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 .
2. Claims 1–20 are pending for examination in the reply filed on 01/26/2026.
Examiner’s Remarks
3. Examiner refers to and explicitly cites particular pages, sections, figures, paragraphs or columns and lines in the references as applied to Applicant’s claims to the extent practicable to streamline prosecution.
Although the cited portions of the references are representative of the best teachings in the art and are applied to meet the specific limitations of the claims, other uncited but related teachings of the references may be equally applicable as well. It is respectfully requested that, in preparing responses to the rejections, the Applicant fully considers not only the cited portions of the references, but also the references in their entirety, as potentially teaching, suggesting or rendering obvious all or one or more aspects of the claimed invention.
Abbreviations
4. Where appropriate, the following abbreviations will be used when referencing Applicant’s submissions and specific teachings of the reference(s):
i. figure / figures: Fig. / Figs.
ii. column / columns: Col. / Cols.
iii. page / pages: p. / pp.
References Cited
5. (A) McKee et al., US 2005/0286434 A1 (“McKee”).
(B) Zhang, US 2014/0325649 A1.
(C) Altman et al., US 2017/0168914 A1 (“Altman”).
(D) Guim Bernat et al., US 2018/0091383 A1 (“Guim Bernat”).
McKee, Zhang, Altman, and Guim Bernat were cited in the previous Office action.
Notice re prior art available under both pre-AIA and AIA
6. 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 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.
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.
A.
7. Claims 1, 8, 10–11, 14, 17, and 19–20 are rejected under 35 U.S.C. 103 as being unpatentable over (A) McKee in view of (B) Zhang.
See “References Cited” section, above, for full citations of references.
8. Regarding claim 1, (A) McKee teaches/suggests the invention substantially as claimed, including:
“A method, comprising:
determining, by a device, a set of flows to be monitored within a computer network”
(¶ 9: comprises assigning a subset of network traffic sampling points to a unique pair of nodes. The sampling point subset may be assigned to the unique node pair based on, for example, historical traffic within the network, routing tables learned from the network devices, or an examination of the network topology. The number of sampling points in the subset may be fixed or variable. The sampling point subset may contain a single sampling point or multiple sampling points, although the subset preferably contains as many sampling points as possible. The sampling point subset can be assigned based on any suitable criteria, but it preferably includes the sampling points most likely to monitor all traffic flows associated with the node pair;
¶ 11: flows between each unique node pair in the network are monitored;
¶ 16: sampling points can be assigned based on any suitable criteria, but preferably include the sampling points most likely to monitor all data traffic associated with the nodes or node pairs);
“determining, by the device, a set of nodes within the computer network through which the set of flows traverse”
(¶ 9: comprises assigning a subset of network traffic sampling points to a unique pair of nodes. The sampling point subset may be assigned to the unique node pair based on, for example, historical traffic within the network, routing tables learned from the network devices, or an examination of the network topology. The number of sampling points in the subset may be fixed or variable. The sampling point subset may contain a single sampling point or multiple sampling points, although the subset preferably contains as many sampling points as possible. The sampling point subset can be assigned based on any suitable criteria, but it preferably includes the sampling points most likely to monitor all traffic flows associated with the node pair;
¶ 34: each of the sampling agents 102 is associated with a switch or router in a known manner, so that they can monitor data packets as they flow through the switch or router (not shown;
¶ 44: the sampling agents 102 selected for the unique node pair AB (node A is a source, and node B is a destination) should be the ones along the path from node A to node B (shown as arrows), namely sampling agents S1, S2, S3, S4, S10, S12, S15, S20, and S21 … the sampling agents 102 selected for unique node pairs AC, CA, BC, and CB should be the sampling agents that reside along the respective paths between the respective node pairs);
“generating, by the device, an assignment for each node of the set of nodes to monitor a subset of one or more flows of the set of flows … wherein the assignment for the each node of the set of nodes ensures that each flow of the set of flows is monitored by at least one or more nodes of the set of nodes”
(¶ 9: comprises assigning a subset of network traffic sampling points to a unique pair of nodes ….
The sampling point subset can be assigned based on any suitable criteria, but it preferably includes the sampling points most likely to monitor all traffic flows associated with the node pair;
¶ 16: monitor all data traffic associated with the nodes or node pairs);
“instructing, by the device, the set of nodes to monitor the set of flows according to the assignment for the each node of the set of nodes”
(¶ 17: obtaining sampled traffic flow counts for a flow associated with source and destination nodes of a unique pair of nodes from the diagnostic traffic data collected from the sampling points assigned to the source and destination nodes).
