IP Library › Granted Patent US 12,513,063
Granted Patent B2
US 12,513,063 · App. 18/669,832 · Granted Dec 30, 2025

Techniques for dynamic network management

Inventors: Bryan Pinos (Williamsburg, VA); Christopher Moczydlowski (Ruther Glen, VA); John Anand Lourdusamy (Glen Allen, VA); Eric Barnum (Midlothian, VA)
Assignee: Capital One Services, LLC
H04L43/04H04L41/0893H04L41/0896H04L41/22H04L43/062H04L43/0876H04L47/20H04L47/2483H04L41/0894H04L67/10
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 12,513,063
App. No.
18/669,832
Granted
Dec 30, 2025
Kind
B2
Abstract

Various embodiments are generally directed to techniques for dynamic network management, such as by monitoring and analyzing network parameters, such as network traffic and network configurations, to enable visualization of network state and improved situational awareness. Some embodiments are particularly directed to providing a graphical user interface (GUI) that utilizes various network parameters to map, characterize, and/or assign attributes to network traffic and resources. In many embodiments, network traffic may be monitored and/or routed based on their attributes.

Claims (33)

1 . A method comprising:

monitoring a flow of traffic through one or more network resources in a set of network resources, the flow of traffic including data packets for one or more applications;

characterizing the flow of traffic based at least on a packet type of the data packets;

applying an attribute to at least one data packet for a particular application of the flow of traffic based on the packet type of the at least one data packet; and

routing the at least one data packet through the one or more network resources based on the applied attribute.

2 . The method of claim 1 , wherein monitoring the flow of traffic includes monitoring the flow of traffic based on a latency or bandwidth of the flow of traffic.

3 . The method of claim 1 , wherein monitoring the flow of traffic includes monitoring the flow of traffic using logs or traffic samples of the flow of traffic.

4 . The method of claim 1 , wherein characterizing the flow of traffic further includes characterizing the flow of traffic based on a number of packets for the packet type, a number of unique users engaging in the flow of traffic, or anomalies in bandwidth by traffic type.

5 . The method of claim 1 , wherein applying the attribute includes applying attributes related to traffic type, directionality, traffic endpoints, health checks, environment, or time.

6 . The method of claim 1 , wherein routing the at least one data packet through the one or more network includes routing the at least one data packet through a dark instance of the network resources.

7 . The method of claim 6 , wherein the dark instance is a failover link in the network resources, and routing the at least one data packet through the dark instance frees up bandwidth on a primary active link in the network resources.

8 . The method of claim 1 , wherein routing the at least one data packet further includes routing the at least one data packet based on one or more traffic policies or one or more resource policies, wherein the one or more traffic policies and the one or more resource policies are generated based on monitoring the flow of traffic.

9 . The method of claim 1 , wherein applying the attribute includes applying an attribute that indicates that the traffic flow is related to production data or non-production data, and

wherein routing the at least one data packet includes routing the production data through a different part of the network resources compared to the non-production data.

10 . The method of claim 1 , wherein applying the attribute further includes applying a time attribute to the at least one data packet; and

wherein routing the at least one data packet includes routing the traffic flow through a part of the network resources during peak usage times that is different than when the traffic flow is not at peak usage times.

11 . An apparatus comprising:

a memory having executable instructions stored thereon;

a processing circuit coupled to the memory to execute the executable instructions, which when executed by the processing circuit, causes the processing circuit to:

monitor a flow of data packets through one or more network devices in a set of network devices, the flow of data packets including data packets for one or more applications;

apply an attribute to at least one data packet for a particular application of the flow of data packets based on a packet type of the at least one data packet; and

route the at least one data packet through the one or more network devices based on the applied attribute.

12 . The apparatus of claim 11 , wherein monitoring the flow of data packets includes monitoring the flow of data packets based on a latency or bandwidth of the flow of data packets.

13 . The apparatus of claim 11 , wherein monitoring the flow of data packets includes monitoring the flow of data packets using logs or data packets samples of the flow of data packets.

14 . The apparatus of claim 11 , wherein applying the attribute is further based on a number of packets for the packet type, a number of unique users engaging in the flow of data packets, or anomalies in bandwidth by data packets type.

15 . The apparatus of claim 11 , wherein applying the attribute includes applying attributes related to data packet type, directionality, data packet endpoints, health checks, environment, or time.

16 . The apparatus of claim 11 , wherein routing the at least one data packet through the one or more network devices includes routing the at least one data packet through a redundant path of the one or more network devices.

17 . The apparatus of claim 16 , wherein routing the at least one data packet through the redundant path frees up bandwidth on a primary active path in the network devices.

18 . The apparatus of claim 11 , wherein routing the at least one data packet further includes routing the at least one data packet based on one or more traffic policies or one or more resource policies, wherein the one or more traffic policies and the one or more resource policies are generated based on monitoring the flow of data packets.

19 . The apparatus of claim 11 , wherein applying the attribute includes applying an attribute that indicates that the data packets are related to production data or non-production data, and

wherein routing the at least one data packet includes routing the production data through a different part of the network devices compared to the non-production data.

20 . The apparatus of claim 11 , wherein applying the attribute further includes applying a time attribute to the at least one data packet; and

wherein routing the at least one data packet includes routing the at least one data packet through a part of the network devices during peak usage times that is different than during non-peak usage times.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 24, 2025
From: PINOS, BRYAN; MOCZYDLOWSKI, CHRISTOPHER; LOURDUSAMY, JOHN ANAND; BARNUM, ERIC
To: CAPITAL ONE SERVICES, LLC
Reel/Frame 070302/0947 →
Continuity (5)
Continuation 18124878 · Mar 22, 2023
Continuation 17307068 · May 4, 2021
Continuation 16744917 · Jan 16, 2020
Continuation 16409208 · May 10, 2019
Related Publication 20240305530A1 · Sep 12, 2024
References Cited (16)
US 7543052B1 · Cesa Klein · 2009 [cited by examiner]
US 7742406B1 · Muppala · 2010 [cited by examiner]
US 7890813B2 · Usynin et al. · 2011 [cited by applicant]
US 7925756B1 · Riddle · 2011 [cited by examiner]
US 10679133B1 · Mathur et al. · 2020 [cited by applicant]
US 20080215925A1 · Degenaro et al. · 2008 [cited by applicant]
US 20090182794A1 · Sekiguchi · 2009 [cited by applicant]
US 20100058120A1 · Coleman et al. · 2010 [cited by applicant]
US 20130191524A1 · Dupre et al. · 2013 [cited by applicant]
US 20150161025A1 · Baset et al. · 2015 [cited by applicant]
US 20150378859A1 · Jang et al. · 2015 [cited by applicant]
US 20160105353A1 · Cociglio · 2016 [cited by examiner]
US 20180114126A1 · Das et al. · 2018 [cited by applicant]
US 20180367399A1 · Pani et al. · 2018 [cited by applicant]
US 20190095298A1 · Fricano et al. · 2019 [cited by applicant]
US 20190342146A1 · Magcale · 2019 [cited by applicant]