Method and system for dynamically managing cable data bandwidth based on channel congestion state and subscriber usage profile

• US 20050052992A1
• Filed: 08/02/2004
• Published: 03/10/2005
• Est. Priority Date: 08/01/2003
• Status: Abandoned Application

• Current Assignee: Arris International, Inc. (CommScope Holding Company, Inc.)
• Original Assignee: Arris International, Inc. (CommScope Holding Company, Inc.)
• Inventors: Sullivan, Michael P., Daun, Carl, Krapp, Steven J., Cloonan, Thomas J., Howe, Jeffrey J., Robbins, Max
• Application Number:
  US10/910,168
• Publication Number:
  US 20050052992A1
• Time in Patent Office: Days
• US Class Current: 370/229
• CPC Class Codes: H04L 41/5003 Managing SLA; Interaction between SLA and QoS
• CPC Class Codes: H04L 41/5025 by proactively reacting to service quality change, e.g. by reconfiguration after service quality degradation or upgrade
• CPC Class Codes: H04L 41/5067 Customer-centric QoS measurements
• CPC Class Codes: H04L 43/067 using time frame reporting
• CPC Class Codes: H04L 43/0829 Packet loss
• CPC Class Codes: H04L 43/0894 Packet rate
• CPC Class Codes: H04L 43/16 Threshold monitoring
• CPC Class Codes: H04L 47/10 Flow control; Congestion control
• CPC Class Codes: H04L 47/11 Identifying congestion
• CPC Class Codes: H04L 47/12 Avoiding congestion; Recovering from congestion
• CPC Class Codes: H04L 47/27 Evaluation or update of window size, e.g. using information derived from acknowledged [ACK] packets
• CPC Class Codes: H04L 47/29 using a combination of thresholds
• CPC Class Codes: H04L 47/326 with random discard, e.g. random early discard [RED]
• CPC Class Codes: H04L 47/70 Admission control; Resource allocation
• CPC Class Codes: H04L 47/808 User-type aware
• CPC Class Codes: H04L 47/826 Involving periods of time
• CPC Class Codes: H04L 47/828 Allocation of resources per group of connections, e.g. per group of users
• CPC Class Codes: H04L 67/104 Peer-to-peer [P2P] networks
• CPC Class Codes: H04L 67/306 User profiles
• CPC Class Codes: H04L 67/54 Presence management, e.g. monitoring or registration for receipt of user log-on information, or the connection status of the users
• CPC Class Codes: H04L 69/329 : in the application layer [OSI layer 7]
• CPC Class Codes: H04N 21/2385 : Channel allocation H04N21/266 takes precedence; Bandwidth allocation H04N21/24 takes precedence ; allocation of channels according to the instantaneous demands of the users in time-division multiplex systems H04J3/1682; admission control, resource allocation in open networks H04L12/5692; arrangements for maintenance or administration in data switching networks involving bandwidth and capacity management H04L41/0896; negotiating bandwidth in wireless networks H04W28/16
• CPC Class Codes: H04N 21/2402 : Monitoring of the downstream path of the transmission network, e.g. bandwidth available traffic monitoring in data switching networks H04L43/00; monitoring data switching networks utilization H04L43/0876
• CPC Class Codes: H04N 21/2408 : Monitoring of the upstream path of the transmission network, e.g. client requests monitoring data switching networks utilization H04L43/0876; scheduling or organising the servicing of application requests H04L67/60
• CPC Class Codes: H04N 21/25866 : Management of end-user data customer care in data networks H04L41/5077
• CPC Class Codes: H04N 21/64738 : Monitoring network characteristics, e.g. bandwidth, congestion level data switched network analysis H04L41/14; monitoring functioning in data switched networks H04L43/0817; flow control in packet networks H04L47/10
• CPC Class Codes: H04N 7/165 : Centralised control of user terminal subsequent to an upstream request signal H04N7/17345; Registering at central by two-way working H04N7/17309

Abstract

A long-term usage profile and a congestion state metric are used to determine QoS treatment to apply to packets corresponding to a given network user. A user'"'"'s historical long-term use, measured over one or more periods of time, is used to generate a profile that is compared to one or more predetermined usage threshold level(s). If the usage profile, either singular or composite corresponding to whether one or more than one measurement is used respectively, exceeds the threshold(s), QoS treatment is applied to service flow bytes according to the comparison results during times of network channel congestion. Congestion metrics are determined based on a count of the number of bytes dropped during a congestion measurement window. Either the count itself or the count rate of change combined with the count are compared to a congestion threshold. If the measured/derived values exceed a congestion threshold, the channel is deemed congested.

