DETAILED ACTION
Notice of Pre-AIA or AIA Status
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Remarks
This Action is in response to Applicant’s Response to Election/Restriction Requirement filed on February 11, 2026.
Election/Restrictions
Applicant’s election with traverse of Group I, claims 35-43 in the reply filed on February 11, 2026 is acknowledged. Because applicant did not distinctly and specifically point out the supposed errors in the restriction requirement, the election has been treated as an election without traverse (MPEP § 818.01(a)).
Information Disclosure Statement
5. The information disclosure statement (IDS) submitted on 01/10/2024 is being considered by the examiner.
Preliminary Amendment
The present Office Action is based upon the original patent application filed on November 13, 2023 as modified by the preliminary amendment also filed on November 13, 2023. Claims 35, 37-39, and 41 are now pending in the present application.
Drawings
The drawings are objected to because the lines, numbers, and letters are not durable, clean, black, sufficiently dense and dark, and uniformly thick and well-defined in Figures 4 and 10; the font is too small in Figures 4 and 6; and they contain black shading in Figures 5, 6, and 9. Figures 4 and 10 are all in grayscale which cause the lines, numbers, and letters to not be durable, clean, black, sufficiently dense and dark, and uniformly thick and well-defined. Additionally, drawings must be black and white (monochrome) except when another form (grayscale or color) is the only practicable medium for illustrating the claimed invention. For Figures 4 and 10, black and white drawings are sufficient to illustrate the claimed invention. Black and white drawings should be created and filed in monochrome, black only, no gray.
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. The replacement sheet(s) should be labeled “Replacement Sheet” in the page header (as per 37 CFR 1.84(c)) so as not to obstruct any portion of the drawing figures. 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. If a response to the present Office Action fails to include proper drawing corrections, corrected drawings or arguments therefor, the response can be held NON-RESPONSIVE and/or the application could be ABANDONED since the objections/corrections to the drawings are no longer held in abeyance.
Claim Rejections - 35 USC § 102
6. The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office Action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
7. Claims 35 and 37 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Irigi et al. (US 20150078262 A1), hereinafter Irigi.
Regarding claim 35, Irigi discloses a method, comprising the steps ([FIG. 9: 902-912], [0042] “FIG. 9 is a simplified flowchart showing activities associated with performing resource allocation […]”) of:
collecting, by a network management element from an access network element, a plurality of time-stamped geospatial location information associated to a respective one out of a plurality of mobile devices, wherein the plurality of time- stamped geospatial location information indicates the respective mobile devices' geospatial locations at certain times, ([Figures 2, 5B, 9]; [0024], [0019] “[…] a subscriber session condition relates to a user equipment dwell time, a user equipment location, a time, a subscriber session count, etc. Hence, the term "subscriber session condition" is a broad term that includes any condition, characteristic or parameter associated with session data, subscriber data, network data, location information, timing, etc. [0020] wireless access gateway resource allocation to be based, at least in part, on subscriber session analytic data aggregated, collected, […] over some period of time. […] accumulated data, modeled data, and/or the like may relate to multi-temporal subscriber session analytic data, similar as described regarding FIGS. 5A-5D. […] multi-temporal subscriber session analytic data may be received from memory, received from a separate apparatus, and/or the like. Determination of a subscriber session policy may, for example, be based, at least in part, on the received multi-temporal subscriber session analytic data. [0043] At block 902, the apparatus receives a multi-temporal subscriber session analytic data, similar as may be described regarding block 802 of FIG. 8. At block 904, the apparatus receives a subscriber session policy from at least one of a memory or a separate apparatus, similar as may be described regarding FIG. 2 and FIGS. 5A-5D […]. [0027] […] management of wireless access gateway resource allocation may be based, at least in part, on subscriber session location data. […] Such subscriber session location data may relate to global positioning system location data, triangulation location data, and/or the like, and may be similar as described regarding FIGS. 5A-5D”);
developing, by the network management element and for an aggregated group of the plurality of mobile devices, based on the plurality of time-stamped geospatial location information, a spatial-temporal time series cumulative distribution function, wherein the spatial-temporal time series cumulative distribution function, indicates a probability that a geospatial location defined by its coordinate values of a respective one out of the plurality of mobile devices has coordinate values less than or equal to a selected geospatial location's coordinate values within a defined time window, ((Figure 5B), [0018], [0027], [0033] “In the example of FIG. 5B, data 510 relates to multi-temporal subscriber session analytic data. In the example of FIG. 5B, each set of time data, duration data, location data, and count data comprises a subscriber session analytic data. For example, one subscriber session analytic data comprises time data 512, duration data 514, location data 516, and count data 518. Another subscriber session analytic data comprises time data 520, duration data 522, location data 524, and count data 526. Together, the plurality of subscriber session analytic data sets comprises the multi-temporal subscriber session analytic data. In the example of FIG. 5B, each subscriber session analytic data set may not be a discrete data set but may instead be integrated into a data average, a data model, and/or the like that is indicative of the multi-temporal subscriber session analytic data. In the example of FIG. 5B, data 510 may be associated with subscriber session analytic data in addition to the subscriber session analytic data shown”);