McKee teaches that the sampling points can be assigned based on any suitable criteria (¶ 16), but does not teach:
“generating, by the device, an assignment … based on FLOW CHARACTERISTICS associated with the subset of the one or more flows and the monitoring capabilities of the each node.”
(B) Zhang however teaches or suggests:
“generating, by the device, an assignment … based on FLOW CHARACTERISTICS associated with the subset of the one or more flows
(¶ 36: network manager 152 monitors traffic flows by traffic aggregates. A traffic aggregate is a set of TRAFFIC FLOWS SHARING SOME COMMON CHARACTERISTICS, for example, same source address or destination address blocks, port number blocks, traffic type (e.g., same quality of service (QoS) requirements), or other traffic characteristics;
¶ 66: traffic flows are grouped into various traffic aggregates. Each traffic aggregate contains a number of traffic flows that share some common characteristics. In this example, all traffic flows within an aggregate share a common route within the network;
¶ 71: Traffic flows can be divided based on a variety of criteria. For example, the division can be based on source or destination address blocks of traffic flows, port numbers reflecting different applications, or other traffic characteristics. An operator of a network may change the traffic division based on network condition);
and the monitoring capabilities of the each node.”
(¶ 70: and a network device often needs to monitor multiple traffic aggregates. A network device has a capacity limit as of how many traffic aggregate it can monitor. In one embodiment, a network device is not removed from the candidate network device set until the network device has been assigned to a number of traffic aggregates, where the number reaches its capacity limit;
¶ 67: each network device is given a monitor count based on how many traffic aggregates the network device forwards through. The monitor count is used to denote the most traffic aggregate a network device covers;
¶ 75: distributing the responsibility of monitoring traffic anomalies to multiple network devices, and the distribution preferably considers how many entries of the monitor set that the network device has already signed up to monitor. In some embodiment, the distribution may also consider the monitoring capacity limitation of the network device, which may be different for different network devices;
¶ 40: redistributes the not-selected traffic flows to another network device for monitoring, by
considering the monitoring capability left on each network device).
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of (B) Zhang with those of (A) McKee to select sampling points along a flow based on flow characteristics and capacity limits on each monitoring nodes. The motivation or advantage to do so is to allow for the balanced load sharing of traffic monitoring functions based on different flow characteristics and node (device) features/capabilities.
9. Regarding claim 8, McKee and Zhang teach/suggest:
“wherein the set of nodes further monitor the set of flows according to one or more configured sampling mechanisms”
(McKee, ¶ 11: obtaining sampled traffic flow counts from the diagnostic traffic data collected from the sampling point subset assigned to the respective node pair;
¶ 34: each of the sampling agents 102 is associated with a switch or router in a known manner, so that they can monitor data packets as they flow through the switch or router (not shown);
Zhang, ¶ 57: controller 252 polls traffic statistics of a particular traffic aggregate from a selected SDN switch (SDN switch C) and adaptively samples traffic flows within the traffic aggregate to detect anomaly).
10. Regarding claim 10, Zhang teaches/suggests:
“wherein each particular node of the set of nodes is assigned an individualized number of flows to monitor based on an individual node-by- node-based determination of the monitoring capabilities of that particular node”
(¶ 67: each network device is given a monitor count based on how many traffic aggregates the network device forwards through. The monitor count is used to denote the most traffic aggregate a network device covers;
¶ 75: distributing the responsibility of monitoring traffic anomalies to multiple network devices, and the distribution preferably considers how many entries of the monitor set that the network device has already signed up to monitor. In some embodiment, the distribution may also consider the monitoring capacity limitation of the network device, which may be different for different network devices;
¶ 40: redistributes the not-selected traffic flows to another network device for monitoring, by
considering the monitoring capability left on each network device).
11. Regarding claim 11, McKee teaches/suggests:
“wherein the set of flows use a same ingress and a same egress of the computer network”
(¶ 37: The traffic between a node pair may be made up of a single flow, or it may be made up of a plurality of separate flows;
see Fig. 7, illustrating that traffic flowing between nodes A and B have the same ingress and egress points on the network);
12. Regarding claims 14, 17, and 19, they are the corresponding computer program product claims reciting similar limitations of commensurate scope as the method of claims 1, 8, and 10, respectively. Therefore, they are rejected on the same basis as claims 1, 8, and 10 above.