Claims

1. A method for balancing bandwidth allocation of data subscribers over a broadband network channel comprising:

classifying the subscribers into different groupings based on a long-term historical usage profile associated with each subscriber; and

assigning predetermined treatment policies to each of the subscribers based on their corresponding long term usage history profile grouping.

2. The method of claim 1 wherein a predetermined time period window is selected over which the long-term historical usage pattern is determined.

3. The method of claim 2 wherein the window is one hour.

4. The method of claim 2 wherein the window is one day.

5. The method of claim 2 wherein the window is one week.

6. The method of claim 2 wherein the window is one month.

7. The method of claim 1 wherein a subscriber is penalized based on the long term usage history profile corresponding to the subscriber.

8. The method of claim 7 wherein the subscriber is penalized if the long-term usage profile exceeds a predetermined usage level threshold corresponding to the predetermined time period.

9. A method for balancing bandwidth allocation of data subscribers over a broadband network channel comprising:

classifying the subscribers into different groupings based on a long term historical usage profile associated with each subscriber; and

identifying a channel congestion metric; and

assigning predetermined treatment policies to each of the subscribers based on their corresponding long term usage profile grouping and the channel congestion metric.

10. The method of claim 9 wherein a predetermined time period window is selected over which the historical usage pattern is determined.

11. The method of claim 10 wherein the window is one hour.

12. The method of claim 10 wherein the window is one day.

13. The method of claim 10 wherein the window is one week.

14. The method of claim 10 wherein the window is one month.

15. The method of claim 9 wherein a subscriber is penalized based on the long term usage history profile corresponding to the subscriber.

16. The method of claim 15 wherein the subscriber is penalized if the long-term usage profile exceeds a predetermined usage level threshold corresponding to the predetermined time period.

17. The method of claim 9 wherein the channel congestion metric includes a count of the number bytes corresponding to a given subscriber that are dropped during a predetermined congestion measurement window period.

18. The method of claim 17 wherein dropped bytes during a first predetermined congestion measurement window period and a second predetermined congestion measurement window period are determined and the number of dropped bytes counted for the first a second predetermined congestion measurement window periods are used to determine a dropped byte rate of change derivative.

19. The method of claim 18 wherein the dropped byte rate of change derivative and a count of the number of bytes dropped during a given congestion measurement window period are used to determine a summed and weighted congestion metric.

20. The method of claim 17 wherein a user is penalized if the channel congestion metric exceeds a predetermined congestion threshold.

21. The method of claim 18 wherein a user is penalized if the dropped byte rate of change derivative exceeds a predetermined congestion threshold.

22. The method of claim 19 wherein a user is penalized if the summed and weighted congestion metric exceeds a predetermined congestion threshold.

23. A method for balancing bandwidth allocation of data subscribers over a broadband network channel comprising:

classifying the subscribers into different groupings based on a composite long-term historical usage profile associated with each subscriber; and

assigning predetermined treatment policies to each of the subscribers based on their corresponding long term usage history profile grouping.

24. The method of claim 23 wherein a plurality of predetermined time period windows are selected over which components of the long-term historical usage pattern is determined.

25. The method of claim 24 wherein a first component window is one hour.

26. The method of claim 24 wherein a second component window is one day.

27. The method of claim 24 wherein a third component window is one week.

28. The method of claim 24 wherein a forth component window is one month.

29. The method of claim 23 wherein a subscriber is penalized based on the composite long term usage history profile corresponding to the subscriber.

30. The method of claim 29 wherein the subscriber is penalized if the composite long-term usage profile exceeds a predetermined composite usage level threshold corresponding to the predetermined time period.