collecting time-stamped network resource requirement information associated with the plurality of mobile devices, wherein the time-stamped network resource requirement information indicates at least one of data throughput, quality-of-service flow characteristics, or application type associated with the mobile devices at corresponding times; ((Figures 2, 5B, 9), [0024], [0019] “[…] a subscriber session condition relates to a user equipment dwell time, a user equipment location, a time, a subscriber session count, etc. Hence, the term "subscriber session condition" is a broad term that includes any condition, characteristic or parameter associated with session data, subscriber data, network data, location information, timing, etc. [0020] wireless access gateway resource allocation to be based, at least in part, on subscriber session analytic data aggregated, collected, […] over some period of time. […] accumulated data, modeled data, and/or the like may relate to multi-temporal subscriber session analytic data, similar as described regarding FIGS. 5A-5D. […] multi-temporal subscriber session analytic data may be received from memory, received from a separate apparatus. [0031] The subscriber session management parameter may, […] relate to […] a quality of service parameter, […] The quality of service parameter may, for example, relate to bandwidth allocation, traffic priority, channel selection [0035] In the example of FIG. 5D, directive 580 comprises parameter 582, parameter 584, parameter 586, and parameter 588. Each of parameter 582, parameter 584, parameter 586, and parameter 588 may relate to a subscriber session management parameter, […] keep-alive timer parameter, a quality of service parameter”);
developing, based on the spatial-temporal time series cumulative distribution function and the time-stamped network resource requirement information, a weighted spatial-temporal time series cumulative distribution function, wherein the weighting reflects aggregated network resource requirements across the group of the mobile devices, ((Figure 5B), [0018], [0027], [0033] “In the example of FIG. 5B, data 510 relates to multi-temporal subscriber session analytic data. In the example of FIG. 5B, each set of time data, duration data, location data, and count data comprises a subscriber session analytic data. For example, one subscriber session analytic data comprises time data 512, duration data 514, location data 506, and count data 518. Another subscriber session analytic data comprises time data 520, duration data 522, location data 524, and count data 526. Together, the plurality of subscriber session analytic data sets comprises the multi-temporal subscriber session analytic data. In the example of FIG. 5B, each subscriber session analytic data set may not be a discrete data set but may instead be integrated into a data average, a data model, and/or the like that is indicative of the multi-temporal subscriber session analytic data.“);
predicting spatial-temporal changes in the distribution of the plurality of mobile devices by applying predictive analysis to the weighted spatial-temporal time series cumulative distribution function, ([0041], [0020] “In some circumstances, it may be desirable for wireless access gateway resource allocation to be based, at least in part, on subscriber session analytic data aggregated, collected, averaged, modeled, and/or accumulated over some period of time. For example, it may be desirable to base a subscriber session policy on historical wireless local area network resource utilization data. Such historical data, accumulated data, modeled data, and/or the like may relate to multi-temporal subscriber session analytic data, similar as described regarding FIGS. 5A-5D. In at least one example embodiment, multi-temporal subscriber session analytic data may be received from memory, received from a separate apparatus, and/or the like. Determination of a subscriber session policy may, for example, be based, at least in part, on the received multi-temporal subscriber session analytic data. In such circumstances, it may be desirable to update a multi-temporal subscriber session analytic data on a continual or rolling basis in order to grow and/or develop a larger subscriber session analytic data set. For example, based, at least in part, on a current subscriber session analytic data and the multi-temporal subscriber session analytic data, a changed multi-temporal subscriber session analytic data may be determined and subsequently stored in at least one memory. The change to the multi-temporal subscriber session analytic data may relate to an addition of subscriber session analytic data points to a data set that comprises the multi-temporal subscriber session analytic data, a re-averaging of data that comprises the multi-temporal subscriber session analytic data, an update to a data model associated with the multi-temporal subscriber session analytic data […]. In at least one example embodiment, a subscriber session policy is caused to be modified based, at least in part, on a multi-temporal subscriber session analytic data and the subsequently stored in at least one memory. For example, in order to account for changed multi-temporal subscriber session analytic data, the subscriber session policy may be modified to account for the new multi-temporal subscriber session analytic data and the modified subscriber session policy stored in memory for current and/or future enforcement”);
