Granted Patent B2

US 8,902,958 · App. 12/226,910 · Granted Dec 2, 2014

Abstract

Claims (80)

1. An apparatus comprising:

a programmable processor to execute machine instructions obtained from a memory of the programmable processor to implement a data collector, the data collector operative to:

receive first data indicative of at least one digital subscriber line (DSL) characteristic from a first data source;

receive second data indicative of at least one DSL characteristic from a second data source, the second data source being different than, and not connected or associated with, the first data source;

check the integrity of the first data and the second data; and

check the consistency of the first data and the second data; and

the programmable processor further to execute machine instructions obtained from the memory of the programmable processor to implement a data combiner, the data combiner operative to:

logically or heuristically combine the first data and the second data; and

probabilistically combine the first data and the second data to estimate at least one DSL characterizing parameter given at least one conditional probability.

2. An apparatus as in claim 1 , wherein the data combiner operative to probabilistically combine the first data and the second data is operative to probabilistically combine the first data and the second data according to Bayes' theorem.

3. An apparatus as in claim 1 , wherein the data collector comprises:

a data acquirer operative to receive the first data and the second data;

a data integrity checker operative to check the integrity of the first data and the second data;

a data preprocessor operative to preprocess an output of the data integrity checker; and

a data consistency checker operative to check the consistency of the output of the data preprocessor.

4. An apparatus as in claim 1 , further comprising a database operative to store the estimated at least one DSL characterizing parameter, and a data store operative to store the first data and the second data.

5. An apparatus as in claim 1 , further comprising a network management system operative to receive the at least one estimated DSL characterizing parameter and in response thereto perform at least one of: diagnose a fault, monitor a performance, estimate a performance, and determine a configuration parameter, of an associated DSL line.

6. An apparatus as in claim 1 , wherein the data combiner is operative to probabilistically combine the first data and the second data to estimate the DSL characterizing parameter by applying Bayes' theorem to estimate the DSL characterizing parameter given the at least one conditional probability.

7. An apparatus as in claim 1 , wherein the first data and the second data is received from at least a respectively different one of a plurality of data sources selected from a group of data sources consisting of: an auto-configuration server, a line tester system, an element management system, a service assurance system, a DSL access multiplexer, loop test equipment and a service delivery system.

8. An apparatus as in claim 1 , wherein at least one of: the first data and the second data includes at least one of: a time-domain reflectometry (TDR) signal, a loop attenuation, a signal attenuation, a signal-to-noise ratio, a loop insertion loss, a bridged tap presence, a bridged tap location, a bridged tap parameter, a quiet line noise, a crosstalk noise, a data rate, an error rate, a count of code violations, a count of errored seconds, a margin, a delay, a coding parameter and a loop transfer function.

9. An apparatus as in claim 1 , wherein the estimated DSL characterizing parameter is at least one of: a loop length, a loop impedance, a segment length, a cable gauge, a noise parameter, a short fault location, an open fault location, a cross fault location, a loop fault location, a bridged-tap presence, a bridged-tap location, a bridged-tap parameter, a loop attenuation, a signal-to-noise ratio, a loop insertion loss, a data rate, an error rate, a margin, a delay, a coding parameter, a loop transfer function, an impulse noise parameter, a network congestion, a spectrum management parameter, and a home distribution quality.

10. A computer-implemented method comprising:

collecting first data indicative of at least one DSL characteristic from a first data source;

collecting second data indicative of at least one DSL characteristic from a second data source, the second data source being different than, and unrelated to, the first data source;

checking the integrity of the first data and the second data;

checking the consistency of the first data and the second data;

logically or heuristically combining the first data and the second data; and

probabilistically combining the first data and the second data to estimate at least one DSL characterizing parameter given at least one conditional probability.

11. A method as in claim 10 , wherein the first data is collected at a customer premises and the second data is collected at a service provider location.

12. A method as in 10 , further comprising using the at least one estimated DSL characterizing parameter to at least one of: diagnose a fault, monitor a performance, estimate a performance, and determine a configuration parameter, of an associated DSL line.

13. A method as in claim 10 , wherein probabilistically combining comprises applying Bayes' theorem to estimate the at least one estimated DSL characterizing parameter given the first data, the second data, and the at least one conditional probability.