13. Regarding claim 20, it is the corresponding system claim reciting similar limitations of commensurate scope as the method of claim 1. Therefore, it is rejected on the same basis as claim 1 above, including the following rationale:
McKee and Zhang teach/suggest “one or more network interfaces to communicate with a network; a processor coupled to the one or more network interfaces and configured to execute one or more processes; and a memory configured to store a process that is executable by the processor, the process, when executed, configured to”
(McKee, Fig. 7 and ¶ 36: functions of the sample collector 104 are implemented in a computer program having computer executable instructions, which may be stored on any suitable medium, such as a hard drive or CD-ROM, and may be executed to perform the required instructions;
Zhang, Figs. 8–9 and ¶ 106: one or more processors coupled to one or more other components, such as one or more storage devices).
B.
14. Claims 2–5, 9, 12–13, 15, and 18 are rejected under 35 U.S.C. 103 as being unpatentable over (A) McKee in view of (B) Zhang, as applied to claims 1 and 14 above, and further in view of (C) Altman.
15. Regarding claim 2, McKee teaches “increased number of nodes along a particular flow of the set of flows to monitor the particular flow; and instructing … the increased number of nodes along the particular flow to monitor the particular flow”
(¶ 5: The number of monitoring points can be increased, so that more of the data traffic between the nodes can be monitored;
¶ 47: allowing sampling agent subsets to be dynamically changed over time in an efficient manner as traffic conditions vary).
McKee and Zhang do not teach “detecting, based on monitoring performed by the set of nodes, a trigger to instruct an increased number of nodes along a particular flow of the set of flows to monitor the particular flow; and instructing, based on the trigger, the increased number of nodes along the particular flow to monitor the particular flow”
(C) Altman, in the context of McKee and Zhang, however teaches or suggests implementing:
“detecting, based on monitoring performed by the set of nodes, a trigger to instruct an increased number of nodes along a particular flow of the set of flows to monitor the particular flow; and instructing, based on the trigger, the increased number of nodes along the particular flow to monitor the particular flow”
(¶¶ 6–7: the performance metrics fail to meet the performance goal, indicating a performance issue; and increasing the monitoring levels for the system node exhibiting the performance issue …
the method for adaptive performance monitoring of a system includes changing monitoring options during run-time, responsive to determining that the performance metrics fail to meet the performance goal by a specified threshold amount. Changing the monitoring options can include: adjusting sampling size, adjusting the workload, ADDING LOGGING POINTS, and adjusting the collection intervals;
Fig. 5 and ¶¶ 56–57: if CPU utilization is measured as 75%, the monitoring processor 150 returns a rule failure … if CPU utilization is not less 70%, the monitoring processor 150 then applies the filter 414 to determine if CPU utilization is 90%, considerably above the rule threshold. If that is the case, in step 254 the monitoring processor 150 executes a further change in monitoring options, such as 1) very aggressively adjusting the monitoring levels with logging turned up to maximum levels; 2) alerting the administrator; and/or 3) shortening wait intervals to increase the frequency of data collection, to name a few;
Claims 6 and 7: wherein changing the monitoring options comprises at least one of: adjusting sampling size, adjusting workload, adding logging points, and adjusting the pre-determined intervals).
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of (C) Altman with those of McKee and Zhang to add additional sampling points along a flow based on a monitored performance metric exceeding (failing) a threshold. The motivation or advantage to do so is to provide for the adaptive monitoring of traffic flows based on monitored network performance or metric
(see McKee, ¶ 47: allowing sampling agent subsets to be dynamically changed over time in an efficient manner as traffic conditions vary).
16. Regarding claim 3, McKee teaches/suggests:
“wherein the increased number of nodes is all nodes along the particular flow”
(¶ 5: The number of monitoring points can be increased, so that more of the data traffic between the nodes can be monitored;
¶ 47: allowing sampling agent subsets to be dynamically changed over time in an efficient manner as traffic conditions vary).
17. Regarding claim 4, Altman teaches/suggests:
“wherein the trigger is selected from a group consisting of: one or more particular errors; a particular number of errors; crossing a static threshold of a particular attribute; and crossing a dynamically established threshold of a particular attribute”
(Fig. 5 and ¶¶ 56–57: if CPU utilization is measured as 75%, the monitoring processor 150 returns a rule failure … if CPU utilization is not less 70%, the monitoring processor 150 then applies the filter 414 to determine if CPU utilization is 90%, considerably above the rule threshold. If that is the case, in step 254 the monitoring processor 150 executes a further change in monitoring options, such as 1) very aggressively adjusting the monitoring levels with logging turned up to maximum levels; 2) alerting the administrator; and/or 3) shortening wait intervals to increase the frequency of data collection, to name a few;
Claims 6 and 7: wherein changing the monitoring options comprises at least one of: adjusting sampling size, adjusting workload, adding logging points, and adjusting the pre-determined intervals).