generating configuration information at the network management element for the access network element, wherein the configuration information is indicative of a time- dependent and group-based allocation of network resources and network slice characteristics based on the weighted time series cumulative distribution function and the predicted spatial-temporal changes, ((Figures 2, 5B, 9), [0014] […] determining at least one current subscriber session analytic data, the current subscriber session analytic data comprising subscriber session analytic data (equivalent to “configuration information”) that is indicative of at least one current subscriber session condition, and performing resource allocation based, at least in part, on the subscriber session policy and the current subscriber session analytic data. [0024]) [0019] […] a subscriber session condition relates to a user equipment dwell time, a user equipment location, a time, a subscriber session count, etc. Hence, the term "subscriber session condition" is a broad term that includes any condition, characteristic or parameter associated with session data, subscriber data, network data, location information, timing, etc. [0020] wireless access gateway resource allocation to be based, at least in part, on subscriber session analytic data aggregated, collected, […] over some period of time. […] accumulated data, modeled data, and/or the like may relate to multi-temporal subscriber session analytic data, similar as described regarding FIGS. 5A-5D. […] multi-temporal subscriber session analytic data may be received from memory, received from a separate apparatus, and/or the like. Determination of a subscriber session policy may, for example, be based, at least in part, on the received multi-temporal subscriber session analytic data. [0018] The current subscriber session analytic data may, for example, relate to subscriber session analytic data that is indicative of at least one current subscriber session condition. The subscriber session analytic data may, for example, relate to data that is current, real-time, predicted, delayed, at a time proximate to current conditions such that current conditions may be approximated, estimated, and/or inferred, and/or the like”);
and providing the configuration information to the access network element to dynamically adjust network resource allocation behavior over time in accordance with the predicted spatial- temporal distribution of the plurality of mobile devices, ([0043] “At block 902, the apparatus receives a multi-temporal subscriber session analytic data, similar as may be described regarding block 802 of FIG. 8. At block 904, the apparatus receives a subscriber session policy from at least one of a memory or a separate apparatus, similar as may be described regarding FIG. 2 and FIGS. 5A-5D […]. [0020], [0017] […] The `subscriber session policy` may include any data, objects, information, rules, parameters, guidelines, frameworks, templates, etc. that may affect a session, a network characteristic, subscriber behavior, resource allocation, session treatment, etc.”).
Regarding claim 37, as applied to claim 35 above, Irigi discloses further comprising the steps of: predicting geospatial locations for the plurality of mobile devices by applying predictive analysis on the time series cumulative distribution function or on the weighted time series cumulative distribution function, ([0041], [0020] “In some circumstances, it may be desirable for wireless access gateway resource allocation to be based, at least in part, on subscriber session analytic data aggregated, collected, averaged, modeled, and/or accumulated over some period of time. For example, it may be desirable to base a subscriber session policy on historical wireless local area network resource utilization data. Such historical data, accumulated data, modeled data, and/or the like may relate to multi-temporal subscriber session analytic data, similar as described regarding FIGS. 5A-5D. In at least one example embodiment, multi-temporal subscriber session analytic data may be received from memory, received from a separate apparatus, and/or the like. Determination of a subscriber session policy may, for example, be based, at least in part, on the received multi-temporal subscriber session analytic data. In such circumstances, it may be desirable to update a multi-temporal subscriber session analytic data on a continual or rolling basis in order to grow and/or develop a larger subscriber session analytic data set. For example, based, at least in part, on a current subscriber session analytic data and the multi-temporal subscriber session analytic data, a changed multi-temporal subscriber session analytic data may be determined and subsequently stored in at least one memory. The change to the multi-temporal subscriber session analytic data may relate to an addition of subscriber session analytic data points to a data set that comprises the multi-temporal subscriber session analytic data, a re-averaging of data that comprises the multi-temporal subscriber session analytic data, an update to a data model associated with the multi-temporal subscriber session analytic data […]. In at least one example embodiment, a subscriber session policy is caused to be modified based, at least in part, on a multi-temporal subscriber session analytic data and the subsequently stored in at least one memory. For example, in order to account for changed multi-temporal subscriber session analytic data, the subscriber session policy may be modified to account for the new multi-temporal subscriber session analytic data and the modified subscriber session policy stored in memory for current and/or future enforcement”).
Allowable Subject Matter
Claims 38, 39, and 41 are 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.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to GILBERT GRANT whose telephone number is (703)756-1136. The examiner can normally be reached 9:00 am - 7:00 pm, Monday - Thursday.
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, Rafael Perez-Gutierrez can be reached on 571-272-7915. 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.
/GILBERT M. GRANT/Examiner, Art Unit 2642
/Rafael Pérez-Gutiérrez/Supervisory Patent Examiner, Art Unit 2642