14. A method as in claim 10 , wherein:

the first data is an upstream attenuation;

the second data is a downstream attenuation; and

the at least one estimated DSL characterizing parameter is a presence of a bridged tap.

15. A method as in claim 10 , wherein:

the first data is a bit allocation of a first system;

the second data is a bit allocation of a second system; and

the at least one estimated DSL characterizing parameter is a bit allocation of a third system.

16. A method as in claim 10 , wherein:

the first data is a first channel transfer function from an element management system;

the second data is a second channel transfer function from an auto-configuration server; and

the at least one estimated DSL characterizing parameter is an estimated channel transfer function.

17. A method as in claim 10 , further comprising:

collecting third data indicative of a status of the first data; and

collecting fourth data indicative of a status of the second data, wherein the first data is a first signal-to-noise ratio from an element management system, the second data is a second signal-to-noise ratio from an auto-configuration server, and the at least one estimated DSL characterizing parameter is an estimated signal-to-noise ratio.

18. A method as in claim 10 , further comprising:

collecting third data indicative of a status of the first data; and

collecting fourth data indicative of a status of the second data, wherein the first data is a first channel transfer function from an element management system, the second data is a line test response, and the at least one estimated DSL characterizing parameter is a length of a bridged tap.

19. A method as in claim 10 , further comprising:

collecting third data indicative of a status of the first data;

collecting fourth data indicative of a status of the second data; and

collecting fifth data indicative of a time of data, wherein the first data is a number of code violations function from an element management system, the second data is moving picture experts group (MPEG) statistics, and the at least one estimated DSL characterizing parameter is a packet loss rate.

20. A method as in claim 10 , further comprising:

developing a Bayesian network representation, wherein probabilistically combining further comprises using the Bayesian network representation for the probabilistically combining.

21. A method as in claim 20 wherein developing a Bayesian network representation comprises:

selecting a set of parameters of a communication system that includes at least the first data, the second data and the at least one DSL characterizing parameter;

determining dependency relationships amongst the selected set of parameters; and

determining models of the dependency relationships.

22. A method as defined in claim 21 , further comprising:

assigning each parameter to a node of a graph; and

drawing edges of the graph based upon the dependency relationships.

23. An article of manufacture storing machine accessible instructions which, when executed, cause one or more machines to:

collect first data indicative of at least one DSL characteristic from a first data source;

collect second data indicative of at least one DSL characteristic from a second data source, the second data source being different than, and not connected or associated with, the first data source;

check the integrity of the first data and the second data;

check the consistency of the first data and the second data;

logically or heuristically combine the first data and the second data; and

probabilistically combine the first data and the second data to estimate at least one DSL characterizing parameter given at least one conditional probability.

24. An article of manufacture as in claim 23 , wherein the machine accessible instructions, when executed, cause the one or more machines to use the at least one estimated DSL characterizing parameter to at least one of: diagnose a fault, monitor a performance, estimate a performance, and determine a configuration parameter, of an associated DSL line.

25. An article of manufacture as in claim 23 , wherein probabilistically combining comprises applying Bayes' theorem to statistically estimate the at least one DSL characterizing parameter given at least the first data, the second data and the at least one conditional probability.

26. An apparatus comprising:

a programmable processor to execute machine instructions obtained from a memory of the programmable processor to implement a data collector combiner, the data collector combiner operative to:

receive first data indicative of at least one digital subscriber line (DSL) characteristic from a first data source;

receive second data indicative of at least one DSL characteristic from a second data source, the second data source being different than, and unrelated to, the first data source;

logically or heuristically combine the first data and the second data;

and

probabilistically combine at least the first data and the second data to estimate at least one DSL characterizing parameter, given at least one conditional probability, in response to a data integrity check of the first data and the second data.

27. An apparatus as defined in claim 26 , further comprising a network management system operative to receive the at least one estimated DSL characterizing parameter and in response thereto perform at least one of: diagnose a fault, monitor a performance, estimate a performance, and determine a configuration parameter, of an associated DSL line.

28. An apparatus as defined in claim 26 , wherein the data collector combiner is operative to probabilistically combine the first data and the second data to estimate the at least one DSL characterizing parameter by applying Bayes' theorem to estimate the DSL characterizing parameter given at least the first data, the second data and the at least one conditional probability.

Assignments (12)