DISTRIBUTED ACOUSTIC SENSING TO IDENTIFY NON-DISJOINT PATHS IN COMMUNICATIONS NETWORKS

1 . A system comprising:

a signal generator configured to transmit a signal into a fiber optic network, the fiber optic network comprising fiber optic devices distributed within a geographic region;

a receiver configured to receive a set of signals from the fiber optic network comprising at least first and second ones of the set of signals for respective first and second network segments;

a comparator coupled to the receiver, the comparator configured to compare the first and second ones of the set of signals to determine if a comparison exceeds a similarity threshold; and

a proximity device configured to, in response to the first and second ones of the set of signals exceeding the similarity threshold, determine a proximity measure between the first network segment and the second network segment,

wherein upon determining the proximity measure is less than a proximity threshold, classifying the first network segment and the second network segment as a pair of non-disjoint network segments.

2 . The system of claim 1 , further comprising:

a network device configured to determine a first fiber path and a second fiber path, each comprising a plurality of network segments of the fiber-optic network, between a source and a destination such that if the first fiber path includes the first network segment the second fiber path does not include the second network segment.

3 . The system of claim 1 , wherein, to determine whether the comparison exceeds the similarity threshold, the comparator is further configured to:

normalize the first and second ones of the set of signals to eliminate variability between the first and second ones of the set of signals due to a difference in lengths of the first network segment and the second network segment; and

determine a correlation coefficient between normalized first one of the set of signals and normalized second one of the set of signals.

4 . The system of claim 3 , wherein the first and second ones of the set of signals are normalized using a dynamic time warping technique.

5 . The system of claim 1 , wherein, to determine whether the comparison exceeds the similarity threshold, the comparator is further configured to:

normalize the first and second ones of the set of signals to eliminate variability between the first and second ones of the set of signals due to a difference in types of fiber of the first network segment and the second network segment; and

determine a correlation coefficient between normalized first one of the set of signals and normalized second one of the set of signals.

6 . The system of claim 1 , wherein the fiber optic devices are a set of fiber-optic acoustic sensing devices.

7 . The system of claim 1 , wherein the set of signals are a set of time-domain (TD) signatures received from a plurality of fiber-optic acoustic sensing devices distributed within a geographic area.

8 . The system of claim 1 , wherein the proximity measure between the first network segment and the second network segment is determined based on a keyhole markup language zipped (KMZ) file.

9 . The system of claim 1 , wherein, to receive the set of signals, the receiver is further configured to:

configure each of the fiber optic devices to:

transmit a reference optical signal over a respective fiber-optic network segment within a geographic area;

determine a respective signal based on reflected and back-scattered optical signals; and

transmit the set of signals to a distributed acoustic sensing control unit of the receiver.

10 . A method, comprising:

transmitting, using a signal generator, a signal into a fiber optic network, the fiber optic network comprising fiber optic devices distributed within a geographic region;

receiving, using a receiver, a set of signals from the fiber optic network comprising at least first and second ones of the set of signals for respective first and second network segments;

comparing, using a comparator coupled to the receiver, the first and second ones of the set of signals to determine if a comparison exceeds a similarity threshold;

determining a proximity measure, using a proximity device, in response to the first and second ones of the set of signals exceeding the similarity threshold, between the first network segment and the second network segment; and

determining, based on determining the proximity measure is less than a proximity threshold, the first network segment and the second network segment as a pair of non-disjoint network segments.

11 . The method of claim 10 , further comprising:

configuring a first fiber path and a second fiber path, each comprising a plurality of network segments of the fiber-optic network, between a source and a destination such that if the first fiber path includes the first network segment, the second fiber path does not include the second network segment.

12 . The method of claim 10 , wherein, the determining whether the comparison exceeds the similarity threshold further comprises:

normalizing the first and second ones of the set of signals to eliminate variability between the first and second ones of the set of signals due to a difference in lengths of the first network segment and the second network segment; and

determining a correlation coefficient between normalized first one of the set of signals and normalized second one of the set of signals.

13 . The method of claim 12 , wherein the first and second ones of the set of signals are normalized using a dynamic time warping technique.

14 . The method of claim 10 , wherein, the determining whether the comparison exceeds the similarity threshold further comprises:

normalizing the first and second ones of the set of signals to eliminate variability between the first and second ones of the set of signals due to a difference in types of fiber of the first network segment and the second network segment; and

determining a correlation coefficient between normalized first one of the set of signals and normalized second one of the set of signals.

15 . The method of claim 10 , wherein the proximity measure between the first network segment and the second network segment is determined based on a keyhole markup language zipped (KMZ) file.

16 . A non-transitory computer-readable medium (CRM) having instructions stored thereon that, when executed by at least one computing device, causes the at least one computing device to perform operations comprising:

transmitting, using a signal generator, a signal into a fiber optic network, the fiber optic network comprising fiber optic devices distributed within a geographic region;

receiving, using a receiver, a set of signals from the fiber optic network comprising at least first and second ones of the set of signals for respective first and second network segments;

comparing, using a comparator coupled to the receiver, the first and second ones of the set of signals to determine if a comparison exceeds a similarity threshold;

determining a proximity measure, using a proximity device, in response to the first and second ones of the set of signals exceeding the similarity threshold, between the first network segment and the second network segment; and

determining, based on determining the proximity measure is less than a proximity threshold, the first network segment and the second network segment as a pair of non-disjoint network segments.

17 . The non-transitory CRM of claim 16 , the operations further comprising:

configuring a first fiber path and a second fiber path, each comprising a plurality of network segments of the fiber-optic network, between a source and a destination such that if the first fiber path includes the first network segment, the second fiber path does not include the second network segment.

18 . The non-transitory CRM of claim 16 , wherein, the determining whether the comparison exceeds the similarity threshold further comprises:

normalizing the first and second ones of the set of signals to eliminate variability between the first and second ones of the set of signals due to a difference in lengths of the first network segment and the second network segment; and

determining a correlation coefficient between normalized first one of the set of signals and normalized second one of the set of signals.

19 . The non-transitory CRM of claim 18 , wherein the first and second ones of the set of signals are normalized using a dynamic time warping technique.

20 . The non-transitory CRM of claim 16 , wherein the proximity measure between the first network segment and the second network segment is determined based on a keyhole markup language zipped (KMZ) file