18. Regarding claim 5, Altman teaches/suggests:
“wherein instructing the increased number of nodes along the particular flow to monitor the particular flow comprises one of either: a) indicating a pre-defined time period for the increased number of nodes along the particular flow to monitor the particular flow; or b) transmitting a subsequent instruction to have the increased number of nodes along the particular flow terminate monitoring of the particular flow”
(¶ 37: the rules 114 can specify the length of time to maintain the increased monitoring level, after which the monitoring level reverts to its initially low default level;
Claim 15: wherein the rules mandate automatically reverting to the default monitoring levels after a specified period of time).
19. Regarding claim 9, McKee, Zhang, and Altman teach/suggest:
“classifying, by the device and based at least in part on the flow characteristics, the set of flows to one or more groups, each group of the one or more groups including one or more flows;
(Zhang, ¶ 36: network manager 152 monitors traffic flows by traffic aggregates. A traffic aggregate is a set of TRAFFIC FLOWS SHARING SOME COMMON CHARACTERISTICS, for example, same source address or destination address blocks, port number blocks, traffic type (e.g., same quality of service (QoS) requirements), or other traffic characteristics;
¶ 66: traffic flows are grouped into various traffic aggregates. Each traffic aggregate contains a number of traffic flows that share some common characteristics. In this example, all traffic flows within an aggregate share a common route within the network;
¶ 71: Traffic flows can be divided based on a variety of criteria. For example, the division can be based on source or destination address blocks of traffic flows, port numbers reflecting different applications, or other traffic characteristics. An operator of a network may change the traffic division based on network condition);
assigning, by the device, one or more nodes of the set of nodes to monitor a particular group of the one or more groups; and
(McKee, ¶ 9: comprises assigning a subset of network traffic sampling points to a unique pair of nodes ….
The sampling point subset can be assigned based on any suitable criteria, but it preferably includes the sampling points most likely to monitor all traffic flows associated with the node pair;
¶ 16: monitor all data traffic associated with the nodes or node pairs;
Zhang, ¶ 69: method assigns the network device with the lowest monitor count to one of the traffic aggregate it covers );
scheduling, by the device, the one or more nodes to monitor corresponding flows in the particular group based at least in part on the monitoring capabilities”
(Zhang, ¶ 85: SDN controller increases the sampling rate of the entry. The increased sampling rate (accompanied by reduced the sampling interval) provides a temporal zoom-in of traffic flows;
Altman, ¶ 43: interval timer 180 is operably coupled with the monitoring processor 150 and can be embodied as a system clock or global clock. The timer 180 is implemented by the monitoring processor 150 to schedule collections of monitoring data 105 at pre-set intervals).
20. Regarding claim 12, McKee, Zhang, and Altman teach/suggest:
“updating one or both of a) a number of the set of flows to be monitored and b) the monitoring capabilities for the set of nodes”
(McKee, ¶ 5: The number of monitoring points can be increased, so that more of the data traffic between the nodes can be monitored;
¶ 47: allowing sampling agent subsets to be dynamically changed over time in an efficient manner as traffic conditions vary;
Zhang, ¶ 70: and a network device often needs to monitor multiple traffic aggregates. A network device has a capacity limit as of how many traffic aggregate it can monitor. In one embodiment, a network device is not removed from the candidate network device set until the network device has been assigned to a number of traffic aggregates, where the number reaches its capacity limit;
Altman, ¶ 37: the rules 114 can specify the length of time to maintain the increased monitoring level, after which the monitoring level reverts to its initially low default level;
Claim 15: wherein the rules mandate automatically reverting to the default monitoring levels after a specified period of time).
21. Regarding claim 13, Zhang and Altman teach/suggests:
“wherein determining monitoring capabilities is based on hardware-based telemetry monitoring on the set of nodes”
(Zhang, ¶ 75: the distribution may also consider the monitoring capacity limitation of the network device, which may be different for different network devices;
Altman, ¶ 37: rules set 114 stored in the rules database 112 specifies the upper/lower bounds for performance goals for each node 132, mapped to the requisite monitoring action to take when the performance goal is not met;
¶ 80: automatically control and optimize resource use by leveraging a metering capability at some level of abstraction appropriate to the type of service, e.g., storage, processing, bandwidth).
22. Regarding claim 15, it is the corresponding computer program product claim reciting similar limitations of commensurate scope as the method of claim 2. Therefore, it is rejected on the same basis as claim 2 above.
23. Regarding claim 18, it is the corresponding computer program product claim reciting similar limitations of commensurate scope as the method of claim 9. Therefore, it is rejected on the same basis as claim 9 above.
C.
24. Claims 6–7 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over (A) McKee in view of (B) Zhang, as applied to claims 1 and 14 above, and further in view of (D) Guim Bernat.
