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

• US 20050240466A1
• Filed: 04/27/2004
• Published: 10/27/2005
• Est. Priority Date: 04/27/2004
• Status: Active Grant

• Current Assignee: AT&T Corporation (AT&T, Inc.)
• Original Assignee: AT&T Corporation (AT&T, Inc.)
• Inventors: Duggirala, Somayajulu
• Granted Patent: US 7,617,303 B2
• Time in Patent Office: Days
• US Class Current: 705/10
• 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 method for avoiding demand forecast errors in a network topology model having a plurality of nodes, by monitoring and controlling the capacity of a node for a selected port type, the method comprising:

(a) providing information of the capacity at a node for a selected port type,

(b) providing information of the initial demand forecast for the port type at the node for a forecast period, wherein the forecast period is a function of the time required to change the capacity at the node,

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

(d) monitoring the node for a change in the 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, wherein if the difference is greater than the threshold value, then generating an alert, whereby the alert can be used to avoid demand forecast errors, wherein the method can be used to continuously monitor and control a network topology model.

2. The method according to claim 1 wherein the change in the demand forecast is the addition or deletion of customer assignments at a node, or the addition or deletion of a port at the node.

3. The method according to claim 1 further comprising associating the alert with recipient information.

4. The method according to claim 3 wherein the recipient information comprises the identification of monitored nodes, the port types at nodes, actual capacity at the node, demand forecast of ports at the node, or combinations thereof.

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

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

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

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

(c) an alert engine, wherein the engine is activated by the analytical module if the module detects a change in the demand forecasted, wherein when the engine is alerted the engine computes the difference between the demand forecasted and the actual quantity of ports at the node, wherein if the difference is greater than the threshold value, then the engine generates an alert; and

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

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

8. The system according to claim 6 wherein the alert comprises the identification of the monitored node, type of the port, actual quantity of ports at the node, forecasted demand at the node, or combinations thereof.

9. The system according to claim 6 wherein the network topology model is an internet protocol backbone network.

15. The system according to claim 6 further comprising an alternate node component, wherein the component determines an optimal alternate node for a customer premise, wherein the customer premise'"'"'s planned node does not meet the demand for a desired port type, and wherein the optimal alternate node has excess capacity for the desired port type, wherein the optimal alternate node is determined by a method comprising:

(a) assigning a first access cost to each of a plurality of alternate nodes that are nearby the customer premise, wherein the cost is a function of the distance between the customer premise 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 premise; and

(c) 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.”

19. A system according to claim 6 further comprising a re-home component, wherein the component determines if re-homing is cost effective.

10. 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 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 port type at a node, and information of the demand forecast of the quantity of the port type at the node,

(b) configuring the system via the user interface comprising

(i) setting a forecast period for the particular port type 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 the demand forecast for the port type, wherein if a forecast change is detected then update the demand forecast quantity and go to step (d), otherwise do nothing;

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

otherwise do nothing;

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

(f) forwarding the alert and recipient information to a contact manager, thereby avoiding demand forecast errors.

11. The method according to claim 10 wherein the forecast change is the addition or deletion of customer assignments at a node, or a change in quantity of the ports at the node.

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

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

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

(b) monitoring a node for a change in the 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, wherein if the difference is greater than the threshold value, then generating an alert, whereby the alert can be used to avoid demand forecast errors.

16. An article of manufacture according to claim 12 for additionally determining an optimal alternate node for a customer premise, wherein the customer premise'"'"'s planned node does not meet the demand for a desired port type, and wherein the optimal alternate node has excess capacity for the desired port type, the article further comprising:

a machine readable medium 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 premise, wherein the cost is a function of the distance between the customer premise 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 premise; and

(c) 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.”

20. An article of manufacture according to claim 12 for additionally determining if re-homing is cost effective, wherein the customer demand was redirected from a planned node to an alternate node, the article further comprising:

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

(a) assigning a “

cost of re-home,”

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

(b) providing a “

total access cost,”

wherein the cost is the sum of;

(i) a first access cost, wherein the first access cost is a function of the distance between the customer and the alternate node, and

(ii) 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 premise; and

(c) 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.

13. A method of determining an optimal alternate node for a customer premise, wherein the customer premise'"'"'s planned node does not meet the demand for a desired port type, and wherein the optimal alternate node has excess capacity for the desired port type, wherein the optimal alternate node is determined by a method comprising:

(a) assigning a first access cost to each of a plurality of alternate nodes that are nearby the customer premise, wherein the cost is a function of the distance between the customer premise 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 premise; and

(c) 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.”

14. A method according to claim 13 wherein the second access cost is calculated by the following method:

(a) determining the “

time for re-home,”

wherein the “

time for re-home”

is the forecasted time required for the planned node to be provided with the desired port type,

(b) determining the “

probability for spillover”

during the “

time for re-home”

for each alternate node, wherein the “

probability for spillover”

is calculated by the following method;

(i) determining the forecasted demand for each alternate node as if the customer premise had been directed to the alternate node, designated as “

alternate node with customer,”

(ii) determining the forecasted demand for each alternate node as if the customer premise had not been directed to the alternate node, designated as “

alternate node without customer” and

(iii) determining the actual capacity at each alternate node, wherein the “

probability for spillover”

for each alternate node is calculated by the following formula;

{(“

alternate node with customer”

) minus (the actual capacity at alternate node)}divided by (“

alternate node without customer”

),

(c) for each alternate node, determining the “

cost of spillover,”

wherein the “

cost of spill-over”

is calculated by;

determining the distance between the alternate node and the “

spill-over alternate node,”

wherein the “

spill-over alternate node”

is the alternate node for the alternate node, and multiplying the distance between the alternate node and the “

spill-over alternate node”

with the cost per mile, wherein the “

second access cost”

is the product of the “

probability of spill-over” and

the “

cost of spill-over.”

17. A method for determining whether it is cost effective to re-home a customer, wherein the customer demand was redirected from a planned node to an alternate node, the method comprising:

(a) providing a “

cost of re-home,”

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

(b) providing a “

total access cost,”

wherein the cost is the sum of;

(i) a first access cost, wherein the first access cost is a function of the distance between the customer and the alternate node, and

(ii) 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 premise; and

(c) 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.

18. A method according to claim 17 wherein the second access cost is calculated by the following method:

(a) determining the “

time for re-home,”

wherein the “

time for re-home”

is the forecasted time required for the planned node to be provided with the desired port type,

(b) determining the “

probability for spillover”

during the “

time for re-home”

for the alternate node, wherein the “

probability for spillover”

is calculated by the following method;

(i) determining the forecasted demand at the alternate node with the customer premise directed to the alternate node, designated as “

alternate node with customer,”

(ii) determining the forecasted demand at the alternate node without the customer premise being directed to the alternate node, designated as “

alternate node without customer” and

(iii) determining the actual capacity at the alternate node,

wherein the “

probability for spillover”

for the alternate node is calculated by the following formula;

{(“

alternate node with customer”

) minus (the actual capacity at alternate node)}divided by (“

alternate node without customer”

),

(c) determining the “

cost of spillover,”

wherein the “

cost of spill-over”

is calculated by;

determining the distance between the alternate node and the “

spill-over alternate node,”

wherein the “

spill-over alternate node”

is the alternate node for the alternate node, and multiplying the distance between the alternate node and the “

spill-over alternate node”

with the cost per mile,

wherein the “

second access cost”

is the product of the “

probability of spill-over” and

the “

cost of spill-over.”