter Shathakumar) and Vig as applied to claims 1 and 11, and in further view of Song et al. (US 2017/032011) (hereinafter Song).
Regarding claim 8, Wu/Shanthakumar/Vig teach a system of claim 1.
Wu/Shanthakumar/Vig does not explicitly teach wherein: the first data partition is replicated across a plurality of nodes; and the instructions further cause the at least one processor to: determine a hardware capacity for a first node of the plurality of nodes; and determine a hardware capacity for a second node of the plurality of nodes, wherein the hardware capacity determined for the second node is different from the hardware capacity of the determined for the first node; and configure the first set of database hardware to host the first node using the hardware capacity determined for the first node and to host the second node using the hardware capacity determined for the second node.
Song teaches wherein: the first data partition is replicated across a plurality of nodes (see Fig. 3B, para [0024], discloses sharding protocol and configurable replication of shards across nodes); and the instructions further cause the at least one processor to: determine a hardware capacity for a first node of the plurality of nodes (see para [0025], para [0037], discloses capacities of respective nodes and shard allocation); and determine a hardware capacity for a second node of the plurality of nodes, wherein the hardware capacity determined for the second node is different from the hardware capacity of the determined for the first node (see para [0025], para [0037], discloses capacities of respective nodes and shard allocation); and configure the first set of database hardware to host the first node using the hardware capacity determined for the first node and to host the second node using the hardware capacity determined for the second node (see fig. 1, para [0013, 0015], para [0049-0050], discloses configuring respective capacities for respective nodes based on parameters).
Wu/Shanthakumar/Vig/Song are analogous arts as they are each from the same field of endeavor of database systems.
Before the effective filing date of the invention it would have been obvious to a person of ordinary skill in the art to modify the system of Wu/Shanthakumar/Vig to include partition replication across plurality of nodes from disclosure of Song. The motivation to combine these arts is disclosed by Song as “a partial replication system can significantly improve scalability and convergence of spine nodes,” (para [0025]) and including partition replication across plurality of nodes is well known to persons of ordinary skill in the art, and therefore one of ordinary skill would have good reason to pursue the known options within his or her technical grasp that would lead to anticipated success.
Regarding claims 9 and 16, Wu/Shanthakumar/Vig teach a system of claim 1 and a method of claim 11.
Wu/Shanthakumar/Vig does not explicitly teach wherein determining the first hardware capacity for hosting the first data partition comprises: selecting the first hardware capacity from among a plurality of hardware capacities that the database hardware is configurable to provide.
Song teaches wherein determining the first hardware capacity for hosting the first data partition comprises: selecting the first hardware capacity from among a plurality of hardware capacities that the database hardware is configurable to provide (see Figs. 3A-4, para [0037], discloses closes selecting a capacity level for respective spine in shard allocation).
Wu/Shanthakumar/Vig/Song are analogous arts as they are each from the same field of endeavor of database systems.
Before the effective filing date of the invention it would have been obvious to a person of ordinary skill in the art to modify the system of Wu/Shanthakumar/Vig to include partition replication across plurality of nodes from disclosure of Song. The motivation to combine these arts is disclosed by Song as “a partial replication system can significantly improve scalability and convergence of spine nodes,” (para [0025]) and including partition replication across plurality of nodes is well known to persons of ordinary skill in the art, and therefore one of ordinary skill would have good reason to pursue the known options within his or her technical grasp that would lead to anticipated success.
Regarding claim 10, Wu/Shanthakumar/Vig teach a system of claim 1.
Wu/Shanthakumar/Vig does not explicitly teach wherein each of the plurality of hardware capacities comprises a specification of at least one of: CPU hardware to be used to host a data partition; and an amount of RAM to be used to host a data partition.
Song teaches wherein each of the plurality of hardware capacities comprises a specification of at least one of: CPU hardware to be used to host a data partition; and an amount of RAM to be used to host a data partition (see Figs. 1-3B, par [0030], para [0082-0083], discloses host for shards and memory capacities).
Wu/Shanthakumar/Vig/Song are analogous arts as they are each from the same field of endeavor of database systems.
Before the effective filing date of the invention it would have been obvious to a person of ordinary skill in the art to modify the system of Wu/Shanthakumar/Vig to include partition replication across plurality of nodes from disclosure of Song. The motivation to combine these arts is disclosed by Song as “a partial replication system can significantly improve scalability and convergence of spine nodes,” (para [0025]) and including partition replication across plurality of nodes is well known to persons of ordinary skill in the art, and therefore one of ordinary skill would have good reason to pursue the known options within his or her technical grasp that would lead to anticipated success.
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to COURTNEY HARMON whose telephone number is (571)270-5861. The examiner can normally be reached M-F 9am - 5pm.
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, Ann Lo can be reached at 571-272-9767. 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.
/Courtney Harmon/Primary Examiner, Art Unit 2159
Prosecution Insights