25. Regarding claim 6, McKee teaches “subsequent instructions to monitor a given flow”
(¶ 5: The number of monitoring points can be increased, so that more of the data traffic between the nodes can be monitored;
¶ 47: allowing sampling agent subsets to be dynamically changed over time in an efficient manner as traffic conditions vary).
McKee and Zhang do not teach “reserving a defined amount of monitoring resources on the set of nodes sufficient for subsequent instructions to monitor a given flow in response to a trigger to end-to-end monitor the given flow.”
(D) Guim Bernat, in the context of McKee and Zhang’s teachings, however teaches or suggests:
“reserving a defined amount of monitoring resources on the set of nodes sufficient for subsequent instructions to monitor a given flow in response to a trigger to end-to-end monitor the given flow”
(¶ 22: the switch 105 is responsible for executing Quality of Service (QoS) features such as congestion management functions;
¶ 35: application 103-1 may have resource QoS requirements for the resources of node 101-1, switch 105, and node 101-2 creating an end-to-end path. These resources can include the processing circuitries 102-1, 120, and 102-2, the memories 104-1, 122, and 104-2, the interfaces 106-1, 106-2, and 126, and storage 108-1, 124, and 108-2. These requirements may be based on the needs of the application 103-1 and determined by logic as part of a software stack and processing circuitry;
¶ 37: establishing resource monitoring and QoS management for one or more applications utilizing one or more end-to-end paths having resources for processing capabilities. The resource monitoring includes registering one or more resources utilized by a particular application to monitor, monitoring the registered resources, and performing corrective actions when required;
¶ 55: resource utilization may be reserved for each resource of the end-to-end path to meet the needs of the sending node and application, e.g. a guaranteed resource utilization QoS scheme;
¶ 61: the QoS scheme may be change to reserve usage or bandwidth for the application on the resource. In some instances, the QoS scheme may affect each resource in the end-to-end path or only those resources that are not meeting the load requirements for the application in the end-to-end path).
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of (D) Guim Bernat with those of McKee and Zhang to reserve resources of each of the monitoring points along a path between two nodes exchanging traffic to accommodate potential increases in end-to-end monitoring activity. The motivation or advantage to do so is to manage and ensure a guaranteed quality of service requirement for traffics between the two nodes are being met.
26. Regarding claim 7, McKee and Guim Bernat teach or suggest:
“determining the defined amount of monitoring resources based on one or both of a total number of the set of flows and a total number of the set of nodes”
(McKee, ¶ 9: comprises assigning a subset of network traffic sampling points to a unique pair of nodes ….
The sampling point subset can be assigned based on any suitable criteria, but it preferably includes the sampling points most likely to monitor all traffic flows associated with the node pair;
¶ 16: monitor all data traffic associated with the nodes or node pairs);
Guim Bernat, ¶ 55: resource utilization may be reserved for each resource of the end-to-end path to meet the needs of the sending node and application, e.g. a guaranteed resource utilization QoS scheme;
¶ 61: the QoS scheme may be change to reserve usage or bandwidth for the application on the resource. In some instances, the QoS scheme may affect each resource in the end-to-end path or only those resources that are not meeting the load requirements for the application in the end-to-end path).
27. Regarding claim 16, it is the corresponding computer program product claim reciting similar limitations of commensurate scope as the method of claim 6. Therefore, it is rejected on the same basis as claim 6 above.
Response to Arguments
28. Applicant’s arguments with respect to the claims have been considered but are moot because the arguments do not apply to any of the newly applied teachings or references being used in the current rejection.
In the Remarks, the Applicant also argues that McKee and Zhang do not teach or suggest the feature of “generating, by the device, an assignment for each node of the set of nodes to monitor a subset of one or more flows of the set of flows based on flow characteristics associated with the subset of the one or more flows and the monitoring capabilities of the each node.”
The Examiner disagrees.
As applied in the rejection, Zhang specifically teaches these features in at least paragraphs 36, 66, and 75, wherein Zhang teaches that traffic flows are monitored by traffic aggregates, each of which (an aggregate) is a set of traffic flows sharing some common characteristics, and that the distribution (assignment of monitoring) may also consider the monitoring capacity limitation of the network device.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
(a) COCIGLIO, US 2020/0067806 A1, teaching performing a performance measurement on a multipoint packet flow transmitted in a packet-switched subnetwork. A monitoring network of measurement points is implemented in the subnetwork.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL 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 extension fee 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.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Aimee J. Li can be reached on (571)272-4169. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/BENJAMIN C WU/Primary Examiner, Art Unit 2195
April 30, 2026
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