Systems and method for optimizing access provisioning and capacity planning in IP networks

• US 7,617,303 B2
• Filed: 04/27/2004
• Issued: 11/10/2009
• Est. Priority Date: 04/27/2004
• Status: Expired due to Fees

• Current Assignee: AT&T Corporation (AT&T, Inc.)
• Original Assignee: AT&T Intellectual Property I LP (AT&T, Inc.)
• Inventors: Duggirala, Somayajulu
• Primary Examiner(s): Follansbee; John
• Assistant Examiner(s): Daftuar; Saket K
• Application Number:
  US10/832,885
• Publication Number:
  US 20050240466A1
• Time in Patent Office: 2,023 Days
• Field of Search: 709/219, 709/223, 709/224, 709/225, 709/227, 703/2, 703/13, 703/21, 703/22, 703/23, 703/24, 705/10, 379 9- 10, 379 15- 17, 379 33- 34, 379111-113, 379/220, 379/269, 379/374
• US Class Current: 709/223
• CPC Class Codes: G06Q 10/06315 Needs-based resource requirements planning or analysis
• CPC Class Codes: G06Q 30/0202 Market predictions or forecasting for commercial activities
• CPC Class Codes: H04L 12/2856 Access arrangements, e.g. Internet access asynchronous transfer mode networks H04L12/5601; broadband local area networks H04L12/2801; optical access or distribution networks H04Q11/0067; access to open networks H04L12/5691; digital subscriber line end-user equipment and bit-level processing of data on a PSTN-based network H04M11/00; home network gateways H04L12/2834; wireless access networks H04W
• CPC Class Codes: H04L 41/147 for predicting network behaviour

Abstract

The present invention provides a method for avoiding demand forecast errors in a network topology model having a plurality of nodes, by monitoring and controlling the quantity of a selected port type at a node. The method comprises determining the actual quantity of a selected port type at a node, setting a forecast of the quantity of the port required, setting a forecast period for the ports, wherein the forecast period is a function of the time required to change the quantity of the ports, and setting a threshold value to generate alerts, wherein the threshold value is a function of the forecast period; monitoring the node for a forecast change, if a forecast change is found then computing the difference between the actual quantity and the forecast quantity, wherein if the difference is greater than the threshold value, then generating an alert and forwarding the alert to a user.

Claims

1. A system for avoiding demand forecast errors in a network topology model wherein the system monitors and controls quantity of a particular type of port at a node, the system comprising:

a memory;

(a) a user interface, wherein the system is configured via the user interface wherein a configuration comprises;

(i) setting a forecast period for ports at the node, wherein the forecast period is a function of the time required to change the quantity of a particular type of port at the node, and

(ii) setting a threshold value to generate alerts, wherein the threshold value is a function of the forecast period;

(b) an analytical module, wherein the analytical module monitors the node for a change in demand forecasted for the particular type of port;

(c) an alert engine, wherein the alert engine is activated by the analytical module if the analytical module detects a change in demand forecasted, wherein when the alert engine is alerted the alert engine computes difference between the demand forecasted and actual quantity of ports at the node, wherein upon detecting the difference is greater than the threshold value, the alert engine generates an alert, wherein the change in the demand forecasted is the addition or deletion of customer assignments at the node, or a change in quantity of the ports at the node, or a combination of both;

(d) an alert distributor, which receives the alert, wherein the alert distributor associates the alert with recipient information, and forwards the alert and recipient information to a user; and

(e) an alternate node component, wherein the alternate node component determines an optimal alternate node for a customer premise, wherein a planned node does not meet demand for a desired type of port, and wherein the optimal alternate node has excess capacity for the desired type of port;

wherein the optimal alternate node is determined by a method comprising;

(i) assigning a “

first access cost”

to each of a plurality of alternate nodes that are nearby the customer premise, wherein the “

first access cost”

is a function of the distance between the customer premise and the alternate node;

(ii) assigning a “

second access cost”

to each of the plurality of alternate nodes, wherein the “

second access cost”

is a function of the probability that the alternate node would not be able to accommodate demand from the customer premise; and

(iii) for each alternate node, calculating a “

total access cost,”

wherein the “

total access cost”

is the sum of the “

first access cost” and

the “

second access cost,”

wherein the optimal node is the node which has one of the lowest “

total access costs”

.

2. The system according to claim 1 wherein the change in the demand forecasted is the addition or deletion of customer assignments at the node, or a change in quantity of the ports at the node or a combination of both.

3. The system according to claim 1 wherein the alert comprises the identification of the node, type of the port, actual quantity of ports at the node, demand forecasted at the node, or combinations thereof.

4. The system according to claim 1 wherein the network topology model is an internet protocol backbone network.

5. A system according to claim 1 further comprising a re-home component, wherein the re-home component determines if re-homing is cost effective.

6. A method for avoiding demand forecast errors in a network topology model, having a plurality of nodes, by monitoring and controlling quantity of a particular type of port at a node, the method comprising:

(a) providing a system that comprises an user interface, an analytic module, an alert engine, an alert distributor, a contact manager, information of the actual quantity of a particular type of port at a node, and information of the demand forecast of the quantity of the type of port at the node;

(b) configuring the system via the user interface comprising

(i) setting a forecast period for the particular type of port at the node, wherein the forecast period is a function of the time required to change the quantity of the ports at the node, and

(ii) setting a threshold value to generate alerts, wherein the threshold value is a function of the forecast period;

(c) monitoring the node via the analytical module for a change in demand forecast for the type of port, wherein if a change in the demand forecast is detected then updating the demand forecast and go to step (d);

(d) activating the alert engine wherein the alert engine computes the difference between the updated demand forecast and actual quantity of the type of port at the node, wherein upon detecting the difference is greater than the threshold value, generating an alert and go to step (e);

(e) passing the alert to an alert distributor, wherein the alert distributor associates the alert with recipient information;

(f) forwarding the alert and the recipient information to a contact manager, wherein the network topology model can be reconfigured to avoid demand forecast errors; and

(g) determining an optimal alternate node for a customer premise, wherein a planned node does not meet the demand for a desired type of port, and wherein the optimal alternate node has excess capacity for the desired type of port, by a method comprising;

(i) assigning a “

first access cost”

to each of a plurality of alternate nodes that are nearby the customer premise, wherein the “

first access cost”

is a function of the distance between the customer premise and the alternate node;

(ii) assigning a “

second access cost”

to each of the plurality of alternate nodes, wherein the “

second access cost”

is a function of the probability that the alternate node would not be able to accommodate demand from the customer premise; and

(iii) for each alternate node, calculating the “

total access cost,”

wherein the “

total access cost”

is the sum of the “

first access cost” and

the “

second access cost,”

wherein the optimal node is the node which has one of the lowest “

total access costs”

.

7. The method according to claim 6 wherein the change in the demand forecast is the addition or deletion of customer assignments at a node, or a change in quantity of the ports at the node, or a combination of both.

8. An article of manufacture for avoiding demand forecast errors in a network topology model by monitoring and controlling quantity of a selected type of port at a node, the article comprising:

a machine readable storage medium, and a memory, containing one or more programs which when executed implement the steps of;

(a) setting of a threshold value to generate alerts, wherein the threshold value is a function of a forecast period, wherein a capacity at a node for a selected type of port is provided, and wherein a demand forecast of the type of port at the node for a forecast period is provided, and wherein the forecast period is a function of the time required to change the capacity at the node;

(b) monitoring a node for a change in a demand forecast, wherein if a change is detected then

(i) updating the demand forecast, and

(ii) computing the difference between the updated demand forecast and the capacity of the node, wherein if the difference is greater than a threshold value, then generating an alert, wherein the network topology model can be reconfigured to avoid demand forecast errors; and

(c) determining if re-homing a customer is cost effective, wherein customer demand was redirected from a planned node to an alternate node, comprising;

(i) assigning a “

cost of re-home,”

wherein the “

cost of re-home”

comprises cost of directing the customer demand to the planned node and cost of adding of new ports to the planned node;

(ii) providing a “

total access cost,”

wherein the “

total access cost”

is the sum of;

a “

first access cost,”

wherein the “

first access cost”

is a function of the distance between the customer and the alternate node, and a second access cost, wherein the “

second access cost”

is a function of the probability that the alternate node would not be able to accommodate demand from the customer; and

(iii) comparing the difference between the “

cost of re-home” and

the “

total access cost”

to a re-home threshold value, wherein the re-home threshold value is a monetary value, or a function of a such a value, and wherein an alert is generated if the comparison indicates that it is cost effective to re-home the customer.

9. An article of manufacture according to claim 8 for further determining an optimal alternate node for a customer premise, wherein a planned node does not meet demand for a desired type of port, and wherein the optimal alternate node has excess capacity for the desired type of port, the article further comprising:

a machine readable storage medium, and a memory, containing one or more programs which when executed implement the steps of;

(a) assigning a “

first access cost”

to each of a plurality of alternate nodes that are nearby the customer, wherein the “

first access cost”

is a function of the distance between the customer and the alternate node;

(b) assigning a “

second access cost”

to each of the plurality of alternate nodes, wherein the “

second access cost”

is a function of the probability that the alternate node would not be able to accommodate demand from the customer; and

(c) for each alternate node, calculating “

total access cost,”

wherein the “

total access cost”

is the sum of the “

first access cost” and

the “

second access cost,”

wherein the optimal node is the node which has one of the lowest “

total access costs”

.